WO2014208662A1 - Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium - Google Patents

Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium Download PDF

Info

Publication number
WO2014208662A1
WO2014208662A1 PCT/JP2014/066974 JP2014066974W WO2014208662A1 WO 2014208662 A1 WO2014208662 A1 WO 2014208662A1 JP 2014066974 W JP2014066974 W JP 2014066974W WO 2014208662 A1 WO2014208662 A1 WO 2014208662A1
Authority
WO
WIPO (PCT)
Prior art keywords
content
information
sales promotion
promotion effect
effect estimation
Prior art date
Application number
PCT/JP2014/066974
Other languages
French (fr)
Japanese (ja)
Inventor
広明 近藤
小笠原 大樹
Original Assignee
シャープ株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by シャープ株式会社 filed Critical シャープ株式会社
Publication of WO2014208662A1 publication Critical patent/WO2014208662A1/en

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0211Determining the effectiveness of discounts or incentives

Definitions

  • the present invention relates to a sales promotion effect estimation method, a sales promotion effect estimation device, a sales promotion effect estimation system, and a recording medium.
  • the automatic product order processing system of Patent Document 1 extracts the product introduced in the television program from the program data of the television program before airing, calculates the order quantity of the extracted product, and calculates The product is automatically ordered with the ordered quantity.
  • the automatic merchandise order processing system described in Patent Document 1 uses program data of a television program before broadcasting. Therefore, the details of the contents of the television program are not known, and the sales promotion (sales promotion) effect necessary to calculate a suitable order quantity cannot be accurately predicted. In addition, if the television program is a live broadcast, or if the television program is not broadcast due to an extension of a baseball broadcast or the like, it is not only difficult to predict the sales promotion effect with this product automatic order processing system, but also the sales promotion. The effect may be overestimated or underestimated.
  • One aspect of the present invention is to provide a sales promotion effect estimation method capable of more appropriately estimating the sales promotion effect of content including information related to a product.
  • One aspect of the present invention relates to content content information describing the content of broadcast content, and relates to an event occurrence period that indicates a period in which an event that is at least a part of a program is occurring, and a product related to the event
  • Content content information including information and content information is specified, content related to the event occurrence period is specified based on information about the product, and viewing history information of the content related to the specified event occurrence period
  • reading correspondence information that associates the viewing history information with the estimated value from the storage unit, and based on the obtained viewing history information, the effect of promoting the sale of the product played by the content related to the event occurrence period is obtained. It is the sales promotion effect estimation method which calculates the said estimated value to show.
  • a sales promotion effect estimation method that can more appropriately estimate the sales promotion effect of content including information related to a product.
  • FIG. 1 is a diagram illustrating a usage situation of the sales promotion effect estimation system according to the first embodiment.
  • the sales promotion effect estimation system 1 includes a handy terminal 2, a store apparatus 3, a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server. 10 is included.
  • a handy terminal 2 a store apparatus 3, a store product server 5, and a store product supplement server 6 are installed in the store “Shp”.
  • the store apparatus 3, the store product server 5, and the store product supplement server 6 are connected to be communicable via a network such as a LAN (Local Area Network). Further, the handy terminal 2 is connected to the store apparatus 3 so as to be communicable with a wireless LAN or the like, for example.
  • the network NW is, for example, a network such as the Internet or a mobile communication network, but is not limited thereto.
  • the network NW may be an intranet, a dedicated line, or the like, or an information communication network configured by a combination thereof.
  • a store device 3 a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server 10 are connected to the network NW.
  • NW a state where they can communicate with each other.
  • the sales promotion effect estimation server 4 includes, for example, information relating to products that can be handled by the store “Shp”, or information that will be handled in the future (hereinafter referred to as store products), and content that includes information related to store products (hereinafter referred to as introduction content). ) (For example, a television program name, a radio program name, a broadcast date, etc. of the introduction content) is acquired from various servers connected to the network NW. Acquisition of introduction content will be described later.
  • Store merchandise is, for example, food, clothing, or electrical appliances.
  • the content is, for example, a television program or a radio program itself.
  • the content is content that is divided when a television program broadcast by a television broadcast station is divided by time, a corner in a television program, or a time zone that spans multiple television programs. May be.
  • the content may be content that is divided when a radio program broadcast by a radio broadcasting station is divided by time, a corner in the radio program, or a time zone that spans multiple radio programs.
  • the content including information related to the store product includes, for example, content that introduces the store product, content that shows the store product, and content in which the name of the store product appears.
  • the case where the content including information related to the store product is content in which the store product is introduced will be described.
  • the sales promotion effect estimation server 4 performs the following processes for every store product.
  • the sales promotion effect estimation server 4 estimates an effect (hereinafter referred to as a sales promotion effect) of promoting sales by the introduction content for the store product based on the acquired information on the store product and information accompanying the introduction content.
  • the sales promotion effect estimation server 4 uses a coefficient indicating the estimated sales promotion effect and a normal order quantity (hereinafter referred to as a normal order quantity) of the store product acquired from the POS server 7 to obtain a suitable order quantity (hereinafter referred to as a preferred order quantity). Calculate the order quantity). Further, the sales promotion effect estimation server 4 generates information (hereinafter referred to as introduction information) indicating that the store product has been introduced in the introduction content based on the information accompanying the introduction content.
  • introduction information information indicating that the store product has been introduced in the introduction content based on the information accompanying the introduction content.
  • the sales promotion effect estimation server 4 outputs the calculated preferred order quantity and the generated introduction information to the store apparatus 3. Further, the sales promotion effect estimation server 4 generates a sales promotion effect information image in which information associated with the introduction content that is considered to have influenced the sales promotion effect is generated based on the acquired information on the store product and the information on the introduction content. To do. The sales promotion effect estimation server 4 outputs the generated sales promotion effect information image to the store apparatus 3 as necessary in accordance with an operation (request) from the store apparatus 3.
  • FIG. 2 is a diagram illustrating an example of a sales promotion effect information image according to the first embodiment.
  • the sales promotion effect information image “img” is composed of, for example, images p1 to p11.
  • the sales promotion effect estimation server 4 generates, as an image p1, an introduction content information image that displays information on the introduction content having the highest audience rating among the introduction contents that are considered to have influenced the sales promotion effect of the store product.
  • the audience rating may be the national audience rating or the audience rating in the area including the store “Shp” (hereinafter referred to as the regional audience rating).
  • the audience rating may be a combination of the national audience rating and the regional audience rating, with priority given to either the national audience rating or the local audience rating.
  • the sales promotion effect estimation server 4 generates a national audience rating image displaying the national audience rating as an image p2.
  • the sales promotion effect estimation server 4 generates a regional audience rating image displaying the regional audience rating as an image p3.
  • the sales promotion effect estimation server 4 produces
  • the sales promotion effect estimation server 4 produces
  • the sales promotion effect estimation server 4 generates a viewing exposure time graph for a predetermined period as an image p6. Details of the viewing exposure time graph will be described later.
  • the sales promotion effect estimation server 4 generates an order quantity image that displays the normal order quantity and the preferred order quantity as an image p7.
  • the sales promotion effect estimation server 4 acquires a moving image of the introduction content from the content recording server 10, and generates a captured image obtained by capturing the acquired moving image as an image p8.
  • the sales promotion effect estimation server 4 generates, as an image p9, an area exposure time image that displays the accumulated time that the store product appears in the content broadcast in the area including the store “Shp”.
  • the sales promotion effect estimation server 4 is obtained by multiplying the cumulative time when the store product appears in the introduction content broadcast in the area including the store “Shp” by the number of television receivers viewing the introduction content.
  • a total viewing time image displaying the total viewing time is generated as an image p10.
  • the sales promotion effect estimation server 4 generates, as an image p11, an introductory content detail image that displays the local audience rating of each introductory content together with the introductory content that ranks in the top three. Details of generation of the sales promotion effect information image “img” will be described later.
  • the store apparatus 3 is, for example, a computer in which a POS (Point Of Sale) application is installed. Further, the store apparatus 3 includes, for example, an input device such as a barcode reader or a keyboard, and a display device such as an operator display (operation display) or a customer display (customer display). The store apparatus 3 reads a barcode attached to a product (a product ID or the like is recorded) with a barcode reader. Further, the store apparatus 3 accepts input of necessary information such as an order amount through a keyboard. The store apparatus 3 acquires the preferred order quantity of the store product and the introduction information from the sales promotion effect estimation server 4 via the network NW. Further, the store apparatus 3 acquires information related to store products and the above-described normal order quantity from the POS server 7.
  • an input device such as a barcode reader or a keyboard
  • a display device such as an operator display (operation display) or a customer display (customer display).
  • the store apparatus 3 reads a barcode attached to a product (a product ID or the
  • the store apparatus 3 generates an order screen for the store product based on the acquired information about the store product, the preferred order quantity, and the introduction information.
  • the store apparatus 3 receives an operation for displaying an order screen for a store product selected by a user (for example, a store operator)
  • the store device 3 is generated if the store product selected by the user is a product introduced in the introduction content. Display the ordering screen.
  • the store apparatus 3 displays the order screen generated based on the acquired normal order quantity on the display of the store apparatus 3 as a default screen. To do.
  • the shop apparatus 3 demonstrated the case where the information regarding shop goods and the normal order quantity were acquired from the POS server 7, it is not restricted to this.
  • the user may input information related to store products and the normal order quantity with a keyboard or the like.
  • FIG. 3 is a diagram illustrating an example of an ordering screen according to the first embodiment.
  • the store apparatus 3 generates an ordering screen “order” in which the acquired preferred order quantity is displayed in the order quantity “size”, and generates an alert image “ntc” based on the acquired introduction information.
  • the alert image “ntc” is arranged as shown in FIG.
  • a detail button “btn” is arranged in the alert image “ntc”.
  • the sales promotion effect estimation server 4 acquires the sales promotion effect information image “img” for the store product from the sales promotion effect estimation server 4, and acquires the acquired sales promotion effect information image “img”. It is displayed on the display of the store apparatus 3.
  • the store apparatus 3 may output a sound when the sales promotion effect information image “img” is accompanied by a sound.
  • the store apparatus 3 places an order by the user selecting and determining the order button on the order screen “order”.
  • the present invention is not limited to this.
  • the store apparatus 3 may automatically place an order for the acquired preferred order quantity without any user operation.
  • the store apparatus 3 extracts the audience rating of the introduction content from the acquired introduction information, and when the extracted audience rating exceeds a predetermined threshold, for example, the order amount of the store product introduced by the introduction content is increased. An alert image for prompting is generated, and the generated alert image is output to the handy terminal 2 and displayed.
  • the store apparatus 3 extracts the rate of change of the viewing rate of the introduction content from the introduction information, and if the extracted rate of change exceeds a predetermined threshold, the order amount of the store product introduced by the introduction content is increased. An alert image that prompts the user may be generated. Further, the store apparatus 3 acquires the coefficient indicating the sales promotion effect described above, determines whether or not the acquired coefficient indicating the sales promotion effect exceeds a predetermined threshold, and generates an alert image based on the determination result. Good.
  • FIG. 4 is a diagram illustrating an example of an alert image according to the first embodiment.
  • the predetermined threshold value may be set in advance or may be set later by the user. Further, when the extracted audience rating exceeds a predetermined threshold, the store apparatus 3 may generate an alert image “alrt” immediately after that and output the generated alert image “alrt” to the handy terminal 2. However, it is not limited to this.
  • the store apparatus 3 displays information that prompts the customer to increase the order quantity of store products corresponding to the audience rating that exceeds a given threshold during the day until the given time of the day. Report images arranged in descending order may be generated, and the generated report images may be output to the handy terminal 2.
  • FIG. 5 in the first embodiment is a diagram illustrating an example of a report image.
  • the handy terminal 2 is a portable information terminal such as a business PDA (Personal Digital Assistant).
  • the handy terminal 2 acquires the alert screen or the report image “rprt” from the store apparatus 3, the handy terminal 2 displays the acquired image on the display, and adjusts the order quantity of the store product introduced to the user by the sales promotion program (for example, Increase order volume).
  • FIG. 6 is an example of a diagram in which an alert screen “alrt” is displayed on the handy terminal 2 in the first embodiment.
  • the POS server 7 is a server that controls the POS system.
  • the POS server 7 receives product IDs from various servers and devices, and searches for store product information (hereinafter referred to as product information) such as store products indicated by the received product IDs, store product prices, and normal order quantities of store products. Then, the retrieved product information is output to various servers and devices.
  • product information store product information
  • the store product server 5 stores a store product table.
  • FIG. 7 is an example of the store product table t51 stored in the store product server 5 in the first embodiment.
  • the store product table t51 stores, for example, a product ID for identifying a store product, a product name, a place of production, a price of the product, and the like, but is not limited thereto.
  • the store product table t51 may store the number of items in stock, the quantity already ordered, the sales target achievement rate, and the like.
  • the store product supplement server 6 stores supplement information associated with various product names and / or product IDs stored in the store product table t51 as a supplement information table.
  • supplementary information is described as being associated with both a product ID and a product name, but may be associated with either one.
  • the supplemental information is, for example, a keyword related to a product (hereinafter referred to as a product keyword).
  • the product keyword is, for example, a product type corresponding to the product name. Specifically, the product keyword corresponds to a variety or the like when the product is food, and a brand name or the like when the product is clothing.
  • a case where one product keyword is associated with each product name will be described.
  • the present invention is not limited to this, and a plurality of product keywords are associated with one product. May be associated.
  • FIG. 8 is a diagram illustrating an example of the supplement information table t61 stored in the store product supplement server 6 according to the first embodiment.
  • the supplementary information table t61 stores a product keyword associated with the product ID and the product name. Further, the supplementary information table t61 is associated with the store product table t51 of FIG. 7 through the product ID and the product name.
  • the viewing log server 8 stores viewing logs collected from television receivers nationwide.
  • the viewing log is information that stores, for example, a broadcast station identification ID that identifies a broadcast station that has been viewed and a time when the content is broadcast.
  • the viewing log is collected from a television receiver for each country or region where the viewing log can be collected. Note that the viewing log may be recorded not only as a real-time viewing log but also as a view when the content is recorded or reserved for recording when viewing the content by the television receiver.
  • the content information server 9 stores information on the contents of various contents broadcast to television receivers nationwide (hereinafter referred to as content information) as a content information table.
  • the content information is, for example, information describing content details.
  • the content information is information in which content and information related to an event (hereinafter referred to as an event) occurring in the content are associated with each other.
  • FIG. 9 is a diagram illustrating an example of the content information table t91 stored in the content information server 9 according to the first embodiment.
  • the content information table t91 includes, for each record, an identification ID, an event start time, an event end time, content (television program name), a corner name when an event occurs (hereinafter referred to as an event inclusion corner), and the contents of the event.
  • Information to be represented hereinafter referred to as event content information
  • a broadcast station ID are stored in association with each other.
  • the content information is given an identification ID for identifying the information.
  • an event indicates an event such as a speech made by a performer or a video stream.
  • Information related to events includes, for example, the time at which an event occurred (hereinafter referred to as event start time), the time at which the event ended (hereinafter referred to as event end time), event content information, event inclusion corner, And information describing a broadcasting station ID for identifying a broadcasting station broadcasting a television program in which an event has occurred.
  • Event content information includes, for example, the name of the store introduced during the event, the name of the product, the remarks of the performer reflected during the event, the name of the performer, the movement of the performer, the facial expression of the performer, etc. Is recorded as text information.
  • the content information table t91 actually stores all the content information corresponding to the content broadcast in the whole country or region.
  • the content recording server 10 records the content broadcast by each television broadcasting station nationwide and stores it as a content video that is a video for each content.
  • the content recording server 10 transmits the content video to the sales promotion effect estimation server 4 in accordance with the content video acquisition request from the sales promotion effect estimation server 4.
  • FIG. 10 is a schematic block diagram showing an example of the configuration of the sales promotion effect estimation server 4 in the first embodiment.
  • the sales promotion effect estimation server 4 includes, for example, a communication unit 101, a store product acquisition unit 102, a product supplement information acquisition unit 104, an introduction content specification information acquisition unit 105, an introduction content specification information storage unit 106, an audience rating calculation unit 107, and a suitable content.
  • a quantity calculation unit 116 is included.
  • the communication unit 101 is, for example, a network card, and communicates with various servers through a LAN or a network NW. In addition, the communication unit 101 responds to an instruction (request) from the product supplement information acquisition unit 104, the introduction content specifying information acquisition unit 105, the normal order quantity acquisition unit 111, etc., the store product server 5, the store product supplement server 6, It communicates with each of the POS server 7, the viewing log server 8, the content information server 9, and the content recording server 10.
  • an instruction from the product supplement information acquisition unit 104, the introduction content specifying information acquisition unit 105, the normal order quantity acquisition unit 111, etc., the store product server 5, the store product supplement server 6, It communicates with each of the POS server 7, the viewing log server 8, the content information server 9, and the content recording server 10.
  • the store product acquisition unit 102 acquires, for example, the store product table t51 from the store product server 5, selects one product ID from the acquired store product table t51 one by one, and selects the selected product ID as a store product supplement information acquisition unit. To 104.
  • the store product acquisition unit 102 outputs the acquired product ID to the product supplement information acquisition unit 104.
  • the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplementary information acquisition unit 104. However, when there are a plurality of product IDs, the same processing is performed for each product ID. Run repeatedly.
  • the store product acquisition unit 102 acquires the store product table t51 from the store product server 5 and selects the product IDs one by one from the acquired store product table t51.
  • the store product acquisition unit 102 acquires, for example, a store product that the user is trying to place an order from the store apparatus 3, searches the store product server 5 for the product ID of the acquired store product, and acquires the acquired product ID. , It may be output to the store product supplement information acquisition unit 104.
  • the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplemental information acquisition unit 104. However, when there are a plurality of product IDs, the following processing is repeatedly executed.
  • the product supplement information acquisition unit 104 acquires supplement information (product keyword) associated with the acquired product ID from the store product supplement server 6, for example.
  • the product supplementary information acquisition unit 104 outputs the acquired product keyword to the introduction content specifying information acquisition unit 105.
  • the introductory content specifying information acquisition unit 105 acquires information (hereinafter referred to as introductory content specifying information) for specifying the content associated with the event detail information including the acquired product keyword from the content information server 9.
  • introductory content specifying information information for specifying the content associated with the event detail information including the acquired product keyword
  • the introduction content is content specified by a television program name
  • the keyword “strawberry” is included as event content information.
  • this “strawberry” is the product keyword of the sales promotion product, information included in this record is acquired as introduction content specifying information.
  • FIG. 11 is a diagram illustrating an example of the introduction content identification information table t1051 that stores the introduction content identification information acquired by the introduction content identification information acquisition unit 105 according to the first embodiment.
  • the introduction content specifying information table t1051 is a table obtained by extracting the content including the product keyword from the content information table t91 illustrated in FIG. 9.
  • the introduction content specific information acquisition unit 105 stores the acquired introduction content specification information in the introduction content specification information storage unit 106 as an introduction content specification information table t1051.
  • the introduction content specifying information storage unit 106 is a RAM (Random Access Memory), a register, or a recording medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive).
  • the introductory content specific information storage unit 106 stores an introductory content specific information table t1051.
  • the audience rating calculation unit 107 reads the introduction content identification information table t1051 from the introduction content identification information storage unit 106.
  • the audience rating calculation unit 107 acquires the viewing log of the introduction content from the viewing log server 8 based on the read introduction content specifying information table t1051.
  • the audience rating calculation unit 107 calculates the audience rating of the introduction content based on the acquired viewing log, and generates a content audience rating table.
  • FIG. 12 is an example of the content audience rating table t1071 in the first embodiment.
  • the content audience rating table t1071 stores the event inclusion corner including the introduction content, the television program name as the introduction content specifying information, the event start time and the event end time, and the national audience rating and the local audience rating of the introduction content. To do. Details of the audience rating calculation process will be described later. Note that the audience rating calculation unit 107 has been described for calculating the audience rating, but the present invention is not limited to this. For example, the audience rating calculation unit 107 may calculate the rate of change of the audience rating. In this case, the content audience rating table t1071 stores the audience rating change rate together with the audience rating. The audience rating calculation unit 107 outputs the generated content audience rating table t1071 to the preferred content selection unit 108.
  • the audience rating calculation unit 107 calculates the audience rating of the introductory content, but is not limited to this, and the audience rating of the event inclusion corner including the introductory content may be calculated. In that case, the audience rating calculation unit 107 acquires the viewing log of the event inclusion corner including the introduction content from the viewing log server 8 based on the introduction content specifying information.
  • the suitable content selection unit 108 selects introduction contents one by one from the acquired content audience rating table t1071.
  • the preferred content selection unit 108 reads event content information corresponding to the selected introduction content from the introduction content specifying information storage unit 106.
  • the preferred content selection unit 108 performs natural language analysis on the read event content information.
  • the preferred content selection unit 108 determines whether or not the selected introduction content is associated with event content information (hereinafter referred to as negative content information) including a word pronounced of a negative impression through the natural language analysis (hereinafter referred to as negative content information). , Called negative impression determination).
  • the suitable content selection unit 108 excludes all records including the selected introduction content from the content audience rating table t1071 (hereinafter referred to as table optimization processing). ).
  • the preferred content selection unit 108 performs a negative impression determination on all the introduction contents in the content audience rating table t1071, and then uses the content audience rating table in which records remaining without being excluded are stored in the preferred content viewing table. It outputs to the sales promotion effect estimation part 110 as a rate table.
  • the sales promotion effect estimation unit 110 extracts introduction content specifying information having the highest local audience rating from the acquired preferred content audience rating table.
  • the sales promotion effect estimation unit 110 selects the introduction content indicated by the extracted introduction content specifying information as content (hereinafter referred to as sales promotion content) that is a main information source for calculating the preferred order quantity.
  • sales promotion content content
  • the sales promotion effect estimation unit 110 calculates a coefficient indicating the sales promotion effect based on the selected sales promotion content and user input information.
  • the user input information is information used when calculating a coefficient indicating the sales promotion effect, and is an expected audience rating of the sales promotion content predicted by the mass media before the sales promotion content is broadcast.
  • the sales promotion effect estimation unit 110 acquires user input information from the user input information storage unit 115.
  • the sales promotion effect estimation unit 110 obtains various other information necessary for calculating a coefficient indicating the sales promotion effect from various servers or a website on the Internet via the communication unit 101. Details of the calculation of the coefficient indicating the sales promotion effect will be described later.
  • the sales promotion effect estimation unit 110 outputs a coefficient indicating the calculated sales promotion effect to the preferred order quantity calculation unit 116.
  • the user input information is the expected audience rating
  • the present invention is not limited to this and may be the expected number of viewing televisions, the expected number of viewers, and the like.
  • the predicted audience rate, the expected number of viewers, and the expected number of viewers here are examples of values for predicting the degree of content viewing in the claims.
  • the preferred order quantity calculation unit 116 calculates the preferred order quantity based on the calculated coefficient indicating the sales promotion effect.
  • the preferred order quantity calculation unit 116 calculates the preferred order quantity by multiplying the normal order quantity by a coefficient indicating the calculated sales promotion effect.
  • the preferred order quantity calculation unit 116 acquires the product information from the normal order quantity acquisition unit 111, and extracts the normal order quantity from the acquired product information.
  • the preferred order quantity calculation unit 116 outputs the calculated preferred order quantity to the store apparatus 3 via the communication unit 101.
  • the preferred order quantity calculation unit 116 also outputs the calculated preferred order quantity, the extracted normal order quantity, and the preferred content audience rating table to the sales promotion effect information image generation unit 112.
  • the normal order quantity acquisition unit 111 acquires the store product table t51 from the store product server 5, extracts the product ID from the acquired store product table t51, and outputs the extracted product ID to the POS server 7.
  • the product information of the store product indicated by the product ID is acquired from the POS server 7.
  • the normal order quantity acquisition unit 111 outputs the acquired product information to the preferred order quantity calculation unit 116.
  • the user input information reception unit 114 receives user input information, for example, by an operation from the user.
  • the user input information reception unit 114 causes the user input information storage unit 115 to store the received user input information.
  • the user input information storage unit 115 is, for example, a RAM, a register, or a recording medium such as an HDD or an SSD.
  • the user input information storage unit 115 stores user input information.
  • the sales promotion effect information image generation unit 112 acquires a preferred order quantity, a normal order quantity, and a preferred content audience rating table from the preferred order quantity calculation unit 116.
  • the sales promotion effect information image generation unit 112 acquires the introduction content identification information table t1051 from the introduction content identification information storage unit 106.
  • the sales promotion effect information image generation unit 112 generates a sales promotion effect information image based on the acquired preferred order quantity, normal order quantity, preferred content audience rating table, and introduction content specifying information table t1051.
  • the sales promotion effect information image generation unit 112 stores the generated sales promotion effect information image in the sales promotion effect information image storage unit 113.
  • the sales promotion effect information image storage unit 113 is a recording medium such as an HDD or an SSD.
  • the sales promotion effect information image storage unit 113 stores a sales promotion effect information image.
  • the store apparatus 3 reads the sales promotion effect information image from the sales promotion effect information image storage unit 113, for example, when displaying the sales promotion effect information image.
  • FIG. 13 is a sequence diagram for explaining operations until the introduction content specifying information acquisition unit 105, the audience rating calculation unit 107, and the preferred content selection unit 108 generate a preferred content audience rating table according to the first embodiment. It is an example.
  • the introductory content specific information acquisition unit 105 acquires a product keyword of a sales promotion product (ST100).
  • the introduction content specifying information acquisition unit 105 acquires the introduction content specifying information table t1051 based on the product keyword (ST101).
  • introductory content specific information acquisition section 105 outputs introductory content specific information table t1051 to audience rating calculation section 107 (ST102).
  • the audience rating calculation unit 107 selects introduction contents one by one from the acquired introduction content specifying information table t1051, and calculates the national audience rating and the regional audience rating of the selected introduction content (ST103). Details of the audience rating calculation will be described later.
  • audience rating calculation section 107 generates content audience rating table t1071 (ST104).
  • audience rating calculation section 107 outputs content audience rating table t1071 to content selection section 108 (ST105).
  • the preferred content selection unit 108 repeatedly performs the processing from ST107 to ST108 for each record in the content audience rating table t1071 (ST106, ST109).
  • the preferred content selection unit 108 performs negative impression determination (ST107).
  • the preferred content selection unit 108 transitions to ST108.
  • the preferred content selection unit 108 performs the process of ST107 on the next record.
  • the suitable content selection unit 108 performs table optimization processing (ST108).
  • FIG. 14 is an example of a flowchart for explaining the operation of the audience rating calculation unit 107 in the first embodiment calculating the national audience rating and the local audience rating of the introduction content in ST103 of FIG.
  • the audience rating calculation unit 107 acquires the introduction content specifying information table t1051 (ST200).
  • the audience rating calculation unit 107 acquires a viewing log of the introduction content (ST201).
  • audience rating calculation section 107 repeatedly executes the processing from ST203 to ST206 for each introduction content in introduction content identification information table t1051 (ST202, ST207).
  • the audience rating calculation unit 107 determines whether or not the introduction content has ended (ST203). When the introduction content has already ended (ST203-Yes), the audience rating calculation unit 107 transitions to ST204. When the introduction content has not yet ended (ST203-No), the audience rating calculation unit 107 performs the process of ST203 on the next introduction content.
  • the audience rating calculation unit 107 divides the broadcast time of the introduction content into predetermined time intervals, and the television receiver that has watched the introduction content for each divided time interval. The total number of machines in the whole country and region is counted, and the total is calculated by summing up the number of machines counted for each divided time interval (ST204).
  • the predetermined time interval is a one-minute interval in order to obtain the number of viewers per unit time.
  • the audience rating calculation unit 107 divides the total number in ST204 by the broadcasting time of the introduction content, and the national and regional data per unit time (in the case of the first embodiment, per minute). The average number of viewers is calculated (ST205). Next, the audience rating calculation unit 107 calculates the average number of viewers in the whole country and region, the number of all television receivers that can collect viewing logs in the whole country, and all televisions that can collect viewing logs in the region. By dividing by the number of John receivers, the national audience rating and regional audience rating of the introduction content are calculated (ST206).
  • FIG. 15 is an example of a sequence diagram illustrating operations until the sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 according to the first embodiment calculate the preferred order quantity.
  • the sales promotion effect estimation part 110 acquires a suitable content audience rating table (ST300).
  • sales promotion effect estimation section 110 refers to the audience rating in the preferred content audience rating table, and selects the introduction content with the highest local audience rating as the promotional content (ST301).
  • the sales promotion effect estimation unit 110 has described the case where the introduction content with the highest local audience rating is the sales promotion content.
  • the present invention is not limited to this, and the promotion content with the highest national audience rating is promoted. It may be content.
  • the sales promotion effect estimation part 110 acquires the introduction content specific information of the sales promotion content (ST302).
  • the sales promotion effect estimation part 110 acquires user input information (ST303).
  • the sales promotion effect estimation part 110 acquires a viewing log (ST304).
  • the sales promotion effect estimation unit 110 acquires a sales promotion content viewing log, a viewing log of all content for a predetermined period, and a viewing log of all daytime content on the day when the sales promotion content is broadcast.
  • the predetermined period is, for example, the past week.
  • the daytime is, for example, a time zone between 7:00 and 16:00.
  • the sales promotion effect estimation unit 110 calculates a coefficient indicating the sales promotion effect based on the acquired viewing log (ST305).
  • the sales promotion effect estimation unit 110 outputs a coefficient indicating the calculated sales promotion effect to the preferred order quantity calculation unit 116 (ST306).
  • the preferred order quantity calculation unit 116 acquires the normal order quantity (ST307).
  • the preferred order quantity calculation unit 116 calculates the preferred order quantity by multiplying the acquired normal order quantity by a coefficient indicating the calculated sales promotion effect (ST308).
  • FIG. 16 is an example of a flowchart for explaining the operation of the sales promotion effect estimation unit 110 according to the first embodiment calculating the coefficient indicating the sales promotion effect in ST305 of FIG.
  • the coefficient indicating the sales promotion effect is obtained by multiplying, for example, a regional audience rating influence coefficient, an exposure viewing time influence coefficient, a daytime audience rating influence coefficient, a holiday audience rating influence coefficient, a POP influence coefficient, another content influence coefficient, and the like. Is a coefficient. Details of the local audience rating influence coefficient, the exposure time duration influence coefficient, the daytime audience rating influence coefficient, the holiday audience rating influence coefficient, the POP influence coefficient, and the other content influence coefficient will be described below.
  • the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculation unit 107 shown in FIG.
  • the sales promotion effect estimation unit 110 calculates a local audience rating influence coefficient.
  • the regional audience rating influence coefficient is, for example, a coefficient obtained by multiplying a value obtained by dividing the local audience rating of the promotional content by the above-mentioned expected audience rating that is user input information and a predetermined weight. . Therefore, the regional audience rating influence coefficient is a value indicating that the sales promotion effect is larger if the actual audience rating is larger than the audience rating expected by the mass media.
  • the predetermined weight is, for example, 0.8. The predetermined weight may be determined in advance or may be set later by the user.
  • K1 ((regional audience rating of promotional content) / (expected audience rating)) ⁇ (predetermined weight) (1)
  • a site influence coefficient is a coefficient which shows the influence degree of the information obtained from the web site relevant to the store product introduced by the sales promotion content, for example.
  • the site influence coefficient is, for example, a natural language analysis of tweets written on Twitter (registered trademark) from the time the promotional content is broadcast to the present, and counts the number of positive tweets and the number of negative tweets. It is a coefficient obtained by multiplying a value obtained by dividing the number by the number of negative tweets and a predetermined weight. Assuming that the site influence coefficient is k11, k11 is expressed by the following equation (2). Note that 1 is added to the numerator and denominator, for example, to prevent k11 from becoming zero or impossible to calculate when the number of tweets is zero.
  • K11 (number of positive tweets + 1) / (number of negative tweets + 1) (2)
  • the sales promotion effect estimation unit 110 calculates a viewing time influence coefficient during exposure.
  • the viewing time influence coefficient at the time of exposure is, for example, the total viewing time for the sales promotion content of the person who was watching the sales promotion content during the time when the store product introduced in the sales promotion content appears in the sales promotion content. It is a coefficient obtained by dividing by the average viewing time of the person who was watching the whole and multiplying the divided value by a predetermined weight. Assuming that the exposure time influence coefficient during exposure is k2, k2 is expressed by the following equation (3).
  • K2 ((total viewing time when product is exposed) / (average viewing time of promotional content)) ⁇ (predetermined weight) (3)
  • the sales promotion effect estimation part 110 determines whether the present is a holiday (ST403). When the present is not a holiday (ST403-No), sales promotion effect estimating section 110 transitions to ST404. When the current day is a holiday (ST403-Yes), sales promotion effect estimating section 110 transitions to ST405. In ST403, when the present is not a holiday, sales promotion effect estimating section 110 calculates a daytime audience rating influence coefficient (ST404).
  • the daytime audience rating influence coefficient is obtained, for example, by dividing the average audience rating of all contents broadcast during the daytime by the average audience rating of all contents broadcast during a predetermined period. This is a coefficient obtained by multiplying the obtained value by a predetermined weight.
  • k3 is expressed by the following equation (4).
  • K3 ((average audience rating of all contents during the day) / (average audience rating of all contents broadcast during a given period)) ⁇ (predetermined weight) (4)
  • the sales promotion effect estimation unit 110 calculates a holiday audience rating influence coefficient (ST405).
  • the holiday audience rating influence coefficient is obtained, for example, by adding the average audience rating of all contents broadcast in the midnight hours and the average audience rating of all contents broadcast in the morning on Saturday. It is a coefficient obtained by dividing the obtained value by the average audience rating of all contents broadcast during a predetermined period and multiplying the value obtained by the division by a predetermined weight.
  • k4 is expressed by the following equation (5).
  • k4 (((average audience rating of all contents in the midnight) + (average audience rating of all contents on Saturday morning)) / (average audience rating of all contents broadcast in a predetermined period)) ⁇ (predetermined Weight) (5)
  • the sales promotion effect estimation unit 110 calculates a POP influence coefficient (ST406).
  • the POP influence coefficient is a coefficient representing a sales promotion effect that occurs when the POP is used.
  • the POP influence coefficient is obtained by, for example, dividing the local audience rating of the content used in creating the POP by the average audience rating of all the contents broadcast during a predetermined period, and adding a predetermined weight to the value obtained by the division. This is a coefficient obtained by multiplication. Assuming that the POP influence coefficient is k5, k5 is expressed by the following equation (6).
  • K5 ((regional audience rating of the content used when creating the POP) / (average audience rating of all content broadcast during a given period)) ⁇ (predetermined weight) (6)
  • the sales promotion effect estimation unit 110 calculates another content influence coefficient (ST407).
  • the other content influence coefficient is, for example, a predetermined coefficient associated with a keyword introduced in content different from the sales promotion content (hereinafter referred to as other content) or a time when the sales promotion content is broadcast.
  • FIG. 17 is an example of a keyword table showing a list of predetermined coefficients associated with keywords related to store merchandise in the first embodiment.
  • a keyword of Christmas is associated with a time of December 24 before strawberry.
  • the sales promotion effect estimation unit 110 acquires keywords related to the store product introduced in the sales promotion content by the natural language analysis from the content information server 9.
  • the sales promotion effect estimation unit 110 acquires the content introducing the acquired keyword from the content information server 9 and acquires the viewing log of the acquired content from the viewing log server 8.
  • the sales promotion effect estimation unit 110 calculates a national audience rating or a regional audience rating of the acquired content based on the acquired viewing log, and selects a keyword introduced in the content with the highest audience rating.
  • the sales promotion effect estimation unit 110 calculates the other content influence coefficient as shown in the keyword table t1101 based on the selected keyword and the current time.
  • the other content influence coefficient is calculated from Expression (1) based on the audience rating of the content associated with the selected keyword.
  • the other content influence coefficient is represented by k6.
  • the sales promotion effect estimation part 110 calculates the coefficient which shows the sales promotion effect, for example by adding the calculated various coefficients.
  • the coefficient indicating the sales promotion effect is k, for example, k when the current day is a weekday and the POP is used is expressed by the following equation (7).
  • the POP influence coefficient k5 is excluded from the following equation (7).
  • each coefficient may be multiplied by a predetermined weight, for example.
  • the coefficient k indicating the sales promotion effect may be calculated by multiplying each coefficient.
  • FIG. 18 is an example of a flowchart illustrating an operation in which the sales promotion effect information image generation unit 112 according to the first embodiment generates the sales promotion effect information image “img”.
  • the sales promotion effect information image generation part 112 acquires a suitable content audience rating table, suitable order quantity, and normal order quantity (ST500).
  • the sales promotion effect information image generation unit 112 refers to the suitable content audience rating table and selects the introduction content having the highest local audience rating as the sales promotion content (ST501).
  • the sales promotion effect information image generation part 112 acquires the introduction content specific information table t1051 of the sales promotion content (ST502).
  • the sales promotion effect information image generation part 112 acquires the viewing log of the selected sales promotion content (ST503).
  • the sales promotion effect information image generation unit 112 extracts the broadcast date and time of the sales promotion content, the television program name including the sales promotion content (the introduction information described above) from the introduction content specifying information of the sales promotion content, and the introduction content information image. p1 is generated (ST504).
  • the sales promotion effect information image generation part 112 reads the character string showing the predetermined sales promotion phrase registered beforehand.
  • the sales promotion effect information image generation unit 112 combines the extracted broadcast date and time of the sales promotion content, the name of the television program including the sales promotion content, and the character string representing the read sales promotion phrase, and uses the text information used for the introduction content information image p1. Is generated.
  • the sales promotion effect information image generation unit 112 sets the generated text information as the introduction content information image p1 according to a predetermined format.
  • the predetermined format is, for example, the vertical and horizontal widths of the image, the background color, the character color, and the like.
  • the predetermined format when the sales promotion effect information image generation unit 112 generates each image is the vertical and horizontal widths of the image, background color, and character color for each image generated by the sales promotion effect information image generation unit 112.
  • a predetermined format such as is set in the sales promotion effect estimation server 4 in advance will be described.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 extracts the national audience rating of the sales promotion content from the suitable content audience rating table, and generates the national audience rating image p2 according to a predetermined format based on the extracted national audience rating.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 extracts the local audience rating of the sales promotion content from the suitable content audience rating table, and generates the regional audience rating image p3 according to a predetermined format based on the extracted local audience rating.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 extracts, for example, the number of tweets related to the store product introduced in the sales promotion content by natural language analysis from the Internet, and the site information according to a predetermined format based on the extracted number of tweets. An image p4 is generated.
  • sales promotion effect information image generation section 112 generates sales promotion content content image p5 (ST508).
  • the sales promotion effect information image generation unit 112 extracts the event content information of the sales promotion content from the introduction content specifying information table 1051, and generates the sales promotion content content image p5 according to a predetermined format based on the extracted event content information. .
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 for example, based on the introductory content specifying information table t1501 and the viewing log of the introductory content, uses the cumulative broadcast time per day of the introductory content as the exposure time, and exposes it within a predetermined period Graph the time variation. Further, the sales promotion effect information image generation unit 112 calculates the cumulative viewing time based on the viewing log, and based on the calculated cumulative viewing time, the fluctuation of the cumulative viewing time within the same period as the fluctuation of the exposure time is exposed. An exposure time graph p6 is generated by superimposing the graph on the time variation graph.
  • the sales promotion effect information image generation unit 112 generates an order quantity image p7 according to a predetermined format based on the acquired preferred order quantity and normal order quantity (ST510).
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 acquires a content video of the sales promotion content from the content recording server 10, and generates the capture image p8 by capturing the acquired content video.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 extracts the broadcast time of the sales promotion content from the introduction content specifying information table t1051, and generates the regional exposure time image p10 according to a predetermined format based on the extracted broadcast time.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 calculates a total viewing time obtained by multiplying the broadcast time extracted in ST513 by the number of television receivers that have viewed the sales promotion content extracted from the viewing log. Based on, the general viewing time image p11 is generated according to a predetermined format.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 extracts the introduction content having the top three places in the local audience rating from the preferred content audience rating table, and performs natural language analysis from the event content information corresponding to the extracted content. , Extract short text information representing the event.
  • the sales promotion effect information image generation part 112 produces
  • the sales promotion effect information image generation unit 112 generates the sales promotion effect information image “img” by arranging the various images generated in ST504 to ST515 in accordance with a predetermined format (ST515).
  • the sales promotion effect estimation system 1 acquires various pieces of information on the content introducing the post-broadcast store product, and based on the acquired various information, the sales promotion effect of the introduced store product is obtained.
  • the indicated coefficient can be calculated.
  • the sales promotion effect estimation system 1 can calculate an order quantity suitable for the store product introduced in the sales promotion content based on the calculated coefficient indicating the sales promotion effect, it is possible to prevent excessive orders and underorders. it can.
  • the sales promotion effect estimation system 1 generates a sales promotion effect information image and displays the generated sales promotion effect information image. Therefore, the user can obtain the basis of the sales promotion effect by the introduction content immediately after the introduction content is broadcast.
  • FIG. 19 is a flowchart of an action pattern expected to be taken by a general customer.
  • This flowchart shows that the sales promotion effect estimation system 1 of the first embodiment calculates a suitable order quantity, and is considered to have generality.
  • a customer sees an advertisement using information of a television program (promotional content) installed in the store “Shp”, the customer performs the actions from ST600 to ST611.
  • the customer sees the advertisement (ST600).
  • the customer views the advertisement (ST601-program name) using the television program name (name of the promotional content) or the performer who introduced the promotional product that appeared in the promotional content (hereinafter referred to as the introduction person). Different actions are taken depending on whether the advertisement uses (referred to as ST601-introducing person).
  • the viewed advertisement is an advertisement using the television program name in ST601, the customer's behavior transitions to ST602.
  • the viewed advertisement is an advertisement using an introduction person in ST601, the customer's behavior transitions to ST607.
  • the customer's behavior is different depending on whether or not the television program is known (ST602).
  • ST602-Yes the customer transitions to ST603.
  • ST602-No the customer transitions to ST606.
  • ST602 when the user knows the television program, the customer's behavior is different depending on whether or not he / she was watching the television program (ST603).
  • ST603-Yes the transition is made to ST604.
  • ST603-No the customer transitions to ST605.
  • the customer purchases a promotional product with high probability (ST604).
  • the customer may purchase a promotional product (ST605).
  • the customer's willingness to purchase does not increase (ST606).
  • the viewed advertisement is an advertisement using an introduction person in ST601
  • the customer takes different actions depending on whether or not the introduction person is known (ST607).
  • ST607-Yes the behavior of the customer transitions to ST608.
  • ST611 the behavior of the customer transitions to ST611.
  • the customer takes different actions depending on whether or not the television program is being watched (ST608).
  • ST608-Yes the behavior of the customer transitions to ST609.
  • ST608-No the customer behavior transitions to ST610.
  • ST609 the customer purchases a promotional product with high probability (ST609).
  • ST608 when the user does not watch the television program, the customer may purchase (ST610).
  • the introduction person is not known in ST607, the customer's willingness to purchase does not increase (ST611).
  • the sales promotion effect estimation system 1 uses the introduction content with the highest audience rating as the sales promotion content and calculates a suitable order quantity according to the audience rating of the sales promotion content, the user can carry out a more appropriate ordering operation. It can be carried out.
  • FIG. 20 is an example of a graph showing the relationship between the exposure time to the product content and the sales.
  • FIG. 20 shows a histogram of the cumulative time in which the product A or the category (for example, product type) including the product A is introduced in the contents for each date, and the introduced product A It is the figure which showed in a line graph the change of the sales of this, and the change of the sales of the whole category.
  • the sales of the product A and the sales of the entire category including the product A increase as the time (exposure time) for which the product A is introduced in the content increases. Such an increase in sales generally tends to occur in reality.
  • the sales promotion effect estimation system 1 uses the introductory content with the highest audience rating as the sales promotion content, and calculates the preferred order quantity according to the audience rating of the sales promotion content. Therefore, the sales order effect amount more appropriately reflects the sales promotion effect of the sales promotion content. calculate. Then, the user can perform more appropriate ordering work according to the calculated preferred order quantity.
  • the sales promotion effect estimation system 1 demonstrated the case where the sales promotion effect information image was transmitted and displayed on the store apparatus 3 in the said 1st Embodiment, it is not restricted to this.
  • the sales promotion effect estimation system 1 may, for example, send a sales promotion effect information image to a specific PC (Personal Computer) and display it, or send the sales promotion effect information image to a store manager or a person in charge of ordering by e-mail.
  • a predetermined in-store broadcast may be broadcast.
  • the sales promotion effect estimation system 1 includes only one store “Shp” has been described.
  • the present invention is not limited to this, and a plurality of stores may be included.
  • the sales promotion effect estimation server 4 may generate a suitable order quantity, a sales promotion effect information image, and the like for each store (in the case of the first embodiment). Further, the sales promotion effect estimation server 4 may hold suitable order quantities and sales promotion effect information images generated for all stores, and the user may select information desired by the store device 3. Further, the sales promotion effect estimation server 4 automatically distributes the preferred order quantity and the sales promotion effect information image generated for all the stores, and the preferred order quantity and the sales promotion effect information image associated with each store. You may make it do.
  • the second embodiment will be described.
  • the structure of the sales promotion effect estimation system in 2nd Embodiment FIG.1 and FIG.10 is used and the same code
  • the store apparatus 3 includes various functional units of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11.
  • FIG. 21 is a diagram illustrating a usage situation of the sales promotion effect estimation system 1 according to the second embodiment.
  • the sales promotion effect estimation device 11 displays an order screen “order” on the display of the sales promotion effect estimation device 11 based on the calculated preferred order quantity.
  • the sales promotion effect estimation apparatus 11 displays the produced sales promotion effect information image on the display of the sales promotion effect estimation apparatus 11 by operation from a user. Further, the sales promotion effect estimation device 11 outputs and displays an alert image “alrt” on the handy terminal 2 when the audience rating of the sales promotion content exceeds a predetermined threshold.
  • the sales promotion effect estimation system 1 of 2nd Embodiment is provided with the shop apparatus 3 with the function part of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11, and is the same as that of 1st Embodiment.
  • the effect of can be obtained.
  • FIG.1 and FIG.10 are used and it attaches
  • the sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 of the sales promotion effect estimation server 4 according to the third embodiment are configured such that when the store apparatus 3 generates an alert image and outputs the alert image to the handy terminal 2 Only when the predetermined threshold value used for the sales is exceeded, the coefficient indicating the sales promotion effect and the preferred order quantity are calculated. When the predetermined threshold value is not exceeded, the normal order quantity is set as the preferred order quantity and the store apparatus 3 and the sales promotion effect information The image is output to the image generation unit 112.
  • the sales promotion effect estimation system 1 in the third embodiment calculates the preferred order quantity for the order quantity of the store product displayed in the alert image only when the alert image is displayed on the handy terminal 2. And the effect similar to 1st Embodiment can be acquired.
  • the sales promotion effect estimation system 1 of the modification of 3rd Embodiment has the following functions.
  • the audience rating of the sales promotion content exceeds a predetermined threshold used when the store apparatus 3 generates an alert image and outputs it to the handy terminal 2. Only in the case, the sales promotion effect information image is generated.
  • the sales promotion effect estimation system 1 in the modification of the third embodiment generates the sales promotion effect information image only when the alert image is displayed on the handy terminal 2. Therefore, only the sales promotion effect information image of the store product for which the alert image is displayed on the handy terminal 2 can be displayed on the store apparatus 3. Therefore, the sales promotion effect estimation system 1 in the modification of the third embodiment can obtain the same effect as that of the first embodiment only when an alert image is displayed on the handy terminal 2.
  • FIG.1 and FIG.10 are used and it attaches
  • the sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 of the sales promotion effect estimation system 1 according to the fourth embodiment are configured to introduce content that is a candidate for sales promotion content broadcasted in a past predetermined period (for example, 3 days).
  • a past predetermined period for example, 3 days.
  • an appropriate score indicating the level of consumer interest in the promotional product was calculated.
  • the sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 select the sales promotion content from the introduction content according to the calculated appropriate score.
  • FIG. 22 is a conceptual diagram for explaining a method for calculating an appropriate score in the fourth embodiment.
  • the sales promotion effect estimation unit 110 calculates an appropriate score using FIG.
  • the event content information type is information that categorizes how products are introduced.
  • the event content information type is, for example, information A if the information obtained by natural language analysis of the event content information is delicious if the food is eaten as it is, if the promotional product is food. If it is information that it is good for health, it becomes information B, and if it is information that the food is not delicious, it becomes information C.
  • the broadcast end time represents the broadcast end time of each introduction content.
  • the viewing time by the first to fourth viewers represents the time of viewing each introduction content of each of the first to fourth viewers.
  • the content-specific weighting coefficient is an index representing the degree of influence on the sales promotion effect assigned to the event content information type of each introduction content.
  • the sales promotion effect estimation unit 110 performs natural language analysis on the event content information of the introduction content, and assigns a predetermined weighting coefficient to the introduction content as a weighting coefficient for each content based on the strength of the relevance to the viewer's willingness to purchase. . Specifically, for example, if the sales promotion effect estimation unit 110 determines that it is a late night laughing content as a result of the natural language analysis of the introduction content “vvv”, the weighting coefficient is 0.5.
  • the weighting coefficient by elapsed time is an index representing the degree of influence on the sales promotion effect by the elapsed time from the broadcast end time of the introduction content. Since the topicality of the public with respect to the introduction content decreases as time elapses from the broadcast end time of the introduction content, the weighting coefficient for each elapsed time becomes small.
  • the sales promotion effect information image generation unit 112 calculates a weighting coefficient for each elapsed time by the following equation (8).
  • the unit of elapsed time is “time”.
  • the sales promotion effect estimation unit 110 multiplies the total viewing time of the viewer for each introduction content by the weighting coefficient for each content and the weighting coefficient for each elapsed time to calculate an appropriate score.
  • the appropriate score is calculated as follows: the total viewing time of the first to fourth viewers is 320 seconds, the weighting factor by content is 1, and the weighting by elapsed time is Since the coefficient is 0.82, the appropriate score is expressed by the following equation (9) and is 262.
  • the sales promotion effect estimation unit 110 calculates an appropriate score for all the introduction contents in the past three days, and calculates a total score for each event content information type.
  • the total appropriate score of the information A is 298.9 points because it is the total correct score of the two contents of the introduction contents “xxx” and “vvv”.
  • the total appropriate score for information B is 160 points
  • the total proper score for information C is 36.5 points.
  • the sales promotion effect estimation unit 110 selects the sales promotion content from the introduction content corresponding to the event content information type that is the sum of the highest appropriate scores. In FIG. 22, since information A has the highest appropriate score, either “xxx” or “vvv”, which is the introduction content of information A, is selected as the sales promotion content.
  • the sales promotion effect estimation unit 110 selects the introduction content having the highest appropriate score as the sales promotion content from the introduction content of the introduction content specific information type that is the sum of the highest appropriate scores. Note that the processing related to the appropriate score of the sales promotion effect information image generation unit 112 is the same as that of the sales promotion effect estimation unit 110, and thus detailed description thereof is omitted.
  • the sales promotion effect estimation server 4 of the fourth embodiment calculates the appropriate score based on the viewing time that is an example of the viewing history information of the consumer (viewer) who viewed the introduction content. Select content. Since the appropriate score indicates the level of consumer interest in the sales promotion product in the world, the sales promotion effect estimating unit 110 can calculate a coefficient indicating a more preferable sales promotion effect by selection based on the appropriate score.
  • the weighting coefficient in 4th Embodiment was only the weighting coefficient classified by content and the weighting coefficient classified by elapsed time, it is not restricted to this.
  • the weighting coefficient in the fourth embodiment may include a weighting coefficient based on the movement rate.
  • the weighting coefficient in the fourth embodiment may include a weighting coefficient based on the number of tweets.
  • the sales promotion effect estimation system 1 calculates a coefficient indicating the influence on the sales promotion effect for all the introduction contents whose calculated appropriate score is a score larger than 0, and to all the calculated sales promotion effects.
  • a value obtained by adding or multiplying a coefficient indicating the influence of the above may be used as a coefficient indicating the influence on the final sales promotion effect.
  • the fifth embodiment will be described below.
  • the sales promotion effect estimation unit 110 according to the fifth embodiment is based on content information of other content (hereinafter referred to as correlation content) having a high degree of commonality between the viewer of the sales promotion content and the viewer, and the other content influence coefficient k6.
  • correlation content content information of other content
  • the keyword for calculating is extracted.
  • the sales promotion product is food.
  • the present invention is not limited to this, and may be clothing, electrical appliances, or the like.
  • FIG. 23 is a conceptual diagram for explaining selection of correlated content in the fifth embodiment.
  • the sales promotion effect estimation unit 110 selects correlated content using FIG. FIG. 23 shows information in which a viewing pattern indicating whether or not each content is viewed is associated with the number of television receivers.
  • all viewing situations of the contents 1 to 3 are “viewing”.
  • the rightmost column in FIG. 23 displays the number of views for each viewing situation. Therefore, the number of views for each viewing situation in the rightmost column of the second row in FIG. 23 represents the number of television receivers that have viewed all of the contents 1 to 3.
  • the number of views for each viewing situation in the rightmost column is the number of television receivers that have both viewed content 1 and content 2 but have not viewed content 3.
  • the bottom line in FIG. 23 displays the total number of television receivers viewed for each content.
  • the sales promotion effect estimation unit 110 sets the content 1 as the content with the highest audience rating that introduced the promotional product in the past 3 days, and the content 2 as the sales product with the highest national audience rating after the content 1 in the past 3 days. Is the content introduced. Then, for example, the sales promotion effect estimation unit 110 sets the content 3 as content that introduces food (hereinafter referred to as related food) that is used for cooking in association with the sales promotion product in the past three days. For example, if the promotional product is “mochi”, the related food is fresh cream or flour used in the roll cake when the roll cake using mochi is introduced.
  • the sales promotion effect estimation unit 110 converts the content 1 and the content 2 into the above-described introduction content identification information table t1051 storing the introduction content identification information of the introduction content and the above-described viewing log collected from television receivers nationwide. And select based on.
  • the sales promotion effect estimation unit 110 searches for a recipe using the sales promotion product from a predetermined Web site that introduces a recipe for cooking, and extracts related foods from the searched recipe by natural language analysis.
  • the sales promotion effect estimation unit 110 extracts the content introducing the extracted related food (hereinafter referred to as related food introduction content) from the content information table t91.
  • the extracted related food introduction content is associated with the related food.
  • the sales promotion effect estimation unit 110 extracts the viewing number of the extracted related food introduction content from the viewing log, and sets the related food introduction content with the largest viewing number as the content 3.
  • the sales promotion effect estimation unit 110 is a content that introduces the candy “Amaio” as the content 1, the content 2 is the content that introduces the ranking of the candy, and the content 3 is fresh cream (the above-mentioned related food).
  • the other content candidates that are the keyword extraction source for calculating the other content influence coefficient k6 are the content 2 and the content 3.
  • the sales promotion effect estimation unit 110 sets the content of the content 2 and the content 3 that has been viewed together with the content 1 as the extraction source content. Specifically, in the case of FIG. 23, the total number of viewings of content 1 is 100, and the number of viewings of content 2 but not viewing of content 1 is 20; The number of contents 3 that have not been viewed is 45.
  • the number N12 of viewing either the content 1 or the content 2 is expressed by the following equation (10). Further, the number N13 of viewing either the content 1 or the content 3 is expressed by the following equation (11).
  • the sales promotion effect estimation unit 110 since the sales promotion effect estimation unit 110 has more N13 than N12, it can obtain a more suitable other content influence coefficient k6 by selecting the content 3 as the extraction source content. Accordingly, the sales promotion effect estimation unit 110 selects the content 3 as the extraction source content.
  • the sales promotion effect estimation server 4 of the fifth embodiment can obtain a more suitable other content influence coefficient k6 by extracting the extraction source content having a high correlation with the sales promotion content. As a result, a coefficient indicating a more preferable sales promotion effect can be calculated.
  • FIG.1 and FIG.10 The sales promotion effect estimation unit 110 in the sixth embodiment uses the expected audience rating used when calculating the regional audience rating influence coefficient k1, for example, before the previous time when the broadcasted promotional content is regularly broadcast. Calculated based on the audience rating of the broadcast. Therefore, the sales promotion effect estimation server 4 in the sixth embodiment may omit the user input information reception unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.
  • the sales promotion effect estimation unit 110 calculates, for example, the average audience rating of the promotional content broadcast one week ago as the expected audience rating. Since the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculator 107 shown in FIG. 14, detailed description thereof is omitted.
  • the sales promotion effect estimation server 4 of the sixth embodiment obtains the same effect as that of the first embodiment without requiring user input because the sales promotion effect estimation unit 110 calculates the expected audience rating. be able to.
  • the seventh embodiment will be described below. About the structure of the sales promotion effect estimation system in 7th Embodiment, FIG.1 and FIG.10 is used and the same code
  • the sales promotion effect estimation unit 110 according to the seventh embodiment predicts the expected audience rating used when the regional audience rating influence coefficient k1 is calculated by the mass media and the like by registering the expected audience ratings of various contents. Obtained from the audience rating server. Therefore, the sales promotion effect estimation server 4 in the seventh embodiment may omit the user input information receiving unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.
  • FIG. 24 is a diagram showing a usage situation of the sales promotion effect estimation system 1 in the seventh embodiment.
  • the sales promotion effect estimation system 1 in the seventh embodiment is the same as the sales promotion effect estimation system 1, the handy terminal 2, the store apparatus 3, the sales promotion effect estimation server 4, the store product server 5, the store product supplement server 6, the POS server 7, viewing A log server 8, a content information server 9, a content recording server 10, and an expected audience rating providing server 12 are included.
  • the expected audience rating providing server 12 stores the expected audience ratings for various contents provided by mass media and the like.
  • the expected audience rating providing server 12 is communicably connected to the sales promotion effect estimating server 4 via the NW.
  • the sales promotion effect estimation unit 110 of the sales promotion effect estimation server 4 in the seventh embodiment acquires the expected audience rating from the expected audience rating providing server 12 in order to calculate the regional audience rating influence coefficient k1.
  • the sales promotion effect estimation unit 110 calculates the expected viewing rate. Since it acquires from the rate provision server 12, the effect similar to 1st Embodiment can be acquired.
  • achieving the function of each part which comprises the sales promotion effect estimation system 1 in FIG.1, FIG.10, FIG.21 is recorded on a computer-readable recording medium, The program recorded on this recording medium is recorded.
  • the sales promotion effect estimation system 1 may be implemented by being read and executed by a computer system.
  • the “computer system” here includes an OS (Operation System) and hardware such as peripheral devices.
  • the “computer system” includes a homepage providing environment (or display environment) if a WWW (World Wide Web) system is used.
  • the “computer-readable recording medium” means a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), a CD (Compact Disk) -ROM, or a hard disk built in a computer system. Refers to the device.
  • the “computer-readable recording medium” is a medium that dynamically holds a program for a short time, such as a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line, In this case, it also includes those that hold a program for a certain period of time, such as a volatile memory inside a computer system serving as a server or client.
  • the program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.
  • the 1st aspect of this invention is content content information which described the content of the broadcast content, Comprising: The event generation period which shows the period in which the event which is at least one part in a program has generate
  • the said correspondence information is related with the case where the content relevant to the said event occurrence period is used in a store, and the said event occurrence period in a store
  • the estimated value used for calculating the demand amount when the content related to the event occurrence period is used at the store and the content related to the event occurrence period are used at the store It is good also as a sales promotion effect estimation method which calculates the said estimated value used for calculation of the demand amount when not being performed.
  • the 2nd aspect of this invention is the content content information which described the content of the broadcast content, Comprising: The event generation
  • An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information
  • An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content
  • a promotion effect estimation device comprising a.
  • the third aspect of the present invention is content content information describing the content of broadcast content, and an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, and the event occurrence period
  • a specific unit that identifies content related to an event occurrence period based on information related to a product by referring to content content information including information related to a product related to an event and content information indicating content, and the specified event occurrence
  • An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information
  • An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content
  • the 4th aspect of this invention is the content generation
  • the content occurrence information including the period and information related to the product related to the event and the content information indicating the content are referred to, the content related to the event occurrence period is specified based on the information related to the product, and the specified event occurrence Content related to the event occurrence period is obtained by acquiring viewing history information of content related to the period, reading correspondence information associating the viewing history information with the estimated value from the storage unit, and based on the acquired viewing history information Calculate the estimated value indicating the effect of promoting the sale of the product played by A computer-readable recording medium recording a program for.
  • One embodiment of the present invention can be applied to a sales promotion effect estimation device that can more appropriately estimate the sales promotion effect of content including information related to a product.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Strategic Management (AREA)
  • Finance (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A sales promotion effect estimation method according to an embodiment of the present invention includes: referring to content substance information describing the substance of a content that has been broadcast and including information about an event occurrence period indicating a period in which a certain event as at least a part of a program is occurring and about a merchandise relating to the event, and content information indicating the content; identifying the content relating to the event occurrence period on the basis of the information about the merchandise; acquiring viewing history information of the content relating to the identified event occurrence period; reading from a storage unit association information associating the viewing history information with an estimated value; and calculating the estimated value indicating the effect of the content relating to the event occurrence period in promoting the sales of the merchandise, on the basis of the acquired viewing history information.

Description

販促効果推定方法、販促効果推定装置、販促効果推定システム及び記録媒体Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium
 この発明は、販促効果推定方法、販促効果推定装置、販促効果推定システム及び記録媒体に関する。
 本願は、2013年6月28日に、日本に出願された特願2013-137312号に基づき優先権を主張し、その内容をここに援用する。
The present invention relates to a sales promotion effect estimation method, a sales promotion effect estimation device, a sales promotion effect estimation system, and a recording medium.
This application claims priority on June 28, 2013 based on Japanese Patent Application No. 2013-137312 for which it applied to Japan, and uses the content here.
 近年、マスメディアが提供するテレビジョン番組による消費動向への影響は、著しく大きくなっている。特に、テレビジョン番組で紹介した商品は、放送後、販売量が増加する傾向にある。しかし、テレビジョン番組によるマスメディア独自の商品紹介は、本来、商品メーカー等の商品を提供する者が意図した販売促進活動ではない。そのため、従来の販売動向予測に基づく商品発注管理方式では、発注対象としてテレビジョン番組で紹介された商品の発注量を多く予測することは困難であった。 In recent years, the impact on consumption trends by television programs provided by the mass media has been significantly increasing. In particular, products introduced on television programs tend to increase in sales volume after broadcasting. However, mass media's original product introduction by television programs is not originally a sales promotion activity intended by a product maker or other person who provides products. For this reason, it has been difficult to predict the order quantity of products introduced in a television program as a target of order in the conventional product order management system based on sales trend prediction.
 これに関連し、特許文献1の商品自動発注処理システムは、テレビジョン番組で紹介される商品を、放映前のテレビジョン番組の番組データから抽出し、抽出した商品の発注量を算出し、算出した発注量でその商品を自動的に発注する。 In relation to this, the automatic product order processing system of Patent Document 1 extracts the product introduced in the television program from the program data of the television program before airing, calculates the order quantity of the extracted product, and calculates The product is automatically ordered with the ordered quantity.
特開2003-233751号公報Japanese Patent Laid-Open No. 2003-233751
 特許文献1に記載の商品自動発注処理システムでは、放送前のテレビジョン番組の番組データを利用する。そのため、そのテレビジョン番組の内容の詳細が分からず、好適な発注量を算出するために必要な販促(販売促進)効果を正確に予測することができない。
 また、そのテレビジョン番組が生放送の場合や、野球中継等の延長によってそのテレビジョン番組が放映されなかった場合、この商品自動発注処理システムでは販促効果を予測することが困難なだけではなく、販促効果を過大又は過小予測してしまう場合がある。
The automatic merchandise order processing system described in Patent Document 1 uses program data of a television program before broadcasting. Therefore, the details of the contents of the television program are not known, and the sales promotion (sales promotion) effect necessary to calculate a suitable order quantity cannot be accurately predicted.
In addition, if the television program is a live broadcast, or if the television program is not broadcast due to an extension of a baseball broadcast or the like, it is not only difficult to predict the sales promotion effect with this product automatic order processing system, but also the sales promotion. The effect may be overestimated or underestimated.
 本発明の一態様は、商品に関連する情報が含まれたコンテンツの販促効果を、より適切に推定することができる販促効果推定方法を提供することを目的の一つとする。 One aspect of the present invention is to provide a sales promotion effect estimation method capable of more appropriately estimating the sales promotion effect of content including information related to a product.
 本発明の一態様は、放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定し、前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得し、前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する、販促効果推定方法である。 One aspect of the present invention relates to content content information describing the content of broadcast content, and relates to an event occurrence period that indicates a period in which an event that is at least a part of a program is occurring, and a product related to the event Content content information including information and content information is specified, content related to the event occurrence period is specified based on information about the product, and viewing history information of the content related to the specified event occurrence period And reading correspondence information that associates the viewing history information with the estimated value from the storage unit, and based on the obtained viewing history information, the effect of promoting the sale of the product played by the content related to the event occurrence period is obtained. It is the sales promotion effect estimation method which calculates the said estimated value to show.
 本発明の一態様によれば、商品に関連する情報が含まれたコンテンツの販促効果を、より適切に推定することができる販促効果推定方法を提供することができる。 According to one aspect of the present invention, it is possible to provide a sales promotion effect estimation method that can more appropriately estimate the sales promotion effect of content including information related to a product.
第1の実施形態における販促効果推定システムの利用状況を示す図である。It is a figure which shows the utilization condition of the sales promotion effect estimation system in 1st Embodiment. 第1の実施形態における販促効果情報画像の一例を示す図である。It is a figure which shows an example of the sales promotion effect information image in 1st Embodiment. 第1の実施形態における発注画面の一例を示す図である。It is a figure which shows an example of the ordering screen in 1st Embodiment. 第1の実施形態におけるアラート画像の一例を示す図である。It is a figure which shows an example of the alert image in 1st Embodiment. 第1の実施形態におけるレポート画像の一例を示す図である。It is a figure which shows an example of the report image in 1st Embodiment. 第1の実施形態におけるハンディーターミナルにアラート画面が表示された図の一例である。It is an example of the figure by which the alert screen was displayed on the handy terminal in 1st Embodiment. 第1の実施形態における店舗商品テーブルの一例を示す図である。It is a figure which shows an example of the store goods table in 1st Embodiment. 第1の実施形態における補足情報テーブルの一例を示す図である。It is a figure which shows an example of the supplementary information table in 1st Embodiment. 第1の実施形態におけるコンテンツ情報テーブルの一例を示す図である。It is a figure which shows an example of the content information table in 1st Embodiment. 第1の実施形態における販促効果推定サーバの構成の一例を示す概略ブロック図である。It is a schematic block diagram which shows an example of a structure of the sales promotion effect estimation server in 1st Embodiment. 第1の実施形態における紹介コンテンツ特定情報テーブルの一例を示す図である。It is a figure which shows an example of the introduction content specific information table in 1st Embodiment. 第1の実施形態におけるコンテンツ視聴率テーブルの一例を示す図である。It is a figure which shows an example of the content audience rating table in 1st Embodiment. 第1の実施形態における好適コンテンツ視聴率テーブルを生成するまでの動作を説明するシーケンス図の一例である。It is an example of the sequence diagram explaining operation | movement until it produces | generates the suitable content audience rating table in 1st Embodiment. 第1の実施形態における紹介コンテンツの全国視聴率及び地域視聴率を算出する動作を説明するフローチャートの一例を示す図である。It is a figure which shows an example of the flowchart explaining the operation | movement which calculates the national audience rating and local audience rating of the introduction content in 1st Embodiment. 第1の実施形態における好適発注量を算出するまでの動作を説明するシーケンス図の一例を示す図である。It is a figure which shows an example of the sequence diagram explaining operation | movement until calculating the suitable order quantity in 1st Embodiment. 第1の実施形態における販促効果への影響を示す係数を算出する動作を説明するフローチャートの一例を示す図である。It is a figure which shows an example of the flowchart explaining the operation | movement which calculates the coefficient which shows the influence on the sales promotion effect in 1st Embodiment. 第1の実施形態における店舗商品に関連するキーワードに対応付けられた所定の係数の一覧を示すキーワードテーブルの一例を示す図である。It is a figure which shows an example of the keyword table which shows the list | wrist of the predetermined coefficient matched with the keyword relevant to the store goods in 1st Embodiment. 第1の実施形態における販促効果情報画像を生成する動作を説明するフローチャートの一例を示す図である。It is a figure which shows an example of the flowchart explaining the operation | movement which produces | generates the sales promotion effect information image in 1st Embodiment. 一般的な顧客が取ると予想される行動パターンのフローチャートの一例を示す図である。It is a figure which shows an example of the flowchart of the action pattern anticipated that a general customer takes. 商品のコンテンツへの露出時間と売り上げの関係を表すグラフの一例である。It is an example of the graph showing the exposure time to the content of goods, and sales. 第2の実施形態における販促効果推定システムの利用状況を示す図である。It is a figure which shows the utilization condition of the sales promotion effect estimation system in 2nd Embodiment. 第4の実施形態における適正点数の算出方法を説明するための概念図である。It is a conceptual diagram for demonstrating the calculation method of the appropriate score in 4th Embodiment. 第5の実施形態における相関コンテンツの選択を説明するための概念図である。It is a conceptual diagram for demonstrating selection of the correlation content in 5th Embodiment. 第7の実施形態における販促効果推定システムの利用状況を示す図である。It is a figure which shows the utilization condition of the sales promotion effect estimation system in 7th Embodiment.
<第1の実施形態>
 以下、図面を参照して、第1の実施形態について説明する。
 図1は、第1の実施形態における販促効果推定システムの利用状況を示す図である。販促効果推定システム1は、ハンディーターミナル2、店舗装置3、販促効果推定サーバ4、店舗商品サーバ5、店舗商品補足サーバ6、POSサーバ7、視聴ログサーバ8、コンテンツ情報サーバ9、及びコンテンツ記録サーバ10を含む。
 販促効果推定システム1では、例えば、店舗“Shp”内に、ハンディーターミナル2、店舗装置3、店舗商品サーバ5、及び店舗商品補足サーバ6が設置される。
<First Embodiment>
The first embodiment will be described below with reference to the drawings.
FIG. 1 is a diagram illustrating a usage situation of the sales promotion effect estimation system according to the first embodiment. The sales promotion effect estimation system 1 includes a handy terminal 2, a store apparatus 3, a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server. 10 is included.
In the sales promotion effect estimation system 1, for example, a handy terminal 2, a store apparatus 3, a store product server 5, and a store product supplement server 6 are installed in the store “Shp”.
 店舗装置3、店舗商品サーバ5、店舗商品補足サーバ6は、例えば、LAN(Local Area Network)等のネットワークで通信可能に接続される。また、ハンディーターミナル2は、例えば、店舗装置3と、無線LAN等で通信可能に接続される。
 ネットワークNWは、例えば、インターネットや移動体通信網などのネットワークであるが、これらに限られない。ネットワークNWは、イントラネットや専用回線等でもよいし、それらの組み合わせによって構成される情報通信ネットワークでもよい。
 ネットワークNWには、例えば、店舗装置3、販促効果推定サーバ4、店舗商品サーバ5、店舗商品補足サーバ6、POSサーバ7、視聴ログサーバ8、コンテンツ情報サーバ9、及びコンテンツ記録サーバ10が接続され、互いに通信可能な状態にある。
The store apparatus 3, the store product server 5, and the store product supplement server 6 are connected to be communicable via a network such as a LAN (Local Area Network). Further, the handy terminal 2 is connected to the store apparatus 3 so as to be communicable with a wireless LAN or the like, for example.
The network NW is, for example, a network such as the Internet or a mobile communication network, but is not limited thereto. The network NW may be an intranet, a dedicated line, or the like, or an information communication network configured by a combination thereof.
For example, a store device 3, a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server 10 are connected to the network NW. Are in a state where they can communicate with each other.
 販促効果推定サーバ4は、例えば、店舗“Shp”が取り扱うことができる商品、あるいはこれから取り扱う商品(以下、店舗商品という)に関する情報と、店舗商品に関する情報が含まれたコンテンツ(以下、紹介コンテンツという)に付随する情報(例えば、紹介コンテンツのテレビジョン番組名やラジオ番組名や放送日時等)を、ネットワークNWに接続された各種サーバから取得する。紹介コンテンツの取得については後述する。
 店舗商品は、例えば、食品や衣料品、電化製品等である。コンテンツは、例えば、テレビジョン番組やラジオ番組自体である。なお、コンテンツは、テレビジョン放送局が放送しているテレビジョン番組を時間で分割したときの分割された一部分、テレビジョン番組内のコーナー、あるいは複数のテレビジョン番組にまたがる時間帯のコンテンツであってもよい。
 また、コンテンツは、ラジオ放送局が放送しているラジオ番組を時間で分割したときの分割された一部分、ラジオ番組内のコーナー、あるいは複数のラジオ番組にまたがる時間帯のコンテンツであってもよい。
The sales promotion effect estimation server 4 includes, for example, information relating to products that can be handled by the store “Shp”, or information that will be handled in the future (hereinafter referred to as store products), and content that includes information related to store products (hereinafter referred to as introduction content). ) (For example, a television program name, a radio program name, a broadcast date, etc. of the introduction content) is acquired from various servers connected to the network NW. Acquisition of introduction content will be described later.
Store merchandise is, for example, food, clothing, or electrical appliances. The content is, for example, a television program or a radio program itself. Note that the content is content that is divided when a television program broadcast by a television broadcast station is divided by time, a corner in a television program, or a time zone that spans multiple television programs. May be.
In addition, the content may be content that is divided when a radio program broadcast by a radio broadcasting station is divided by time, a corner in the radio program, or a time zone that spans multiple radio programs.
 以下の説明では、コンテンツは、テレビジョン番組自体である場合について説明する。また、店舗商品に関する情報が含まれたコンテンツとは、例えば、店舗商品が紹介されたコンテンツや、店舗商品が映ったコンテンツ、店舗商品の名前が登場したコンテンツ等である。
 以下の説明では、店舗商品に関する情報が含まれたコンテンツは、店舗商品が紹介されたコンテンツである場合について説明する。また、コンテンツに複数の店舗商品に関する情報が含まれる場合、販促効果推定サーバ4は、個々の店舗商品毎に、以下の処理を行う。
In the following description, the case where the content is a television program itself will be described. The content including information related to the store product includes, for example, content that introduces the store product, content that shows the store product, and content in which the name of the store product appears.
In the following description, the case where the content including information related to the store product is content in which the store product is introduced will be described. Moreover, when the information regarding a some store product is contained in a content, the sales promotion effect estimation server 4 performs the following processes for every store product.
 販促効果推定サーバ4は、取得した店舗商品に関する情報と、紹介コンテンツに付随する情報とに基づいて、店舗商品に対する紹介コンテンツによる販売を促進させる効果(以下、販促効果という)を推定する。
 販促効果推定サーバ4は、推定した販促効果を示す係数と、POSサーバ7から取得する店舗商品の通常の発注量(以下、通常発注量という)とに基づいて、好適な発注量(以下、好適発注量という)を算出する。また、販促効果推定サーバ4は、紹介コンテンツに付随する情報に基づいて、紹介コンテンツで店舗商品が紹介されたことを示す情報(以下、紹介情報という)を生成する。
 販促効果推定サーバ4は、算出した好適発注量と、生成した紹介情報とを、店舗装置3に出力する。また、販促効果推定サーバ4は、取得した店舗商品に関する情報と、紹介コンテンツに関する情報とに基づいて、販促効果へ影響を与えたと考えられる紹介コンテンツに付随する情報をまとめた販促効果情報画像を生成する。
 販促効果推定サーバ4は、生成した販促効果情報画像を、店舗装置3からの操作(要求)に従い、必要に応じて店舗装置3に出力する。
The sales promotion effect estimation server 4 estimates an effect (hereinafter referred to as a sales promotion effect) of promoting sales by the introduction content for the store product based on the acquired information on the store product and information accompanying the introduction content.
The sales promotion effect estimation server 4 uses a coefficient indicating the estimated sales promotion effect and a normal order quantity (hereinafter referred to as a normal order quantity) of the store product acquired from the POS server 7 to obtain a suitable order quantity (hereinafter referred to as a preferred order quantity). Calculate the order quantity). Further, the sales promotion effect estimation server 4 generates information (hereinafter referred to as introduction information) indicating that the store product has been introduced in the introduction content based on the information accompanying the introduction content.
The sales promotion effect estimation server 4 outputs the calculated preferred order quantity and the generated introduction information to the store apparatus 3. Further, the sales promotion effect estimation server 4 generates a sales promotion effect information image in which information associated with the introduction content that is considered to have influenced the sales promotion effect is generated based on the acquired information on the store product and the information on the introduction content. To do.
The sales promotion effect estimation server 4 outputs the generated sales promotion effect information image to the store apparatus 3 as necessary in accordance with an operation (request) from the store apparatus 3.
 図2は、第1の実施形態における販促効果情報画像の一例を示す図である。
 図2に示すように、販促効果情報画像“img”は、例えば、画像p1~画像p11によって構成される。販促効果推定サーバ4は、店舗商品の販促効果へ影響を与えたと考えられる紹介コンテンツのうち、最も視聴率の高かった紹介コンテンツの情報を表示する紹介コンテンツ情報画像を画像p1として生成する。
 なお、視聴率は、全国視聴率又は店舗“Shp”を含む地域での視聴率(以下、地域視聴率という)でもよい。また、視聴率は、全国視聴率と地域視聴率の組み合わせを比較し、全国視聴率又は地域視聴率のいずれか一方を優先したものでもよい。販促効果推定サーバ4は、全国視聴率を表示する全国視聴率画像を画像p2として生成する。
 販促効果推定サーバ4は、地域視聴率を表示する地域視聴率画像を画像p3として生成する。販促効果推定サーバ4は、店舗商品に関してWebサイトから得られる情報を表示するサイト情報画像を画像p4として生成する。
FIG. 2 is a diagram illustrating an example of a sales promotion effect information image according to the first embodiment.
As shown in FIG. 2, the sales promotion effect information image “img” is composed of, for example, images p1 to p11. The sales promotion effect estimation server 4 generates, as an image p1, an introduction content information image that displays information on the introduction content having the highest audience rating among the introduction contents that are considered to have influenced the sales promotion effect of the store product.
The audience rating may be the national audience rating or the audience rating in the area including the store “Shp” (hereinafter referred to as the regional audience rating). The audience rating may be a combination of the national audience rating and the regional audience rating, with priority given to either the national audience rating or the local audience rating. The sales promotion effect estimation server 4 generates a national audience rating image displaying the national audience rating as an image p2.
The sales promotion effect estimation server 4 generates a regional audience rating image displaying the regional audience rating as an image p3. The sales promotion effect estimation server 4 produces | generates the site information image which displays the information obtained from a website regarding a store product as the image p4.
 販促効果推定サーバ4は、紹介コンテンツの内容を表示する販促コンテンツ内容画像を画像p5として生成する。販促効果推定サーバ4は、所定の期間における視聴露出時間グラフを画像p6として生成する。視聴露出時間グラフの詳細は後述する。販促効果推定サーバ4は、通常発注量及び好適発注量を表示する発注量画像を画像p7として生成する。
 販促効果推定サーバ4は、紹介コンテンツの動画像を、コンテンツ記録サーバ10から取得し、取得した動画像をキャプチャしたキャプチャ画像を画像p8として生成する。
The sales promotion effect estimation server 4 produces | generates the sales promotion content content image which displays the content of introduction content as the image p5. The sales promotion effect estimation server 4 generates a viewing exposure time graph for a predetermined period as an image p6. Details of the viewing exposure time graph will be described later. The sales promotion effect estimation server 4 generates an order quantity image that displays the normal order quantity and the preferred order quantity as an image p7.
The sales promotion effect estimation server 4 acquires a moving image of the introduction content from the content recording server 10, and generates a captured image obtained by capturing the acquired moving image as an image p8.
 販促効果推定サーバ4は、店舗“Shp”を含む地域で放送されたコンテンツに、店舗商品が登場した累計時間を表示する地域露出時間画像を画像p9として生成する。販促効果推定サーバ4は、店舗“Shp”を含む地域で放送された紹介コンテンツに店舗商品が登場した累計時間と、紹介コンテンツを視聴していたテレビジョン受像機の数とを乗算して得られる総合視聴時間を表示する総合視聴時間画像を画像p10として生成する。
 販促効果推定サーバ4は、視聴率が上位3位以内に入る紹介コンテンツの内容とともに、それぞれの紹介コンテンツの地域視聴率を表示する紹介コンテンツ内容画像を画像p11として生成する。販促効果情報画像“img”の生成についての詳細は後述する。
The sales promotion effect estimation server 4 generates, as an image p9, an area exposure time image that displays the accumulated time that the store product appears in the content broadcast in the area including the store “Shp”. The sales promotion effect estimation server 4 is obtained by multiplying the cumulative time when the store product appears in the introduction content broadcast in the area including the store “Shp” by the number of television receivers viewing the introduction content. A total viewing time image displaying the total viewing time is generated as an image p10.
The sales promotion effect estimation server 4 generates, as an image p11, an introductory content detail image that displays the local audience rating of each introductory content together with the introductory content that ranks in the top three. Details of generation of the sales promotion effect information image “img” will be described later.
 店舗装置3は、例えば、POS(Point Of Sale)アプリケーションがインストールされたコンピュータである。また、店舗装置3は、例えば、バーコードリーダやキーボード等の入力装置、及び、オペレータディスプレイ(操作用表示器)やカスタマディスプレイ(顧客用表示器)等の表示装置を備える。店舗装置3は、バーコードリーダにより、商品に付されたバーコード(商品ID等が記録されている)を読み取る。
 また、店舗装置3は、キーボードにより発注量等の必要な情報の入力を受け付ける。店舗装置3は、店舗商品の好適発注量と、紹介情報とを、ネットワークNWを介して、販促効果推定サーバ4から取得する。また、店舗装置3は、店舗商品に関する情報及び前述した通常発注量を、POSサーバ7から取得する。
The store apparatus 3 is, for example, a computer in which a POS (Point Of Sale) application is installed. Further, the store apparatus 3 includes, for example, an input device such as a barcode reader or a keyboard, and a display device such as an operator display (operation display) or a customer display (customer display). The store apparatus 3 reads a barcode attached to a product (a product ID or the like is recorded) with a barcode reader.
Further, the store apparatus 3 accepts input of necessary information such as an order amount through a keyboard. The store apparatus 3 acquires the preferred order quantity of the store product and the introduction information from the sales promotion effect estimation server 4 via the network NW. Further, the store apparatus 3 acquires information related to store products and the above-described normal order quantity from the POS server 7.
 店舗装置3は、取得した店舗商品に関する情報及び好適発注量と、紹介情報とに基づいて、店舗商品に対する発注画面を生成する。店舗装置3は、ユーザ(例えば、店舗の運営者)が選択した店舗商品の発注画面を表示する操作を受けると、ユーザが選択した店舗商品が紹介コンテンツで紹介された商品だった場合、生成した発注画面を表示する。
 一方、ユーザが選択した店舗商品が紹介コンテンツで紹介されていない商品だった場合、店舗装置3は、デフォルト画面として、取得した通常発注量に基づいて生成した発注画面を店舗装置3のディスプレイに表示する。なお、第1の実施形態において、店舗装置3は、POSサーバ7から店舗商品に関する情報及び通常発注量を取得する場合について説明したが、これに限られない。例えば、ユーザが店舗商品に関する情報及び通常発注量を、キーボード等で入力してもよい。
The store apparatus 3 generates an order screen for the store product based on the acquired information about the store product, the preferred order quantity, and the introduction information. When the store apparatus 3 receives an operation for displaying an order screen for a store product selected by a user (for example, a store operator), the store device 3 is generated if the store product selected by the user is a product introduced in the introduction content. Display the ordering screen.
On the other hand, if the store product selected by the user is a product that is not introduced in the introduction content, the store apparatus 3 displays the order screen generated based on the acquired normal order quantity on the display of the store apparatus 3 as a default screen. To do. In addition, in 1st Embodiment, although the shop apparatus 3 demonstrated the case where the information regarding shop goods and the normal order quantity were acquired from the POS server 7, it is not restricted to this. For example, the user may input information related to store products and the normal order quantity with a keyboard or the like.
 図3は、第1の実施形態における発注画面の一例を示す図である。
 店舗装置3は、取得した好適発注量を、発注量“size”に表示させた発注画面“order”を生成し、取得した紹介情報に基づいて、注意喚起画像“ntc”を生成し、生成した注意喚起画像“ntc”を、図3に示すように配置する。
 注意喚起画像“ntc”には、詳細ボタン“btn”が配置される。ユーザが詳細ボタン“btn”を選択決定すると、販促効果推定サーバ4は、店舗商品に対する販促効果情報画像“img”を、販促効果推定サーバ4から取得し、取得した販促効果情報画像“img”を店舗装置3のディスプレイに表示する。
 なお、店舗装置3は、販促効果情報画像“img”に音声が付随している場合には、音声を出力してもよい。また、第1の実施形態において、店舗装置3は、ユーザが発注画面“order”の発注ボタンを選択決定することによって発注が行われるが、これに限られない。店舗装置3は、例えば、ユーザによる操作を行うことなく、取得した好適発注量を自動で発注してもよい。
FIG. 3 is a diagram illustrating an example of an ordering screen according to the first embodiment.
The store apparatus 3 generates an ordering screen “order” in which the acquired preferred order quantity is displayed in the order quantity “size”, and generates an alert image “ntc” based on the acquired introduction information. The alert image “ntc” is arranged as shown in FIG.
A detail button “btn” is arranged in the alert image “ntc”. When the user selects and determines the detail button “btn”, the sales promotion effect estimation server 4 acquires the sales promotion effect information image “img” for the store product from the sales promotion effect estimation server 4, and acquires the acquired sales promotion effect information image “img”. It is displayed on the display of the store apparatus 3.
Note that the store apparatus 3 may output a sound when the sales promotion effect information image “img” is accompanied by a sound. In the first embodiment, the store apparatus 3 places an order by the user selecting and determining the order button on the order screen “order”. However, the present invention is not limited to this. For example, the store apparatus 3 may automatically place an order for the acquired preferred order quantity without any user operation.
 店舗装置3は、取得した紹介情報から紹介コンテンツの視聴率を抽出し、抽出した視聴率が所定の閾値を超えていた場合、例えば、その紹介コンテンツが紹介した店舗商品の発注量を増やすことを促すアラート画像を生成し、生成したアラート画像をハンディーターミナル2に出力して表示させる。
 なお、店舗装置3は、紹介情報から紹介コンテンツの視聴率の変化率を抽出し、抽出した変化率が所定の閾値を超えていた場合、その紹介コンテンツが紹介した店舗商品の発注量を増やすことを促すアラート画像を生成してもよい。
 また、店舗装置3は、前述した販促効果を示す係数を取得し、取得した販促効果を示す係数が所定の閾値を超えたか否かを判定し、判定結果に基づいてアラート画像を生成してもよい。
The store apparatus 3 extracts the audience rating of the introduction content from the acquired introduction information, and when the extracted audience rating exceeds a predetermined threshold, for example, the order amount of the store product introduced by the introduction content is increased. An alert image for prompting is generated, and the generated alert image is output to the handy terminal 2 and displayed.
The store apparatus 3 extracts the rate of change of the viewing rate of the introduction content from the introduction information, and if the extracted rate of change exceeds a predetermined threshold, the order amount of the store product introduced by the introduction content is increased. An alert image that prompts the user may be generated.
Further, the store apparatus 3 acquires the coefficient indicating the sales promotion effect described above, determines whether or not the acquired coefficient indicating the sales promotion effect exceeds a predetermined threshold, and generates an alert image based on the determination result. Good.
 図4は、第1の実施形態におけるアラート画像の一例を示す図である。
 なお、所定の閾値は、予め設定されてもよいし、ユーザが後から設定してもよい。また、店舗装置3は、抽出した視聴率が所定の閾値を超えていた場合、その直後にアラート画像“alrt”を生成し、生成したアラート画像“alrt”をハンディーターミナル2に出力してもよいが、これに限られない。
 店舗装置3は、一日のうちの所定の時刻に、それまでの一日の間に所定の閾値を超えた視聴率に対応する店舗商品の発注量を増やすことを促す情報を、視聴率の高い順に並べたレポート画像を生成し、生成したレポート画像をハンディーターミナル2に出力してもよい。
FIG. 4 is a diagram illustrating an example of an alert image according to the first embodiment.
The predetermined threshold value may be set in advance or may be set later by the user. Further, when the extracted audience rating exceeds a predetermined threshold, the store apparatus 3 may generate an alert image “alrt” immediately after that and output the generated alert image “alrt” to the handy terminal 2. However, it is not limited to this.
The store apparatus 3 displays information that prompts the customer to increase the order quantity of store products corresponding to the audience rating that exceeds a given threshold during the day until the given time of the day. Report images arranged in descending order may be generated, and the generated report images may be output to the handy terminal 2.
 第1の実施形態における図5は、レポート画像の一例を示す図である。 FIG. 5 in the first embodiment is a diagram illustrating an example of a report image.
 ハンディーターミナル2は、例えば、業務用PDA(Personal Digital Assistant)等の携帯情報端末である。ハンディーターミナル2は、店舗装置3からアラート画面、あるいは、レポート画像“rprt”を取得すると、ディスプレイに取得した画像を表示し、ユーザに販促番組によって紹介された店舗商品の発注量の調整(例えば、発注量を増やす)を促す。 The handy terminal 2 is a portable information terminal such as a business PDA (Personal Digital Assistant). When the handy terminal 2 acquires the alert screen or the report image “rprt” from the store apparatus 3, the handy terminal 2 displays the acquired image on the display, and adjusts the order quantity of the store product introduced to the user by the sales promotion program (for example, Increase order volume).
 図6は、第1の実施形態におけるハンディーターミナル2にアラート画面“alrt”が表示された図の一例である。 FIG. 6 is an example of a diagram in which an alert screen “alrt” is displayed on the handy terminal 2 in the first embodiment.
 POSサーバ7は、POSシステムを制御するサーバである。POSサーバ7は、各種サーバや装置から商品IDを受け付け、受け付けた商品IDが指し示す店舗商品、店舗商品の価格、店舗商品の通常発注量等、店舗商品に関する情報(以下、商品情報という)を検索し、検索した商品情報を、各種サーバや装置に出力する。 The POS server 7 is a server that controls the POS system. The POS server 7 receives product IDs from various servers and devices, and searches for store product information (hereinafter referred to as product information) such as store products indicated by the received product IDs, store product prices, and normal order quantities of store products. Then, the retrieved product information is output to various servers and devices.
 店舗商品サーバ5は、店舗商品テーブルを記憶する。 The store product server 5 stores a store product table.
 図7は、第1の実施形態における店舗商品サーバ5に記憶される店舗商品テーブルt51の一例である。
 図7に示すように、店舗商品テーブルt51は、例えば、店舗商品を識別する商品ID、商品名、産地、商品の価格等を格納するが、これに限られない。例えば、店舗商品テーブルt51は、商品の在庫数や、既発注量や、販売目標達成率等を格納してもよい。
FIG. 7 is an example of the store product table t51 stored in the store product server 5 in the first embodiment.
As illustrated in FIG. 7, the store product table t51 stores, for example, a product ID for identifying a store product, a product name, a place of production, a price of the product, and the like, but is not limited thereto. For example, the store product table t51 may store the number of items in stock, the quantity already ordered, the sales target achievement rate, and the like.
 店舗商品補足サーバ6は、店舗商品テーブルt51に格納されている各種商品名及び/又は商品IDに対応付けられた補足情報を、補足情報テーブルとして記憶する。第1の実施形態では、補足情報は、商品ID及び商品名の両方に対応付けられる場合について説明するが、いずれか一方に対応付けられてもよい。
 補足情報は、例えば、商品に関連するキーワード(以下、商品キーワードという)である。商品キーワードは、例えば、商品名に対応する商品の種類である。具体的には、商品キーワードは、商品が食品の場合には品種等が該当し、商品が衣料品の場合にはブランド名等が該当する。第1の実施形態では、説明を簡略化するために、一つの商品名毎に一つの商品キーワードが対応付けられている場合について説明するが、これに限られず、一つの商品に複数の商品キーワードが対応付けられてもよい。
The store product supplement server 6 stores supplement information associated with various product names and / or product IDs stored in the store product table t51 as a supplement information table. In the first embodiment, supplementary information is described as being associated with both a product ID and a product name, but may be associated with either one.
The supplemental information is, for example, a keyword related to a product (hereinafter referred to as a product keyword). The product keyword is, for example, a product type corresponding to the product name. Specifically, the product keyword corresponds to a variety or the like when the product is food, and a brand name or the like when the product is clothing. In the first embodiment, in order to simplify the description, a case where one product keyword is associated with each product name will be described. However, the present invention is not limited to this, and a plurality of product keywords are associated with one product. May be associated.
 図8は、第1の実施形態における店舗商品補足サーバ6に記憶される、補足情報テーブルt61の一例を示す図である。
 補足情報テーブルt61は、商品ID、商品名とともに、これらに対応付けられた商品キーワードを格納する。また、補足情報テーブルt61は、商品ID及び商品名を通して、図7の店舗商品テーブルt51と対応付けられる。
FIG. 8 is a diagram illustrating an example of the supplement information table t61 stored in the store product supplement server 6 according to the first embodiment.
The supplementary information table t61 stores a product keyword associated with the product ID and the product name. Further, the supplementary information table t61 is associated with the store product table t51 of FIG. 7 through the product ID and the product name.
 視聴ログサーバ8は、全国のテレビジョン受像機から収集された視聴ログを記憶する。視聴ログは、例えば、視聴された放送局を識別する放送局識別IDと、コンテンツが放送された時間とを対応付けて記憶した情報である。視聴ログは、視聴ログを収集可能な全国又は地域毎のテレビジョン受像機から収集される。なお、視聴ログは、テレビジョン受像機によるコンテンツの視聴に関して、リアルタイムでの視聴ログだけではなく、録画された場合や、録画予約された場合も視聴したものとして記録されてもよい。 The viewing log server 8 stores viewing logs collected from television receivers nationwide. The viewing log is information that stores, for example, a broadcast station identification ID that identifies a broadcast station that has been viewed and a time when the content is broadcast. The viewing log is collected from a television receiver for each country or region where the viewing log can be collected. Note that the viewing log may be recorded not only as a real-time viewing log but also as a view when the content is recorded or reserved for recording when viewing the content by the television receiver.
 コンテンツ情報サーバ9は、全国のテレビジョン受像機に対して放送される各種コンテンツの内容に関する情報(以下、コンテンツ情報という)を、コンテンツ情報テーブルとして記憶する。コンテンツ情報は、例えば、コンテンツの内容を記述した情報である。コンテンツ情報は、コンテンツと、コンテンツ内で起こった出来事(以下、イベントという)に関連した情報とが対応付けられた情報である。 The content information server 9 stores information on the contents of various contents broadcast to television receivers nationwide (hereinafter referred to as content information) as a content information table. The content information is, for example, information describing content details. The content information is information in which content and information related to an event (hereinafter referred to as an event) occurring in the content are associated with each other.
 図9は、第1の実施形態におけるコンテンツ情報サーバ9に記憶されるコンテンツ情報テーブルt91の一例を示す図である。
 コンテンツ情報テーブルt91は、レコード毎に、識別ID、イベント開始時刻、イベント終了時刻、コンテンツ(テレビジョン番組名)、イベントが起こった時のコーナー名(以下、イベント包含コーナーという)、イベントの内容を表す情報(以下、イベント内容情報という)、及び放送局IDを対応付けて格納する。
 コンテンツ情報には、情報を識別するための識別IDが付与される。イベントとは、例えば、出演者が発言したり、映像が流れたりといった一つ一つの出来事を示す。
FIG. 9 is a diagram illustrating an example of the content information table t91 stored in the content information server 9 according to the first embodiment.
The content information table t91 includes, for each record, an identification ID, an event start time, an event end time, content (television program name), a corner name when an event occurs (hereinafter referred to as an event inclusion corner), and the contents of the event. Information to be represented (hereinafter referred to as event content information) and a broadcast station ID are stored in association with each other.
The content information is given an identification ID for identifying the information. For example, an event indicates an event such as a speech made by a performer or a video stream.
 イベントに関連した情報とは、例えば、イベント毎に、イベントが起こった時刻(以下、イベント開始時刻という)、イベントが終わった時刻(以下、イベント終了時刻という)、イベント内容情報、イベント包含コーナー、及びイベントが起こったテレビジョン番組を放送している放送局を識別する放送局ID等が記述された情報である。
 イベント内容情報とは、例えば、イベント中に紹介された店舗名、商品名や、イベントが起こっている間に映った出演者の発言内容、出演者名、出演者の動き、出演者の表情等をテキスト情報で記録したものである。図9では、コンテンツ情報テーブルt91の一部分のみを示したが、実際にはコンテンツ情報テーブルt91は、全国又は地域で放送されたコンテンツに対応したコンテンツ情報を全て格納する。
Information related to events includes, for example, the time at which an event occurred (hereinafter referred to as event start time), the time at which the event ended (hereinafter referred to as event end time), event content information, event inclusion corner, And information describing a broadcasting station ID for identifying a broadcasting station broadcasting a television program in which an event has occurred.
Event content information includes, for example, the name of the store introduced during the event, the name of the product, the remarks of the performer reflected during the event, the name of the performer, the movement of the performer, the facial expression of the performer, etc. Is recorded as text information. Although only a part of the content information table t91 is shown in FIG. 9, the content information table t91 actually stores all the content information corresponding to the content broadcast in the whole country or region.
 コンテンツ記録サーバ10は、全国の各テレビジョン放送局が放送しているコンテンツを録画し、コンテンツ毎の動画であるコンテンツ動画として記憶する。コンテンツ記録サーバ10は、販促効果推定サーバ4からのコンテンツ動画取得要求に従い、販促効果推定サーバ4に、コンテンツ動画を送信する。 The content recording server 10 records the content broadcast by each television broadcasting station nationwide and stores it as a content video that is a video for each content. The content recording server 10 transmits the content video to the sales promotion effect estimation server 4 in accordance with the content video acquisition request from the sales promotion effect estimation server 4.
 図10は、第1の実施形態における販促効果推定サーバ4の構成の一例を示す概略ブロック図である。
 販促効果推定サーバ4は、例えば、通信部101、店舗商品取得部102、商品補足情報取得部104、紹介コンテンツ特定情報取得部105、紹介コンテンツ特定情報記憶部106、視聴率算出部107、好適コンテンツ選択部108、販促効果推定部110、通常発注量取得部111、販促効果情報画像生成部112、販促効果情報画像記憶部113、ユーザ入力情報受付部114、ユーザ入力情報記憶部115、及び好適発注量算出部116を含む。
FIG. 10 is a schematic block diagram showing an example of the configuration of the sales promotion effect estimation server 4 in the first embodiment.
The sales promotion effect estimation server 4 includes, for example, a communication unit 101, a store product acquisition unit 102, a product supplement information acquisition unit 104, an introduction content specification information acquisition unit 105, an introduction content specification information storage unit 106, an audience rating calculation unit 107, and a suitable content. Selection unit 108, sales promotion effect estimation unit 110, normal order quantity acquisition unit 111, sales promotion effect information image generation unit 112, sales promotion effect information image storage unit 113, user input information reception unit 114, user input information storage unit 115, and preferred order A quantity calculation unit 116 is included.
 通信部101は、例えば、ネットワークカードであり、LANやネットワークNWを通して、各種サーバと通信する。また、通信部101は、商品補足情報取得部104、紹介コンテンツ特定情報取得部105、通常発注量取得部111等からの指示(要求)に応じて、店舗商品サーバ5、店舗商品補足サーバ6、POSサーバ7、視聴ログサーバ8、コンテンツ情報サーバ9、コンテンツ記録サーバ10のそれぞれと通信する。 The communication unit 101 is, for example, a network card, and communicates with various servers through a LAN or a network NW. In addition, the communication unit 101 responds to an instruction (request) from the product supplement information acquisition unit 104, the introduction content specifying information acquisition unit 105, the normal order quantity acquisition unit 111, etc., the store product server 5, the store product supplement server 6, It communicates with each of the POS server 7, the viewing log server 8, the content information server 9, and the content recording server 10.
 店舗商品取得部102は、例えば、店舗商品テーブルt51を、店舗商品サーバ5から取得し、取得した店舗商品テーブルt51から商品IDを一つずつ選択し、選択した商品IDを店舗商品補足情報取得部104に出力する。
 店舗商品取得部102は、取得した商品IDを、商品補足情報取得部104に出力する。なお、以下では、店舗商品取得部102は、商品IDを一つのみ店舗補足情報取得部104に出力した場合について説明するが、商品IDが複数ある場合には、商品ID毎に同様の処理を繰り返し実行する。
 なお、第1の実施形態において、店舗商品取得部102は、店舗商品サーバ5から店舗商品テーブルt51を取得し、取得した店舗商品テーブルt51から商品IDを一つずつ選択したが、これに限られない。店舗商品取得部102は、例えば、ユーザが発注しようとした店舗商品を店舗装置3から取得し、取得した店舗商品の商品IDを、店舗商品サーバ5から検索して取得し、取得した商品IDを、店舗商品補足情報取得部104に出力してもよい。
 また、以下では、店舗商品取得部102は、商品IDを一つのみ店舗補足情報取得部104に出力する場合について説明するが、商品IDが複数ある場合には、以下の処理を繰り返し実行する。
The store product acquisition unit 102 acquires, for example, the store product table t51 from the store product server 5, selects one product ID from the acquired store product table t51 one by one, and selects the selected product ID as a store product supplement information acquisition unit. To 104.
The store product acquisition unit 102 outputs the acquired product ID to the product supplement information acquisition unit 104. In the following, the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplementary information acquisition unit 104. However, when there are a plurality of product IDs, the same processing is performed for each product ID. Run repeatedly.
In the first embodiment, the store product acquisition unit 102 acquires the store product table t51 from the store product server 5 and selects the product IDs one by one from the acquired store product table t51. However, the present invention is not limited to this. Absent. The store product acquisition unit 102 acquires, for example, a store product that the user is trying to place an order from the store apparatus 3, searches the store product server 5 for the product ID of the acquired store product, and acquires the acquired product ID. , It may be output to the store product supplement information acquisition unit 104.
Hereinafter, the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplemental information acquisition unit 104. However, when there are a plurality of product IDs, the following processing is repeatedly executed.
 商品補足情報取得部104は、例えば、取得した商品IDに対応付けられた補足情報(商品キーワード)を、店舗商品補足サーバ6から取得する。商品補足情報取得部104は、取得した商品キーワードを紹介コンテンツ特定情報取得部105に出力する。 The product supplement information acquisition unit 104 acquires supplement information (product keyword) associated with the acquired product ID from the store product supplement server 6, for example. The product supplementary information acquisition unit 104 outputs the acquired product keyword to the introduction content specifying information acquisition unit 105.
 紹介コンテンツ特定情報取得部105は、取得した商品キーワードが含まれるイベント内容情報に対応付けられたコンテンツを特定する情報(以下、紹介コンテンツ特定情報という)を、コンテンツ情報サーバ9から取得する。
 以下では、紹介コンテンツは、テレビジョン番組名で特定されるコンテンツである場合について説明する。ここで、紹介コンテンツ特定情報を取得する具体的な例を説明する。
 図9のコンテンツ情報テーブルt91において、識別IDが“3434366”のレコードを見ると、イベント内容情報として「いちご」というキーワードを含んでいる。この「いちご」が販促商品の商品キーワードだった場合、このレコードに含まれる情報が、紹介コンテンツ特定情報として取得される。
The introductory content specifying information acquisition unit 105 acquires information (hereinafter referred to as introductory content specifying information) for specifying the content associated with the event detail information including the acquired product keyword from the content information server 9.
Hereinafter, a case where the introduction content is content specified by a television program name will be described. Here, a specific example of acquiring the introduction content specifying information will be described.
In the content information table t91 of FIG. 9, when a record with the identification ID “3434366” is seen, the keyword “strawberry” is included as event content information. When this “strawberry” is the product keyword of the sales promotion product, information included in this record is acquired as introduction content specifying information.
 図11は、第1の実施形態における紹介コンテンツ特定情報取得部105が取得した紹介コンテンツ特定情報を格納した紹介コンテンツ特定情報テーブルt1051の一例を示す図である。
 図11に示すように、紹介コンテンツ特定情報テーブルt1051は、商品キーワードが含まれるコンテンツを、図9に示すコンテンツ情報テーブルt91から抽出したテーブルである。紹介コンテンツ特定情報取得部105は、取得した紹介コンテンツ特定情報を紹介コンテンツ特定情報テーブルt1051として、紹介コンテンツ特定情報記憶部106に記憶させる。
 紹介コンテンツ特定情報記憶部106は、RAM(Random Access Memory)やレジスタ、あるいは、HDD(Hard Disk Drive)やSSD(Solid State Drive)等の記録媒体である。紹介コンテンツ特定情報記憶部106は、紹介コンテンツ特定情報テーブルt1051を記憶する。
FIG. 11 is a diagram illustrating an example of the introduction content identification information table t1051 that stores the introduction content identification information acquired by the introduction content identification information acquisition unit 105 according to the first embodiment.
As illustrated in FIG. 11, the introduction content specifying information table t1051 is a table obtained by extracting the content including the product keyword from the content information table t91 illustrated in FIG. 9. The introduction content specific information acquisition unit 105 stores the acquired introduction content specification information in the introduction content specification information storage unit 106 as an introduction content specification information table t1051.
The introduction content specifying information storage unit 106 is a RAM (Random Access Memory), a register, or a recording medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The introductory content specific information storage unit 106 stores an introductory content specific information table t1051.
 視聴率算出部107は、紹介コンテンツ特定情報テーブルt1051を、紹介コンテンツ特定情報記憶部106から読み込む。視聴率算出部107は、読み込んだ紹介コンテンツ特定情報テーブルt1051に基づいて、紹介コンテンツの視聴ログを、視聴ログサーバ8から取得する。
 視聴率算出部107は、取得した視聴ログに基づいて、紹介コンテンツの視聴率を算出し、コンテンツ視聴率テーブルを生成する。
The audience rating calculation unit 107 reads the introduction content identification information table t1051 from the introduction content identification information storage unit 106. The audience rating calculation unit 107 acquires the viewing log of the introduction content from the viewing log server 8 based on the read introduction content specifying information table t1051.
The audience rating calculation unit 107 calculates the audience rating of the introduction content based on the acquired viewing log, and generates a content audience rating table.
 図12は、第1の実施形態におけるコンテンツ視聴率テーブルt1071の一例である。
 コンテンツ視聴率テーブルt1071は、紹介コンテンツを含むイベント包含コーナーと、紹介コンテンツ特定情報であるテレビジョン番組名と、イベント開始時刻及びイベント終了時刻と、紹介コンテンツの全国視聴率及び地域視聴率とを格納する。視聴率算出処理の詳細については後述する。
 なお、視聴率算出部107は、視聴率を算出する場合について説明したが、これに限られず、例えば、視聴率算出部107は、視聴率の変化率を算出してよい。また、その場合、コンテンツ視聴率テーブルt1071は、視聴率とともに、視聴率の変化率を格納する。視聴率算出部107は、生成したコンテンツ視聴率テーブルt1071を、好適コンテンツ選択部108に出力する。
FIG. 12 is an example of the content audience rating table t1071 in the first embodiment.
The content audience rating table t1071 stores the event inclusion corner including the introduction content, the television program name as the introduction content specifying information, the event start time and the event end time, and the national audience rating and the local audience rating of the introduction content. To do. Details of the audience rating calculation process will be described later.
Note that the audience rating calculation unit 107 has been described for calculating the audience rating, but the present invention is not limited to this. For example, the audience rating calculation unit 107 may calculate the rate of change of the audience rating. In this case, the content audience rating table t1071 stores the audience rating change rate together with the audience rating. The audience rating calculation unit 107 outputs the generated content audience rating table t1071 to the preferred content selection unit 108.
 なお、視聴率算出部107は、紹介コンテンツの視聴率を算出したが、これに限られず、紹介コンテンツを含むイベント包含コーナーの視聴率を算出してもよい。その場合、視聴率算出部107は、紹介コンテンツ特定情報に基づいて、紹介コンテンツを含むイベント包含コーナーの視聴ログを、視聴ログサーバ8から取得する。 Note that the audience rating calculation unit 107 calculates the audience rating of the introductory content, but is not limited to this, and the audience rating of the event inclusion corner including the introductory content may be calculated. In that case, the audience rating calculation unit 107 acquires the viewing log of the event inclusion corner including the introduction content from the viewing log server 8 based on the introduction content specifying information.
 好適コンテンツ選択部108は、取得したコンテンツ視聴率テーブルt1071から紹介コンテンツを一つずつ選択する。好適コンテンツ選択部108は、選択した紹介コンテンツに対応するイベント内容情報を、紹介コンテンツ特定情報記憶部106から読み込む。
 好適コンテンツ選択部108は、読み込んだイベント内容情報に対して、自然言語解析を行う。好適コンテンツ選択部108は、この自然言語解析によって、選択した紹介コンテンツが、負の印象を連想させる言葉を含むイベント内容情報(以下、負内容情報という)と対応付いているか否かを判定(以下、負印象判定という)する。
The suitable content selection unit 108 selects introduction contents one by one from the acquired content audience rating table t1071. The preferred content selection unit 108 reads event content information corresponding to the selected introduction content from the introduction content specifying information storage unit 106.
The preferred content selection unit 108 performs natural language analysis on the read event content information. The preferred content selection unit 108 determines whether or not the selected introduction content is associated with event content information (hereinafter referred to as negative content information) including a word reminiscent of a negative impression through the natural language analysis (hereinafter referred to as negative content information). , Called negative impression determination).
 負の印象を連想させる言葉は、例えば、「死」、「事件」、及び「事故」等である。好適コンテンツ選択部108は、選択した紹介コンテンツが、負内容情報と対応付いている場合、選択した紹介コンテンツを含む全てのレコードを、コンテンツ視聴率テーブルt1071から除外する(以下、テーブル好適化処理という)。
 好適コンテンツ選択部108は、コンテンツ視聴率テーブルt1071内の全ての紹介コンテンツに対して負印象判定を行った後、除外されずに残ったレコードが格納されているコンテンツ視聴率テーブルを、好適コンテンツ視聴率テーブルとして、販促効果推定部110に出力する。
Examples of words associated with a negative impression are “death”, “incident”, and “accident”. When the selected introduction content is associated with the negative content information, the suitable content selection unit 108 excludes all records including the selected introduction content from the content audience rating table t1071 (hereinafter referred to as table optimization processing). ).
The preferred content selection unit 108 performs a negative impression determination on all the introduction contents in the content audience rating table t1071, and then uses the content audience rating table in which records remaining without being excluded are stored in the preferred content viewing table. It outputs to the sales promotion effect estimation part 110 as a rate table.
 販促効果推定部110は、取得した好適コンテンツ視聴率テーブルの中から、最も地域視聴率の高い紹介コンテンツ特定情報を抽出する。販促効果推定部110は、抽出した紹介コンテンツ特定情報が指し示す紹介コンテンツを、好適発注量を算出するための主たる情報源であるコンテンツ(以下、販促コンテンツという)として選択する。
 販促効果推定部110は、選択した販促コンテンツと、ユーザ入力情報とに基づいて、販促効果を示す係数を算出する。ユーザ入力情報は、販促効果を示す係数を算出する際に利用する情報であって、販促コンテンツが放送される前にマスメディアが予想した販促コンテンツの予想視聴率である。
 販促効果推定部110は、ユーザ入力情報を、ユーザ入力情報記憶部115から取得する。また、販促効果推定部110は、販促効果を示す係数を算出する際に必要な他の各種情報を、通信部101を介して各種サーバやインターネット上のWebサイトから取得する。販促効果を示す係数の算出についての詳細は後述する。
 販促効果推定部110は、算出した販促効果を示す係数を、好適発注量算出部116に出力する。なお、ユーザ入力情報が、予想視聴率である場合について説明したが、これに限られず、予想視聴テレビジョン台数、予想視聴人数等であってもよい。ここでいう予想視聴率、予想視聴台数、予想視聴人数が、特許請求の範囲におけるコンテンツの視聴程度を予想した値の一例である。
The sales promotion effect estimation unit 110 extracts introduction content specifying information having the highest local audience rating from the acquired preferred content audience rating table. The sales promotion effect estimation unit 110 selects the introduction content indicated by the extracted introduction content specifying information as content (hereinafter referred to as sales promotion content) that is a main information source for calculating the preferred order quantity.
The sales promotion effect estimation unit 110 calculates a coefficient indicating the sales promotion effect based on the selected sales promotion content and user input information. The user input information is information used when calculating a coefficient indicating the sales promotion effect, and is an expected audience rating of the sales promotion content predicted by the mass media before the sales promotion content is broadcast.
The sales promotion effect estimation unit 110 acquires user input information from the user input information storage unit 115. Further, the sales promotion effect estimation unit 110 obtains various other information necessary for calculating a coefficient indicating the sales promotion effect from various servers or a website on the Internet via the communication unit 101. Details of the calculation of the coefficient indicating the sales promotion effect will be described later.
The sales promotion effect estimation unit 110 outputs a coefficient indicating the calculated sales promotion effect to the preferred order quantity calculation unit 116. In addition, although the case where the user input information is the expected audience rating has been described, the present invention is not limited to this and may be the expected number of viewing televisions, the expected number of viewers, and the like. The predicted audience rate, the expected number of viewers, and the expected number of viewers here are examples of values for predicting the degree of content viewing in the claims.
 好適発注量算出部116は、算出した販促効果を示す係数に基づいて、好適発注量を算出する。好適発注量算出部116は、算出した販促効果を示す係数を、通常発注量に乗算することで、好適発注量を算出する。ここで、好適発注量算出部116は、商品情報を、通常発注量取得部111から取得し、取得した商品情報から通常発注量を抽出する。
 好適発注量算出部116は、算出した好適発注量を、通信部101を介して、店舗装置3に出力する。また、好適発注量算出部116は、算出した好適発注量と、抽出した通常発注量と、好適コンテンツ視聴率テーブルとを、販促効果情報画像生成部112に出力する。
The preferred order quantity calculation unit 116 calculates the preferred order quantity based on the calculated coefficient indicating the sales promotion effect. The preferred order quantity calculation unit 116 calculates the preferred order quantity by multiplying the normal order quantity by a coefficient indicating the calculated sales promotion effect. Here, the preferred order quantity calculation unit 116 acquires the product information from the normal order quantity acquisition unit 111, and extracts the normal order quantity from the acquired product information.
The preferred order quantity calculation unit 116 outputs the calculated preferred order quantity to the store apparatus 3 via the communication unit 101. The preferred order quantity calculation unit 116 also outputs the calculated preferred order quantity, the extracted normal order quantity, and the preferred content audience rating table to the sales promotion effect information image generation unit 112.
 通常発注量取得部111は、例えば、店舗商品サーバ5から、店舗商品テーブルt51を取得し、取得した店舗商品テーブルt51から商品IDを抽出し、抽出した商品IDをPOSサーバ7に出力することで、POSサーバ7から商品IDが指し示す店舗商品の商品情報を取得する。通常発注量取得部111は、取得した商品情報を、好適発注量算出部116に出力する。 For example, the normal order quantity acquisition unit 111 acquires the store product table t51 from the store product server 5, extracts the product ID from the acquired store product table t51, and outputs the extracted product ID to the POS server 7. The product information of the store product indicated by the product ID is acquired from the POS server 7. The normal order quantity acquisition unit 111 outputs the acquired product information to the preferred order quantity calculation unit 116.
 ユーザ入力情報受付部114は、例えば、ユーザからの操作によって、ユーザ入力情報を受け付ける。ユーザ入力情報受付部114は、受け付けたユーザ入力情報を、ユーザ入力情報記憶部115に記憶させる。
 ユーザ入力情報記憶部115は、例えば、RAMやレジスタ、あるいは、HDDやSSD等の記録媒体である。ユーザ入力情報記憶部115は、ユーザ入力情報を記憶する。
The user input information reception unit 114 receives user input information, for example, by an operation from the user. The user input information reception unit 114 causes the user input information storage unit 115 to store the received user input information.
The user input information storage unit 115 is, for example, a RAM, a register, or a recording medium such as an HDD or an SSD. The user input information storage unit 115 stores user input information.
 販促効果情報画像生成部112は、例えば、好適発注量算出部116から、好適発注量と、通常発注量と、好適コンテンツ視聴率テーブルとを取得する。また、販促効果情報画像生成部112は、紹介コンテンツ特定情報記憶部106から、紹介コンテンツ特定情報テーブルt1051を取得する。
 販促効果情報画像生成部112は、取得した好適発注量と、通常発注量と、好適コンテンツ視聴率テーブルと、紹介コンテンツ特定情報テーブルt1051とに基づいて、販促効果情報画像を生成する。販促効果情報画像生成部112は、生成した販促効果情報画像を、販促効果情報画像記憶部113に記憶させる。
For example, the sales promotion effect information image generation unit 112 acquires a preferred order quantity, a normal order quantity, and a preferred content audience rating table from the preferred order quantity calculation unit 116. In addition, the sales promotion effect information image generation unit 112 acquires the introduction content identification information table t1051 from the introduction content identification information storage unit 106.
The sales promotion effect information image generation unit 112 generates a sales promotion effect information image based on the acquired preferred order quantity, normal order quantity, preferred content audience rating table, and introduction content specifying information table t1051. The sales promotion effect information image generation unit 112 stores the generated sales promotion effect information image in the sales promotion effect information image storage unit 113.
 販促効果情報画像記憶部113は、例えば、HDDやSSD等の記録媒体である。販促効果情報画像記憶部113は、販促効果情報画像を記憶する。なお、店舗装置3は、例えば、販促効果情報画像を表示する際、販促効果情報画像記憶部113から販促効果情報画像を読み込む。 The sales promotion effect information image storage unit 113 is a recording medium such as an HDD or an SSD. The sales promotion effect information image storage unit 113 stores a sales promotion effect information image. The store apparatus 3 reads the sales promotion effect information image from the sales promotion effect information image storage unit 113, for example, when displaying the sales promotion effect information image.
 図13は、第1の実施形態における紹介コンテンツ特定情報取得部105と、視聴率算出部107と、好適コンテンツ選択部108とが、好適コンテンツ視聴率テーブルを生成するまでの動作を説明するシーケンス図の一例である。
 まず、紹介コンテンツ特定情報取得部105は、販促商品の商品キーワードを取得する(ST100)。
 次に、紹介コンテンツ特定情報取得部105は、商品キーワードに基づいて、紹介コンテンツ特定情報テーブルt1051を取得する(ST101)。
 次に、紹介コンテンツ特定情報取得部105は、紹介コンテンツ特定情報テーブルt1051を、視聴率算出部107に出力する(ST102)。
 次に、視聴率算出部107は、取得した紹介コンテンツ特定情報テーブルt1051から紹介コンテンツを一つずつ選択し、選択した紹介コンテンツの全国視聴率及び地域視聴率を算出する(ST103)。視聴率の算出の詳細については後述する。
 次に、視聴率算出部107は、コンテンツ視聴率テーブルt1071を生成する(ST104)。
FIG. 13 is a sequence diagram for explaining operations until the introduction content specifying information acquisition unit 105, the audience rating calculation unit 107, and the preferred content selection unit 108 generate a preferred content audience rating table according to the first embodiment. It is an example.
First, the introductory content specific information acquisition unit 105 acquires a product keyword of a sales promotion product (ST100).
Next, the introduction content specifying information acquisition unit 105 acquires the introduction content specifying information table t1051 based on the product keyword (ST101).
Next, introductory content specific information acquisition section 105 outputs introductory content specific information table t1051 to audience rating calculation section 107 (ST102).
Next, the audience rating calculation unit 107 selects introduction contents one by one from the acquired introduction content specifying information table t1051, and calculates the national audience rating and the regional audience rating of the selected introduction content (ST103). Details of the audience rating calculation will be described later.
Next, audience rating calculation section 107 generates content audience rating table t1071 (ST104).
 次に、視聴率算出部107は、コンテンツ視聴率テーブルt1071を、コンテンツ選択部108に出力する(ST105)。
 次に、好適コンテンツ選択部108は、ST107からST108の処理を、コンテンツ視聴率テーブルt1071のレコード毎に繰り返し実行する(ST106、ST109)。
 好適コンテンツ選択部108は、負印象判定を行う(ST107)。
 好適コンテンツ選択部108は、選択した紹介コンテンツのイベント内容情報が、負内容情報と対応付いているとき(ST107-Yes)、ST108に遷移する。
 好適コンテンツ選択部108は、コンテンツ視聴率テーブルt1071から選択した紹介コンテンツのイベント内容情報が、負内容情報と対応付いていないとき(ST107-No)、次のレコードに対してST107の処理を行う。
 ST107で、自然言語解析を実行した紹介コンテンツのイベント内容情報が、負内容情報と対応付いていたとき、好適コンテンツ選択部108は、テーブル好適化処理を行う(ST108)。
Next, audience rating calculation section 107 outputs content audience rating table t1071 to content selection section 108 (ST105).
Next, the preferred content selection unit 108 repeatedly performs the processing from ST107 to ST108 for each record in the content audience rating table t1071 (ST106, ST109).
The preferred content selection unit 108 performs negative impression determination (ST107).
When the event content information of the selected introduction content is associated with the negative content information (ST107-Yes), the preferred content selection unit 108 transitions to ST108.
When the event content information of the introduction content selected from the content audience rating table t1071 does not correspond to the negative content information (ST107-No), the preferred content selection unit 108 performs the process of ST107 on the next record.
When the event content information of the introduction content for which the natural language analysis has been performed is associated with the negative content information in ST107, the suitable content selection unit 108 performs table optimization processing (ST108).
 図14は、第1の実施形態における視聴率算出部107が、図13のST103で、紹介コンテンツの全国視聴率及び地域視聴率を算出する動作を説明するフローチャートの一例である。
 まず、視聴率算出部107は、紹介コンテンツ特定情報テーブルt1051を取得する(ST200)。
 次に、視聴率算出部107は、紹介コンテンツの視聴ログを取得する(ST201)。
 次に、視聴率算出部107は、紹介コンテンツ特定情報テーブルt1051の紹介コンテンツ毎に、ST203からST206までの処理を繰り返し実行する(ST202、ST207)。
FIG. 14 is an example of a flowchart for explaining the operation of the audience rating calculation unit 107 in the first embodiment calculating the national audience rating and the local audience rating of the introduction content in ST103 of FIG.
First, the audience rating calculation unit 107 acquires the introduction content specifying information table t1051 (ST200).
Next, the audience rating calculation unit 107 acquires a viewing log of the introduction content (ST201).
Next, audience rating calculation section 107 repeatedly executes the processing from ST203 to ST206 for each introduction content in introduction content identification information table t1051 (ST202, ST207).
 視聴率算出部107は、紹介コンテンツが終了しているか否かを判定する(ST203)。
 視聴率算出部107は、紹介コンテンツがすでに終了しているとき(ST203-Yes)、ST204に遷移する。視聴率算出部107は、紹介コンテンツがまだ終了していないとき(ST203-No)、次の紹介コンテンツにST203の処理を行う。
 ST203で、紹介コンテンツが終了していたとき、視聴率算出部107は、紹介コンテンツの放送時間を所定の時間間隔に分割し、分割された時間間隔毎に紹介コンテンツを視聴していたテレビジョン受像機の全国及び地域それぞれの台数をカウントし、分割された時間間隔毎にカウントされた台数を和算して合計を算出する(ST204)。第1の実施形態において、所定の時間間隔は、単位時間当たりの視聴台数を求めるために1分間隔である。
The audience rating calculation unit 107 determines whether or not the introduction content has ended (ST203).
When the introduction content has already ended (ST203-Yes), the audience rating calculation unit 107 transitions to ST204. When the introduction content has not yet ended (ST203-No), the audience rating calculation unit 107 performs the process of ST203 on the next introduction content.
In ST203, when the introduction content has ended, the audience rating calculation unit 107 divides the broadcast time of the introduction content into predetermined time intervals, and the television receiver that has watched the introduction content for each divided time interval. The total number of machines in the whole country and region is counted, and the total is calculated by summing up the number of machines counted for each divided time interval (ST204). In the first embodiment, the predetermined time interval is a one-minute interval in order to obtain the number of viewers per unit time.
 次に、視聴率算出部107は、ST204で合計された台数を、紹介コンテンツの放送時間で除算し、単位時間当たり(第1の実施形態の場合には、1分当たり)の全国及び地域の平均視聴台数を算出する(ST205)。
 次に、視聴率算出部107は、算出した全国及び地域の平均視聴台数をそれぞれ、全国にある視聴ログを収集可能な全テレビジョン受像機の台数、地域にある視聴ログを収集可能な全テレビジョン受像機の台数で除算することで、紹介コンテンツの全国視聴率及び地域視聴率を算出する(ST206)。
Next, the audience rating calculation unit 107 divides the total number in ST204 by the broadcasting time of the introduction content, and the national and regional data per unit time (in the case of the first embodiment, per minute). The average number of viewers is calculated (ST205).
Next, the audience rating calculation unit 107 calculates the average number of viewers in the whole country and region, the number of all television receivers that can collect viewing logs in the whole country, and all televisions that can collect viewing logs in the region. By dividing by the number of John receivers, the national audience rating and regional audience rating of the introduction content are calculated (ST206).
 図15は、第1の実施形態における販促効果推定部110と、好適発注量算出部116とが、好適発注量を算出するまでの動作を説明するシーケンス図の一例である。
 まず、販促効果推定部110は、好適コンテンツ視聴率テーブルを取得する(ST300)。
 次に、販促効果推定部110は、好適コンテンツ視聴率テーブルの視聴率を参照し、最も地域視聴率が高い紹介コンテンツを、販促コンテンツとして選択する(ST301)。なお、第1の実施形態において、販促効果推定部110は、最も地域視聴率が高い紹介コンテンツを販促コンテンツとする場合について説明したが、これに限られず、最も高い全国視聴率の紹介コンテンツを販促コンテンツとしてもよい。
 次に、販促効果推定部110は、販促コンテンツの紹介コンテンツ特定情報を取得する(ST302)。
FIG. 15 is an example of a sequence diagram illustrating operations until the sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 according to the first embodiment calculate the preferred order quantity.
First, the sales promotion effect estimation part 110 acquires a suitable content audience rating table (ST300).
Next, sales promotion effect estimation section 110 refers to the audience rating in the preferred content audience rating table, and selects the introduction content with the highest local audience rating as the promotional content (ST301). In the first embodiment, the sales promotion effect estimation unit 110 has described the case where the introduction content with the highest local audience rating is the sales promotion content. However, the present invention is not limited to this, and the promotion content with the highest national audience rating is promoted. It may be content.
Next, the sales promotion effect estimation part 110 acquires the introduction content specific information of the sales promotion content (ST302).
 次に、販促効果推定部110は、ユーザ入力情報を取得する(ST303)。
 次に、販促効果推定部110は、視聴ログを取得する(ST304)。ここで、販促効果推定部110は、販促コンテンツの視聴ログと、所定の期間の全コンテンツの視聴ログと、販促コンテンツが放送された日における日中の全コンテンツの視聴ログとを取得する。なお、所定の期間とは、例えば、過去一週間である。また、日中とは、例えば、7時~16時の間の時間帯である。
Next, the sales promotion effect estimation part 110 acquires user input information (ST303).
Next, the sales promotion effect estimation part 110 acquires a viewing log (ST304). Here, the sales promotion effect estimation unit 110 acquires a sales promotion content viewing log, a viewing log of all content for a predetermined period, and a viewing log of all daytime content on the day when the sales promotion content is broadcast. The predetermined period is, for example, the past week. The daytime is, for example, a time zone between 7:00 and 16:00.
 次に、販促効果推定部110は、取得した視聴ログに基づいて、販促効果を示す係数を算出する(ST305)。
 次に、販促効果推定部110は、算出した販促効果を示す係数を、好適発注量算出部116に出力する(ST306)。
 次に、好適発注量算出部116は、通常発注量を取得する(ST307)。
 次に、好適発注量算出部116は、取得した通常発注量に、算出した販促効果を示す係数を乗算して好適発注量を算出する(ST308)。
Next, the sales promotion effect estimation unit 110 calculates a coefficient indicating the sales promotion effect based on the acquired viewing log (ST305).
Next, the sales promotion effect estimation unit 110 outputs a coefficient indicating the calculated sales promotion effect to the preferred order quantity calculation unit 116 (ST306).
Next, the preferred order quantity calculation unit 116 acquires the normal order quantity (ST307).
Next, the preferred order quantity calculation unit 116 calculates the preferred order quantity by multiplying the acquired normal order quantity by a coefficient indicating the calculated sales promotion effect (ST308).
 図16は、第1の実施形態における販促効果推定部110が、図15のST305で、販促効果を示す係数を算出する動作を説明するフローチャートの一例である。
 販促効果を示す係数とは、例えば、地域視聴率影響係数、露出時視聴時間影響係数、日中視聴率影響係数、休日視聴率影響係数、POP影響係数、他コンテンツ影響係数等を乗算して得られる係数である。
 地域視聴率影響係数、露出時視聴時間影響係数、日中視聴率影響係数、休日視聴率影響係数、POP影響係数、他コンテンツ影響係数のそれぞれの詳細は、以下で説明する。なお、以下の説明において、視聴率の算出処理は、図14で示した視聴率算出部107の視聴率算出処理と同様なので、詳細な説明を省略する。
FIG. 16 is an example of a flowchart for explaining the operation of the sales promotion effect estimation unit 110 according to the first embodiment calculating the coefficient indicating the sales promotion effect in ST305 of FIG.
The coefficient indicating the sales promotion effect is obtained by multiplying, for example, a regional audience rating influence coefficient, an exposure viewing time influence coefficient, a daytime audience rating influence coefficient, a holiday audience rating influence coefficient, a POP influence coefficient, another content influence coefficient, and the like. Is a coefficient.
Details of the local audience rating influence coefficient, the exposure time duration influence coefficient, the daytime audience rating influence coefficient, the holiday audience rating influence coefficient, the POP influence coefficient, and the other content influence coefficient will be described below. In the following description, the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculation unit 107 shown in FIG.
 まず、販促効果推定部110は、地域視聴率影響係数を算出する。地域視聴率影響係数とは、例えば、ユーザ入力情報である前述した予想視聴率で、販促コンテンツの地域視聴率を除算して得られた値に、所定の重みを乗算して得られる係数である。
 従って、地域視聴率影響係数は、マスメディアが予想した視聴率よりも実際の視聴率が大きければ販促効果も大きいことを表す値である。所定の重みは、例えば、0.8である。所定の重みは、予め決められてもよいし、ユーザが後から設定できるようにしてもよい。地域視聴率影響係数をk1と表すと、k1は以下の式(1)で表される。
First, the sales promotion effect estimation unit 110 calculates a local audience rating influence coefficient. The regional audience rating influence coefficient is, for example, a coefficient obtained by multiplying a value obtained by dividing the local audience rating of the promotional content by the above-mentioned expected audience rating that is user input information and a predetermined weight. .
Therefore, the regional audience rating influence coefficient is a value indicating that the sales promotion effect is larger if the actual audience rating is larger than the audience rating expected by the mass media. The predetermined weight is, for example, 0.8. The predetermined weight may be determined in advance or may be set later by the user. When the regional audience rating influence coefficient is expressed as k1, k1 is expressed by the following equation (1).
 k1=((販促コンテンツの地域視聴率)/(予想視聴率))×(所定の重み)・・・(1) K1 = ((regional audience rating of promotional content) / (expected audience rating)) × (predetermined weight) (1)
 次に、販促効果推定部110は、サイト影響係数を算出する。サイト影響係数とは、例えば、販促コンテンツで紹介された店舗商品に関連するWebサイトから得られる情報の影響度を示す係数である。
 サイト影響係数は、例えば、販促コンテンツが放送された時間から現在までのTwitter(登録商標)に書き込まれたツィートを自然言語解析し、ポジティブなツィート数とネガティブなツィート数をカウントし、ポジティブなツィート数をネガティブなツィート数で除算した値に、所定の重みを乗算して得られる係数である。
 サイト影響係数をk11とすると、k11は以下の式(2)で表される。なお、分子及び分母には、例えば、ツィート数がゼロだった場合に、k11がゼロ、又は計算不能になることを防ぐため、1を加算する。
Next, the sales promotion effect estimation unit 110 calculates a site influence coefficient. A site influence coefficient is a coefficient which shows the influence degree of the information obtained from the web site relevant to the store product introduced by the sales promotion content, for example.
The site influence coefficient is, for example, a natural language analysis of tweets written on Twitter (registered trademark) from the time the promotional content is broadcast to the present, and counts the number of positive tweets and the number of negative tweets. It is a coefficient obtained by multiplying a value obtained by dividing the number by the number of negative tweets and a predetermined weight.
Assuming that the site influence coefficient is k11, k11 is expressed by the following equation (2). Note that 1 is added to the numerator and denominator, for example, to prevent k11 from becoming zero or impossible to calculate when the number of tweets is zero.
 k11=(ポジティブなツィート数+1)/(ネガティブなツィート数+1)・・・(2) K11 = (number of positive tweets + 1) / (number of negative tweets + 1) (2)
 次に、販促効果推定部110は、露出時視聴時間影響係数を算出する。露出時視聴時間影響係数とは、例えば、販促コンテンツで紹介された店舗商品が販促コンテンツ内に登場している時間帯に販促コンテンツを視聴していた人の販促コンテンツに対する総合視聴時間を、販促コンテンツ全体を見ていた人の平均視聴時間で除算し、除算した値に所定の重みを乗算して得られる係数である。露出時視聴時間影響係数をk2とすると、k2は以下の式(3)で表される。 Next, the sales promotion effect estimation unit 110 calculates a viewing time influence coefficient during exposure. The viewing time influence coefficient at the time of exposure is, for example, the total viewing time for the sales promotion content of the person who was watching the sales promotion content during the time when the store product introduced in the sales promotion content appears in the sales promotion content. It is a coefficient obtained by dividing by the average viewing time of the person who was watching the whole and multiplying the divided value by a predetermined weight. Assuming that the exposure time influence coefficient during exposure is k2, k2 is expressed by the following equation (3).
 k2=((商品露出時の総合視聴時間)/(販促コンテンツの平均視聴時間))×(所定の重み)・・・(3) K2 = ((total viewing time when product is exposed) / (average viewing time of promotional content)) × (predetermined weight) (3)
 次に、販促効果推定部110は、現在が休日か否かを判定する(ST403)。現在が休日ではなかったとき(ST403-No)、販促効果推定部110は、ST404に遷移する。現在が休日のとき(ST403-Yes)、販促効果推定部110は、ST405に遷移する。
 ST403で、現在が休日ではなかったとき、販促効果推定部110は、日中視聴率影響係数を算出する(ST404)。日中視聴率影響係数とは、例えば、日中の時間帯に放送されている全コンテンツの平均視聴率を、所定の期間に放送された全コンテンツの平均視聴率で除算し、除算して得られた値に所定の重みを乗算して得られる係数である。
 日中視聴率影響係数をk3とすると、k3は以下の式(4)で表される。
Next, the sales promotion effect estimation part 110 determines whether the present is a holiday (ST403). When the present is not a holiday (ST403-No), sales promotion effect estimating section 110 transitions to ST404. When the current day is a holiday (ST403-Yes), sales promotion effect estimating section 110 transitions to ST405.
In ST403, when the present is not a holiday, sales promotion effect estimating section 110 calculates a daytime audience rating influence coefficient (ST404). The daytime audience rating influence coefficient is obtained, for example, by dividing the average audience rating of all contents broadcast during the daytime by the average audience rating of all contents broadcast during a predetermined period. This is a coefficient obtained by multiplying the obtained value by a predetermined weight.
When the daytime audience rating influence coefficient is k3, k3 is expressed by the following equation (4).
 k3=((日中の全コンテンツの平均視聴率)/(所定の期間に放送された全コンテンツの平均視聴率))×(所定の重み)・・・(4) K3 = ((average audience rating of all contents during the day) / (average audience rating of all contents broadcast during a given period)) × (predetermined weight) (4)
 ST403で、現在が休日だったとき、販促効果推定部110は、休日視聴率影響係数を算出する(ST405)。休日視聴率影響係数とは、例えば、深夜の時間帯に放送されている全コンテンツの平均視聴率と、土曜日の午前中に放送された全コンテンツの平均視聴率とを加算し、加算して得られた値を、所定の期間に放送された全コンテンツの平均視聴率で除算し、除算して得られた値に所定の重みを乗算して得られる係数である。
 休日視聴率影響係数をk4とすると、k4は以下の式(5)で表される。
In ST403, when the present is a holiday, the sales promotion effect estimation unit 110 calculates a holiday audience rating influence coefficient (ST405). The holiday audience rating influence coefficient is obtained, for example, by adding the average audience rating of all contents broadcast in the midnight hours and the average audience rating of all contents broadcast in the morning on Saturday. It is a coefficient obtained by dividing the obtained value by the average audience rating of all contents broadcast during a predetermined period and multiplying the value obtained by the division by a predetermined weight.
When the holiday audience rating influence coefficient is k4, k4 is expressed by the following equation (5).
 k4=(((深夜帯の全コンテンツの平均視聴率)+(土曜午前中の全コンテンツの平均視聴率))/(所定の期間に放送された全コンテンツの平均視聴率))×(所定の重み)・・・(5) k4 = (((average audience rating of all contents in the midnight) + (average audience rating of all contents on Saturday morning)) / (average audience rating of all contents broadcast in a predetermined period)) × (predetermined Weight) (5)
 次に、販促効果推定部110は、POP影響係数を算出する(ST406)。POP影響係数は、POPを利用した際に生じる販促効果を表す係数である。POP影響係数は、例えば、POPを作成するにあたって利用したコンテンツの地域視聴率を、所定の期間に放送された全コンテンツの平均視聴率で除算し、除算して得られた値に所定の重みを乗算して得られる係数である。
 POP影響係数をk5とすると、k5は以下の式(6)で表される。
Next, the sales promotion effect estimation unit 110 calculates a POP influence coefficient (ST406). The POP influence coefficient is a coefficient representing a sales promotion effect that occurs when the POP is used. The POP influence coefficient is obtained by, for example, dividing the local audience rating of the content used in creating the POP by the average audience rating of all the contents broadcast during a predetermined period, and adding a predetermined weight to the value obtained by the division. This is a coefficient obtained by multiplication.
Assuming that the POP influence coefficient is k5, k5 is expressed by the following equation (6).
 k5=((POP作成時に利用したコンテンツの地域視聴率)/(所定の期間に放送された全コンテンツの平均視聴率))×(所定の重み)・・・(6) K5 = ((regional audience rating of the content used when creating the POP) / (average audience rating of all content broadcast during a given period)) × (predetermined weight) (6)
 次に、販促効果推定部110は、他コンテンツ影響係数を算出する(ST407)。他コンテンツ影響係数とは、例えば、販促コンテンツとは別のコンテンツ(以下、他コンテンツという)で紹介されたキーワードや販促コンテンツの放送された時期に対応付けられた所定の係数である。 Next, the sales promotion effect estimation unit 110 calculates another content influence coefficient (ST407). The other content influence coefficient is, for example, a predetermined coefficient associated with a keyword introduced in content different from the sales promotion content (hereinafter referred to as other content) or a time when the sales promotion content is broadcast.
 図17は、第1の実施形態における店舗商品に関連するキーワードに対応付けられた所定の係数の一覧を示すキーワードテーブルの一例である。
 図17に示すように、キーワードテーブルt1101には、例えば、いちごに対して、クリスマスというキーワードと、12月24日前という時期が対応付けられる。
 販促効果推定部110は、コンテンツ情報サーバ9から、自然言語解析によって販促コンテンツで紹介された店舗商品に関連するキーワードを取得する。
FIG. 17 is an example of a keyword table showing a list of predetermined coefficients associated with keywords related to store merchandise in the first embodiment.
As shown in FIG. 17, in the keyword table t1101, for example, a keyword of Christmas is associated with a time of December 24 before strawberry.
The sales promotion effect estimation unit 110 acquires keywords related to the store product introduced in the sales promotion content by the natural language analysis from the content information server 9.
 販促効果推定部110は、取得したキーワード毎に、取得したキーワードを紹介したコンテンツを、コンテンツ情報サーバ9から取得し、取得したコンテンツの視聴ログを、視聴ログサーバ8から取得する。
 販促効果推定部110は、取得した視聴ログに基づいて、取得したコンテンツの全国視聴率又は地域視聴率を算出し、最も高い視聴率のコンテンツで紹介されたキーワードを選択する。
 販促効果推定部110は、選択したキーワードと、現在の時期とに基づいて、キーワードテーブルt1101に示したように、他コンテンツ影響係数を算出する。なお、第1の実施形態において、他コンテンツ影響係数は、選択したキーワードに対応付けられたコンテンツの視聴率に基づいて、式(1)から算出する。
 以下、他コンテンツ影響係数を、k6で表す。
For each acquired keyword, the sales promotion effect estimation unit 110 acquires the content introducing the acquired keyword from the content information server 9 and acquires the viewing log of the acquired content from the viewing log server 8.
The sales promotion effect estimation unit 110 calculates a national audience rating or a regional audience rating of the acquired content based on the acquired viewing log, and selects a keyword introduced in the content with the highest audience rating.
The sales promotion effect estimation unit 110 calculates the other content influence coefficient as shown in the keyword table t1101 based on the selected keyword and the current time. In the first embodiment, the other content influence coefficient is calculated from Expression (1) based on the audience rating of the content associated with the selected keyword.
Hereinafter, the other content influence coefficient is represented by k6.
 次に、販促効果推定部110は、例えば、算出した各種係数を加算することで、販促効果を示す係数を算出する。販促効果を示す係数をkとすると、例えば、現在が平日で、POPを利用する場合のkは、以下の式(7)で表される。
 なお、POPを利用しない場合は、以下の式(7)からPOP影響係数k5を除外する。また、販促効果を示す係数kを算出する際、各係数には、例えば、所定の重みが乗算されてもよい。また、販促効果を示す係数kは、各係数を乗算して算出されてもよい。
Next, the sales promotion effect estimation part 110 calculates the coefficient which shows the sales promotion effect, for example by adding the calculated various coefficients. Assuming that the coefficient indicating the sales promotion effect is k, for example, k when the current day is a weekday and the POP is used is expressed by the following equation (7).
When POP is not used, the POP influence coefficient k5 is excluded from the following equation (7). Further, when calculating the coefficient k indicating the sales promotion effect, each coefficient may be multiplied by a predetermined weight, for example. Further, the coefficient k indicating the sales promotion effect may be calculated by multiplying each coefficient.
 k=k1+k11+k2+k3+k5+k6・・・(7) K = k1 + k11 + k2 + k3 + k5 + k6 (7)
 図18は、第1の実施形態における販促効果情報画像生成部112が、販促効果情報画像“img”を生成する動作を説明するフローチャートの一例である。
 まず、販促効果情報画像生成部112は、好適コンテンツ視聴率テーブルと、好適発注量と、通常発注量とを取得する(ST500)。
 次に、販促効果情報画像生成部112は、好適コンテンツ視聴率テーブルを参照し、最も地域視聴率が高い紹介コンテンツを、販促コンテンツとして選択する(ST501)。
 次に、販促効果情報画像生成部112は、販促コンテンツの紹介コンテンツ特定情報テーブルt1051を取得する(ST502)。
 次に、販促効果情報画像生成部112は、選択した販促コンテンツの視聴ログを取得する(ST503)。
FIG. 18 is an example of a flowchart illustrating an operation in which the sales promotion effect information image generation unit 112 according to the first embodiment generates the sales promotion effect information image “img”.
First, the sales promotion effect information image generation part 112 acquires a suitable content audience rating table, suitable order quantity, and normal order quantity (ST500).
Next, the sales promotion effect information image generation unit 112 refers to the suitable content audience rating table and selects the introduction content having the highest local audience rating as the sales promotion content (ST501).
Next, the sales promotion effect information image generation part 112 acquires the introduction content specific information table t1051 of the sales promotion content (ST502).
Next, the sales promotion effect information image generation part 112 acquires the viewing log of the selected sales promotion content (ST503).
 次に、販促効果情報画像生成部112は、販促コンテンツの紹介コンテンツ特定情報から、販促コンテンツの放送日時、販促コンテンツを含むテレビジョン番組名等(前述した紹介情報)を抽出し、紹介コンテンツ情報画像p1を生成する(ST504)。
 なお、販促効果情報画像生成部112は、予め登録された所定の販促文句を表す文字列を読み込む。販促効果情報画像生成部112は、抽出した販促コンテンツの放送日時、販促コンテンツを含むテレビジョン番組名等と、読み込んだ販促文句を表す文字列とを結合し、紹介コンテンツ情報画像p1に用いるテキスト情報を生成する。
Next, the sales promotion effect information image generation unit 112 extracts the broadcast date and time of the sales promotion content, the television program name including the sales promotion content (the introduction information described above) from the introduction content specifying information of the sales promotion content, and the introduction content information image. p1 is generated (ST504).
In addition, the sales promotion effect information image generation part 112 reads the character string showing the predetermined sales promotion phrase registered beforehand. The sales promotion effect information image generation unit 112 combines the extracted broadcast date and time of the sales promotion content, the name of the television program including the sales promotion content, and the character string representing the read sales promotion phrase, and uses the text information used for the introduction content information image p1. Is generated.
 販促効果情報画像生成部112は、生成したテキスト情報を、所定の形式に従って紹介コンテンツ情報画像p1とする。所定の形式は、例えば、画像の縦幅と横幅、背景色、文字色等のことである。ここでは、所定の形式が、生成する画像毎に予め販促効果予推定サーバ4に設定される場合について説明するが、これに限られず、ユーザが後から自由に設定できるようにしてもよい。
 以下、販促効果情報画像生成部112が各画像を生成する際の所定の形式は、販促効果情報画像生成部112が生成する各画像に対して、画像の縦幅と横幅、背景色、文字色等の所定の形式が、予め販促効果推定サーバ4に設定される場合について説明する。
The sales promotion effect information image generation unit 112 sets the generated text information as the introduction content information image p1 according to a predetermined format. The predetermined format is, for example, the vertical and horizontal widths of the image, the background color, the character color, and the like. Here, a case where the predetermined format is set in advance in the sales promotion effect prediction server 4 for each image to be generated will be described. However, the present invention is not limited to this, and the user may be able to freely set later.
Hereinafter, the predetermined format when the sales promotion effect information image generation unit 112 generates each image is the vertical and horizontal widths of the image, background color, and character color for each image generated by the sales promotion effect information image generation unit 112. A case where a predetermined format such as is set in the sales promotion effect estimation server 4 in advance will be described.
 次に、販促効果情報画像生成部112は、全国視聴率画像p2を生成する(ST505)。販促効果情報画像生成部112は、例えば、好適コンテンツ視聴率テーブルから販促コンテンツの全国視聴率を抽出し、抽出した全国視聴率に基づいて、所定の形式に従って全国視聴率画像p2を生成する。
 次に、販促効果情報画像生成部112は、地域視聴率画像p3を生成する(ST506)。販促効果情報画像生成部112は、例えば、好適コンテンツ視聴率テーブルから販促コンテンツの地域視聴率を抽出し、抽出した地域視聴率に基づいて、所定の形式に従って地域視聴率画像p3を生成する。
Next, the sales promotion effect information image generation part 112 produces | generates the national audience rating image p2 (ST505). For example, the sales promotion effect information image generation unit 112 extracts the national audience rating of the sales promotion content from the suitable content audience rating table, and generates the national audience rating image p2 according to a predetermined format based on the extracted national audience rating.
Next, the sales promotion effect information image generation part 112 produces | generates the regional audience rating image p3 (ST506). For example, the sales promotion effect information image generation unit 112 extracts the local audience rating of the sales promotion content from the suitable content audience rating table, and generates the regional audience rating image p3 according to a predetermined format based on the extracted local audience rating.
 次に、販促効果情報画像生成部112は、サイト情報画像p4を生成する(ST507)。販促効果情報画像生成部112は、例えば、販促コンテンツで紹介された店舗商品に関連するツィート数を、インターネット上から自然言語解析によって抽出し、抽出したツィート数に基づいて、所定の形式に従ってサイト情報画像p4を生成する。
 次に、販促効果情報画像生成部112は、販促コンテンツ内容画像p5を生成する(ST508)。販促効果情報画像生成部112は、例えば、販促コンテンツのイベント内容情報を、紹介コンテンツ特定情報テーブル1051から抽出し、抽出したイベント内容情報に基づいて、所定の形式に従って販促コンテンツ内容画像p5を生成する。
Next, the sales promotion effect information image generation part 112 produces | generates the site information image p4 (ST507). The sales promotion effect information image generation unit 112 extracts, for example, the number of tweets related to the store product introduced in the sales promotion content by natural language analysis from the Internet, and the site information according to a predetermined format based on the extracted number of tweets. An image p4 is generated.
Next, sales promotion effect information image generation section 112 generates sales promotion content content image p5 (ST508). For example, the sales promotion effect information image generation unit 112 extracts the event content information of the sales promotion content from the introduction content specifying information table 1051, and generates the sales promotion content content image p5 according to a predetermined format based on the extracted event content information. .
 次に、販促効果情報画像生成部112は、露出時間グラフp6を生成する(ST509)。販促効果情報画像生成部112は、例えば、紹介コンテンツ特定情報テーブルt1501と、紹介コンテンツの視聴ログとに基づいて、紹介コンテンツの一日あたりの累計放送時間を露出時間として、所定の期間内における露出時間の変動をグラフ化する。
 さらに、販促効果情報画像生成部112は、累計視聴時間を、視聴ログに基づいて算出し、算出した累計視聴時間に基づいて、露出時間の変動と同じ期間内における累計視聴時間の変動を、露出時間の変動を表すグラフの上に重ねることで、露出時間グラフp6を生成する。
Next, the sales promotion effect information image generation part 112 produces | generates the exposure time graph p6 (ST509). The sales promotion effect information image generation unit 112, for example, based on the introductory content specifying information table t1501 and the viewing log of the introductory content, uses the cumulative broadcast time per day of the introductory content as the exposure time, and exposes it within a predetermined period Graph the time variation.
Further, the sales promotion effect information image generation unit 112 calculates the cumulative viewing time based on the viewing log, and based on the calculated cumulative viewing time, the fluctuation of the cumulative viewing time within the same period as the fluctuation of the exposure time is exposed. An exposure time graph p6 is generated by superimposing the graph on the time variation graph.
 次に、販促効果情報画像生成部112は、取得した好適発注量と、通常発注量とに基づいて、所定の形式に従って発注量画像p7を生成する(ST510)。
 次に、販促効果情報画像生成部112は、キャプチャ画像p8を生成する(ST511)。販促効果情報画像生成部112は、例えば、販促コンテンツのコンテンツ動画を、コンテンツ記録サーバ10から取得し、取得したコンテンツ動画をキャプチャすることで、キャプチャ画像p8を生成する。
Next, the sales promotion effect information image generation unit 112 generates an order quantity image p7 according to a predetermined format based on the acquired preferred order quantity and normal order quantity (ST510).
Next, the sales promotion effect information image generation part 112 produces | generates the capture image p8 (ST511). For example, the sales promotion effect information image generation unit 112 acquires a content video of the sales promotion content from the content recording server 10, and generates the capture image p8 by capturing the acquired content video.
 次に、販促効果情報画像生成部112は、地域露出時間画像p9を生成する(ST512)。販促効果情報画像生成部112は、例えば、紹介コンテンツ特定情報テーブルt1051から、販促コンテンツの放送時間を抽出し、抽出した放送時間に基づいて、所定の形式に従って地域露出時間画像p10を生成する。
 次に、販促効果情報画像生成部112は、総合視聴時間画像p11を生成する(ST513)。販促効果情報画像生成部112は、例えば、ST513で抽出した放送時間に、視聴ログから抽出した販促コンテンツを視聴したテレビジョン受像機の台数を乗算した総合視聴時間を算出し、算出した総合視聴時間に基づいて、所定の形式に従って総合視聴時間画像p11を生成する。
Next, the sales promotion effect information image generation part 112 produces | generates the area exposure time image p9 (ST512). For example, the sales promotion effect information image generation unit 112 extracts the broadcast time of the sales promotion content from the introduction content specifying information table t1051, and generates the regional exposure time image p10 according to a predetermined format based on the extracted broadcast time.
Next, the sales promotion effect information image generation part 112 produces | generates the comprehensive viewing-and-listening time image p11 (ST513). For example, the sales promotion effect information image generation unit 112 calculates a total viewing time obtained by multiplying the broadcast time extracted in ST513 by the number of television receivers that have viewed the sales promotion content extracted from the viewing log. Based on, the general viewing time image p11 is generated according to a predetermined format.
 次に、販促効果情報画像生成部112は、紹介コンテンツ内容画像p12を生成する(ST514)。販促効果情報画像生成部112は、例えば、好適コンテンツ視聴率テーブルから、地域視聴率が上位3位に入っている紹介コンテンツを抽出し、抽出したコンテンツに対応するイベント内容情報から、自然言語解析によって、イベントを表す短文のテキスト情報を抽出する。そして、販促効果情報画像生成部112は、抽出したテキスト情報と、対応する紹介コンテンツの地域視聴率とに基づいて、所定の形式に従って紹介コンテンツ内容画像p12を生成する。
 次に、販促効果情報画像生成部112は、ST504~ST515で生成した各種画像を、所定の形式に従って配置することで、販促効果情報画像“img”を生成する(ST515)。
Next, the sales promotion effect information image generation part 112 produces | generates the introduction content content image p12 (ST514). For example, the sales promotion effect information image generation unit 112 extracts the introduction content having the top three places in the local audience rating from the preferred content audience rating table, and performs natural language analysis from the event content information corresponding to the extracted content. , Extract short text information representing the event. And the sales promotion effect information image generation part 112 produces | generates the introduction content content image p12 according to a predetermined format based on the extracted text information and the local audience rating of the corresponding introduction content.
Next, the sales promotion effect information image generation unit 112 generates the sales promotion effect information image “img” by arranging the various images generated in ST504 to ST515 in accordance with a predetermined format (ST515).
 このように、第1の実施形態の販促効果推定システム1は、放送後の店舗商品を紹介したコンテンツの各種情報を取得し、取得した各種情報に基づいて、紹介された店舗商品の販促効果を示す係数を算出することができる。
 また、販促効果推定システム1は、算出した販促効果を示す係数に基づいて、販促コンテンツで紹介された店舗商品にとって好適な発注量を算出することができるため、過剰発注や過少発注を防ぐこともできる。
 さらに、販促効果推定システム1は、販促効果情報画像を生成し、生成した販促効果情報画像を表示する。従って、ユーザは、紹介コンテンツによる販促効果の根拠を、紹介コンテンツが放送された直後に得ることができる。
As described above, the sales promotion effect estimation system 1 according to the first embodiment acquires various pieces of information on the content introducing the post-broadcast store product, and based on the acquired various information, the sales promotion effect of the introduced store product is obtained. The indicated coefficient can be calculated.
Further, since the sales promotion effect estimation system 1 can calculate an order quantity suitable for the store product introduced in the sales promotion content based on the calculated coefficient indicating the sales promotion effect, it is possible to prevent excessive orders and underorders. it can.
Further, the sales promotion effect estimation system 1 generates a sales promotion effect information image and displays the generated sales promotion effect information image. Therefore, the user can obtain the basis of the sales promotion effect by the introduction content immediately after the introduction content is broadcast.
 図19は、一般的な顧客が取ると予想される行動パターンのフローチャートである。このフローチャートは、第1の実施形態の販促効果推定システム1が、好適な発注量を算出することを示すものであり、一般性を持つものと考えられる。
 顧客は、店舗“Shp”内に設置されたテレビジョン番組(販促コンテンツ)の情報を用いた広告を見たとき、ST600からST611の行動を行う。顧客は、広告を見る(ST600)。
 次に、顧客は、見た広告がテレビジョン番組名(販促コンテンツの名称)を用いた広告(ST601-番組名)か、販促コンテンツ内に登場した販促商品を紹介した出演者(以下、紹介人物という)を用いた広告か(ST601-紹介人物)によって、異なる行動を取る。
 ST601で、見た広告がテレビジョン番組名を用いた広告だったとき、顧客の行動は、ST602に遷移する。ST601で、見た広告が紹介人物を用いた広告だったとき、顧客の行動は、ST607に遷移する。
FIG. 19 is a flowchart of an action pattern expected to be taken by a general customer. This flowchart shows that the sales promotion effect estimation system 1 of the first embodiment calculates a suitable order quantity, and is considered to have generality.
When a customer sees an advertisement using information of a television program (promotional content) installed in the store “Shp”, the customer performs the actions from ST600 to ST611. The customer sees the advertisement (ST600).
Next, the customer views the advertisement (ST601-program name) using the television program name (name of the promotional content) or the performer who introduced the promotional product that appeared in the promotional content (hereinafter referred to as the introduction person). Different actions are taken depending on whether the advertisement uses (referred to as ST601-introducing person).
When the viewed advertisement is an advertisement using the television program name in ST601, the customer's behavior transitions to ST602. When the viewed advertisement is an advertisement using an introduction person in ST601, the customer's behavior transitions to ST607.
 次に、顧客の行動は、テレビジョン番組を知っているか否かで異なる行動を取る(ST602)。顧客の行動は、テレビジョン番組を知っているとき(ST602-Yes)、ST603に遷移する。顧客の行動は、テレビジョン番組を知らないとき(ST602-No)、ST606に遷移する。
 ST602で、テレビジョン番組を知っているとき、顧客の行動は、テレビジョン番組を見ていたか否かで異なる行動を取る(ST603)。顧客の行動は、テレビジョン番組を見ていたとき(ST603-Yes)、ST604に遷移する。顧客の行動は、テレビジョン番組を見ていないとき(ST603-No)、ST605に遷移する。
Next, the customer's behavior is different depending on whether or not the television program is known (ST602). When the customer knows the television program (ST602-Yes), the customer transitions to ST603. When the customer does not know the television program (ST602-No), the customer transitions to ST606.
In ST602, when the user knows the television program, the customer's behavior is different depending on whether or not he / she was watching the television program (ST603). When the customer's behavior is watching a television program (ST603-Yes), the transition is made to ST604. When the customer's behavior is not watching the television program (ST603-No), the customer transitions to ST605.
 ST603で、テレビジョン番組を見ていたとき、顧客は、高確率で販促商品を購入する(ST604)。
 ST603で、テレビジョン番組を見ていないとき、顧客は、販促商品を購入する可能性がある(ST605)。
 ST602で、テレビジョン番組を知らないとき、顧客の購入意欲は上がらない(ST606)。
 ST601で、見た広告が紹介人物を用いた広告だったとき、顧客は、紹介人物を知っているか否かで異なる行動を取る(ST607)。紹介人物を知っているとき(ST607-Yes)、顧客の行動は、ST608に遷移する。紹介人物を知らないとき(ST607-No)、顧客の行動は、ST611に遷移する。
When watching a television program in ST603, the customer purchases a promotional product with high probability (ST604).
In ST603, when the user does not watch the television program, the customer may purchase a promotional product (ST605).
When the user does not know the television program in ST602, the customer's willingness to purchase does not increase (ST606).
When the viewed advertisement is an advertisement using an introduction person in ST601, the customer takes different actions depending on whether or not the introduction person is known (ST607). When the introduction person is known (ST607-Yes), the behavior of the customer transitions to ST608. When the introduction person is not known (ST607-No), the behavior of the customer transitions to ST611.
 ST607で、紹介人物を知っているとき、顧客は、テレビジョン番組を見ていたか否かで異なる行動を取る(ST608)。テレビジョン番組を見ていたとき(ST608-Yes)、顧客の行動は、ST609に遷移する。
 テレビジョン番組を見ていなかったとき(ST608-No)、顧客の行動は、ST610に遷移する。ST608で、テレビジョン番組を見ていたとき、顧客は、高確率で販促商品を購入する(ST609)。
 ST608で、テレビジョン番組を見ていなかったとき、顧客は、購入する可能性がある(ST610)。
 ST607で、紹介人物を知らないとき、顧客の購入意欲は上がらない(ST611)。
When the introduction person is known in ST607, the customer takes different actions depending on whether or not the television program is being watched (ST608). When watching a television program (ST608-Yes), the behavior of the customer transitions to ST609.
When the user does not watch the television program (ST608-No), the customer behavior transitions to ST610. When watching a television program in ST608, the customer purchases a promotional product with high probability (ST609).
In ST608, when the user does not watch the television program, the customer may purchase (ST610).
When the introduction person is not known in ST607, the customer's willingness to purchase does not increase (ST611).
 以上のことから、テレビジョン番組で店舗商品が紹介された場合、顧客がそのテレビジョン番組を視聴していれば、より高い確率で紹介された店舗商品を購入すると考えられる。
 従って、視聴率の最も高い紹介コンテンツを販促コンテンツとし、販促コンテンツの視聴率に応じて好適な発注量を算出する第1の実施形態の販促効果推定システム1によって、ユーザはより適切な発注業務を行うことができる。
From the above, when a store product is introduced in a television program, it is considered that if the customer views the television program, the introduced store product is purchased with a higher probability.
Therefore, with the sales promotion effect estimation system 1 according to the first embodiment that uses the introduction content with the highest audience rating as the sales promotion content and calculates a suitable order quantity according to the audience rating of the sales promotion content, the user can carry out a more appropriate ordering operation. It can be carried out.
 図20は、商品のコンテンツへの露出時間と売り上げの関係を表すグラフの一例である。
 具体的には、図20は、日付毎に商品A、あるいは、商品Aが含まれるカテゴリー(例えば、品種等)がコンテンツで紹介された累計時間をヒストグラム化し、その上に、紹介された商品Aの売上高の変化と、カテゴリー全体の売上高の変化とを、折れ線グラフ化して示した図である。
 図20で示したように、商品Aの売上と、商品Aを含むカテゴリー全体の売り上げは、商品Aがコンテンツで紹介される時間(露出時間)の増加とともに上昇する。このような売り上げの上昇は、一般的に現実で起こる傾向にある。
 販促効果推定システム1は、視聴率の最も高い紹介コンテンツを販促コンテンツとし、販促コンテンツの視聴率に応じて好適発注量を算出するので、販促コンテンツによる販促効果をより適切に反映した好適発注量を算出する。そして、ユーザは、算出された好適発注量によって、より適切な発注業務を行うことができる。
FIG. 20 is an example of a graph showing the relationship between the exposure time to the product content and the sales.
Specifically, FIG. 20 shows a histogram of the cumulative time in which the product A or the category (for example, product type) including the product A is introduced in the contents for each date, and the introduced product A It is the figure which showed in a line graph the change of the sales of this, and the change of the sales of the whole category.
As shown in FIG. 20, the sales of the product A and the sales of the entire category including the product A increase as the time (exposure time) for which the product A is introduced in the content increases. Such an increase in sales generally tends to occur in reality.
The sales promotion effect estimation system 1 uses the introductory content with the highest audience rating as the sales promotion content, and calculates the preferred order quantity according to the audience rating of the sales promotion content. Therefore, the sales order effect amount more appropriately reflects the sales promotion effect of the sales promotion content. calculate. Then, the user can perform more appropriate ordering work according to the calculated preferred order quantity.
 なお、上記第1の実施形態において、販促効果推定システム1は、店舗装置3に販促効果情報画像を送信して表示させる場合について説明したが、これに限られない。販促効果推定システム1は、例えば、特定のPC(Personal Computer)に販促効果情報画像を送信して表示させてもよいし、店長や発注担当者の携帯電話端末へ販促効果情報画像をメールで送信してもよいし、所定の店内放送を流してもよい。
 また、第1の実施形態において、販促効果推定システム1には、店舗“Shp”の一店舗のみが含まれる場合を説明したが、これに限られず、複数の店舗が含まれてもよい。その場合、販促効果推定サーバ4は、店舗毎に好適発注量や販促効果情報画像等を生成(第1の実施形態の場合)してもよい。
 また、販促効果推定サーバ4は、すべての店舗に対して生成された好適発注量や販促効果情報画像等を保持し、ユーザが店舗装置3によって欲しい情報を選択するようにてもよい。
 また、販促効果推定サーバ4は、すべての店舗に対して生成された好適発注量や販促効果情報画像等を、各店舗に対応づけられた好適発注量や販促効果情報画像等を自動的に配信するようにしてもよい。
In addition, although the sales promotion effect estimation system 1 demonstrated the case where the sales promotion effect information image was transmitted and displayed on the store apparatus 3 in the said 1st Embodiment, it is not restricted to this. The sales promotion effect estimation system 1 may, for example, send a sales promotion effect information image to a specific PC (Personal Computer) and display it, or send the sales promotion effect information image to a store manager or a person in charge of ordering by e-mail. Alternatively, a predetermined in-store broadcast may be broadcast.
In the first embodiment, the case where the sales promotion effect estimation system 1 includes only one store “Shp” has been described. However, the present invention is not limited to this, and a plurality of stores may be included. In that case, the sales promotion effect estimation server 4 may generate a suitable order quantity, a sales promotion effect information image, and the like for each store (in the case of the first embodiment).
Further, the sales promotion effect estimation server 4 may hold suitable order quantities and sales promotion effect information images generated for all stores, and the user may select information desired by the store device 3.
Further, the sales promotion effect estimation server 4 automatically distributes the preferred order quantity and the sales promotion effect information image generated for all the stores, and the preferred order quantity and the sales promotion effect information image associated with each store. You may make it do.
<第2の実施形態>
 以下、第2の実施形態について説明する。第2の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第2の実施形態における販促効果推定システム1は、例えば、店舗装置3が、販促効果推定装置11として、販促効果推定サーバ4の各種機能部を備える。
<Second Embodiment>
Hereinafter, the second embodiment will be described. About the structure of the sales promotion effect estimation system in 2nd Embodiment, FIG.1 and FIG.10 is used and the same code | symbol is attached | subjected and demonstrated about the same function part.
In the sales promotion effect estimation system 1 in the second embodiment, for example, the store apparatus 3 includes various functional units of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11.
 図21は、第2の実施形態における販促効果推定システム1の利用状況を示す図である。販促効果推定装置11は、算出した好適発注量に基づいて、発注画面“order”を、販促効果推定装置11のディスプレイに表示させる。
 また、販促効果推定装置11は、ユーザからの操作によって、生成した販促効果情報画像を、販促効果推定装置11のディスプレイに表示させる。さらに、販促効果推定装置11は、販促コンテンツの視聴率が所定の閾値を超えた場合、ハンディーターミナル2にアラート画像“alrt”を出力して表示させる。
FIG. 21 is a diagram illustrating a usage situation of the sales promotion effect estimation system 1 according to the second embodiment. The sales promotion effect estimation device 11 displays an order screen “order” on the display of the sales promotion effect estimation device 11 based on the calculated preferred order quantity.
Moreover, the sales promotion effect estimation apparatus 11 displays the produced sales promotion effect information image on the display of the sales promotion effect estimation apparatus 11 by operation from a user. Further, the sales promotion effect estimation device 11 outputs and displays an alert image “alrt” on the handy terminal 2 when the audience rating of the sales promotion content exceeds a predetermined threshold.
 このように、第2の実施形態の販促効果推定システム1は、販促効果推定装置11として、販促効果推定サーバ4の機能部を持った店舗装置3を備えることによって、第1の実施形態と同様の効果を得ることができる。 Thus, the sales promotion effect estimation system 1 of 2nd Embodiment is provided with the shop apparatus 3 with the function part of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11, and is the same as that of 1st Embodiment. The effect of can be obtained.
<第3の実施形態>
 以下、第3の実施形態について説明する。第3の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第3の実施形態の販促効果推定サーバ4の販促効果推定部110と好適発注量算出部116は、販促コンテンツの視聴率が、店舗装置3がアラート画像を生成してハンディーターミナル2に出力するときに用いる所定の閾値を超えた場合のみ、販促効果を示す係数及び好適発注量を算出し、所定の閾値を超えていない場合は、通常発注量を好適発注量として店舗装置3と、販促効果情報画像生成部112に出力する。
<Third Embodiment>
Hereinafter, a third embodiment will be described. About the structure of the sales promotion effect estimation system in 3rd Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 of the sales promotion effect estimation server 4 according to the third embodiment are configured such that when the store apparatus 3 generates an alert image and outputs the alert image to the handy terminal 2 Only when the predetermined threshold value used for the sales is exceeded, the coefficient indicating the sales promotion effect and the preferred order quantity are calculated. When the predetermined threshold value is not exceeded, the normal order quantity is set as the preferred order quantity and the store apparatus 3 and the sales promotion effect information The image is output to the image generation unit 112.
 このように、第3の実施形態における販促効果推定システム1は、ハンディーターミナル2にアラート画像が表示された場合にのみ、アラート画像に表示された店舗商品の発注量に対して好適発注量を算出し、第1の実施形態と同様の効果を得ることができる。 As described above, the sales promotion effect estimation system 1 in the third embodiment calculates the preferred order quantity for the order quantity of the store product displayed in the alert image only when the alert image is displayed on the handy terminal 2. And the effect similar to 1st Embodiment can be acquired.
<第3の実施形態の変形例>
 以下、第3の実施形態の変形例について説明する。第3の実施形態の変形例の販促効果推定システム1は、第3の実施形態の販促効果推定システム1の機能に加えて、以下のような機能を持つ。
 第3の実施形態の変形例の販促効果情報画像生成部112は、販促コンテンツの視聴率が、店舗装置3がアラート画像を生成してハンディーターミナル2に出力するときに用いる所定の閾値を超えた場合のみ、販促効果情報画像を生成する。
<Modification of Third Embodiment>
Hereinafter, modifications of the third embodiment will be described. In addition to the function of the sales promotion effect estimation system 1 of 3rd Embodiment, the sales promotion effect estimation system 1 of the modification of 3rd Embodiment has the following functions.
In the sales promotion effect information image generation unit 112 according to the modification of the third embodiment, the audience rating of the sales promotion content exceeds a predetermined threshold used when the store apparatus 3 generates an alert image and outputs it to the handy terminal 2. Only in the case, the sales promotion effect information image is generated.
 このように、第3の実施形態の変形例における販促効果推定システム1は、ハンディーターミナル2にアラート画像が表示された場合にのみ、販促効果情報画像を生成する。従って、ハンディーターミナル2にアラート画像が表示された店舗商品の販促効果情報画像のみ、店舗装置3で表示することができる。
 従って、第3の実施形態の変形例における販促効果推定システム1は、ハンディーターミナル2にアラート画像を表示させた場合にのみ、第1の実施形態と同様の効果を得ることができる。
As described above, the sales promotion effect estimation system 1 in the modification of the third embodiment generates the sales promotion effect information image only when the alert image is displayed on the handy terminal 2. Therefore, only the sales promotion effect information image of the store product for which the alert image is displayed on the handy terminal 2 can be displayed on the store apparatus 3.
Therefore, the sales promotion effect estimation system 1 in the modification of the third embodiment can obtain the same effect as that of the first embodiment only when an alert image is displayed on the handy terminal 2.
<第4の実施形態>
 以下、第4の実施形態について説明する。第4の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第4の実施形態における販促効果推定システム1の販促効果推定部110及び販促効果情報画像生成部112は、過去の所定の期間(例えば3日間)に放送された販促コンテンツの候補である紹介コンテンツに対して、紹介コンテンツを視聴した消費者の視聴時間、及び紹介コンテンツが放送終了してからの経過時間に基づいて、世間での販促商品に対する消費者からの関心の高さを示す適正点数を算出する。
 販促効果推定部110及び販促効果情報画像生成部112は、算出した適正点数に応じて紹介コンテンツから販促コンテンツを選択する。
<Fourth Embodiment>
Hereinafter, a fourth embodiment will be described. About the structure of the sales promotion effect estimation system in 4th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 of the sales promotion effect estimation system 1 according to the fourth embodiment are configured to introduce content that is a candidate for sales promotion content broadcasted in a past predetermined period (for example, 3 days). On the other hand, based on the viewing time of consumers who watched the introductory content and the elapsed time since the introductory content was broadcast, an appropriate score indicating the level of consumer interest in the promotional product was calculated. To do.
The sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 select the sales promotion content from the introduction content according to the calculated appropriate score.
 図22は、第4の実施形態における適正点数の算出方法を説明するための概念図である。
 販促効果推定部110は、図22を用いて、適正点数を算出する。図22において、イベント内容情報種別は、商品の紹介のされ方を類型化した情報である。
 イベント内容情報種別は、例えば、販促商品が食品である場合、イベント内容情報を自然言語解析して得られた情報が、その食品をそのまま食べると美味しいという情報であれば情報Aとなり、その食品が健康に良いという情報であれば情報Bとなり、その食品を調理したら美味しくなかったという情報であれば情報Cとなる。
FIG. 22 is a conceptual diagram for explaining a method for calculating an appropriate score in the fourth embodiment.
The sales promotion effect estimation unit 110 calculates an appropriate score using FIG. In FIG. 22, the event content information type is information that categorizes how products are introduced.
The event content information type is, for example, information A if the information obtained by natural language analysis of the event content information is delicious if the food is eaten as it is, if the promotional product is food. If it is information that it is good for health, it becomes information B, and if it is information that the food is not delicious, it becomes information C.
 また、放送終了時刻は、各紹介コンテンツの放送終了時刻を表す。また、第1から第4の視聴者による視聴時間は、第1から第4の視聴者それぞれの、各紹介コンテンツを視聴した時間を表す。また、内容別重み付け係数は、各紹介コンテンツのイベント内容情報種別に対して割り当てられた販促効果への影響度を表す指標である。
 販促効果推定部110は、紹介コンテンツのイベント内容情報を自然言語解析し、視聴者の購買意欲との関連性の強弱に基づいて、紹介コンテンツに所定の重み付け係数を、内容別重み付け係数として付与する。具体的には、販促効果推定部110は、例えば、紹介コンテンツ“vvv”の自然言語解析の結果、深夜帯のお笑いコンテンツと判定されると重み付け係数が0.5となる。
The broadcast end time represents the broadcast end time of each introduction content. The viewing time by the first to fourth viewers represents the time of viewing each introduction content of each of the first to fourth viewers. The content-specific weighting coefficient is an index representing the degree of influence on the sales promotion effect assigned to the event content information type of each introduction content.
The sales promotion effect estimation unit 110 performs natural language analysis on the event content information of the introduction content, and assigns a predetermined weighting coefficient to the introduction content as a weighting coefficient for each content based on the strength of the relevance to the viewer's willingness to purchase. . Specifically, for example, if the sales promotion effect estimation unit 110 determines that it is a late night laughing content as a result of the natural language analysis of the introduction content “vvv”, the weighting coefficient is 0.5.
 また、経過時間別重み付け係数は、紹介コンテンツの放送終了時刻からの経過時間による販促効果への影響度を表す指標である。紹介コンテンツに対する世間での話題性は、紹介コンテンツの放送終了時刻から時間が経過するほど低下するので、経過時間別重み付け係数は小さくなる。
 販促効果情報画像生成部112は、例えば、経過時間別重み付け係数を、次式(8)によって算出する。なお、経過時間の単位は「時間」である。
Further, the weighting coefficient by elapsed time is an index representing the degree of influence on the sales promotion effect by the elapsed time from the broadcast end time of the introduction content. Since the topicality of the public with respect to the introduction content decreases as time elapses from the broadcast end time of the introduction content, the weighting coefficient for each elapsed time becomes small.
For example, the sales promotion effect information image generation unit 112 calculates a weighting coefficient for each elapsed time by the following equation (8). The unit of elapsed time is “time”.
 (経過時間別重み付け係数)=1-(経過時間)/70・・・(8) (Weighting coefficient by elapsed time) = 1- (Elapsed time) / 70 (8)
 販促効果推定部110は、紹介コンテンツ毎の視聴者の視聴時間の合計に対して、内容別重み付け係数と、経過時間別重み付け係数とを乗算し、適正点数を算出する。図22では、視聴者は第1から第4の視聴者の4人のみとなっているが、これは一例である。
 適正点数の算出は、例えば、紹介コンテンツ“xxx”に対しては、第1から第4の視聴者の視聴時間の合計が320秒であり、内容別重み付け係数が1であり、経過時間別重み付け係数が0.82であるので、適正点数は、次式(9)で表され、262となる。
The sales promotion effect estimation unit 110 multiplies the total viewing time of the viewer for each introduction content by the weighting coefficient for each content and the weighting coefficient for each elapsed time to calculate an appropriate score. In FIG. 22, there are only four viewers, the first to fourth viewers, but this is an example.
For example, for the introductory content “xxx”, the appropriate score is calculated as follows: the total viewing time of the first to fourth viewers is 320 seconds, the weighting factor by content is 1, and the weighting by elapsed time is Since the coefficient is 0.82, the appropriate score is expressed by the following equation (9) and is 262.
 320×1×0.82≒262・・・(9) 320 × 1 × 0.82 ≒ 262 ... (9)
 販促効果推定部110は、例えば、過去3日間の紹介コンテンツ全てに対して、適正点数を算出し、イベント内容情報種別毎に合計点数を算出する。図22では、情報Aの適正点数の合計は、紹介コンテンツ“xxx”、“vvv”の2つのコンテンツの適正点数の合計なので、298.9ポイントとなる。
 同様に、情報Bの適正点数の合計は160ポイントであり、情報Cの適正点数の合計は36.5ポイントである。販促効果推定部110は、最も高い適正点数の合計となったイベント内容情報種別に対応する紹介コンテンツの中から、販促コンテンツを選択する。
 図22では、情報Aが最も適正点数の合計が高いので、情報Aの紹介コンテンツである“xxx”、“vvv”のいずれかが販促コンテンツとして選択される。販促効果推定部110は、最も高い適正点数の合計となった紹介コンテンツ特定情報種別の紹介コンテンツの中から、適正点数が最も高い紹介コンテンツを、販促コンテンツとして選択する。
 なお、販促効果情報画像生成部112の適正点数に関する処理は、販促効果推定部110と同様であるため、詳細な説明を省略する。
For example, the sales promotion effect estimation unit 110 calculates an appropriate score for all the introduction contents in the past three days, and calculates a total score for each event content information type. In FIG. 22, the total appropriate score of the information A is 298.9 points because it is the total correct score of the two contents of the introduction contents “xxx” and “vvv”.
Similarly, the total appropriate score for information B is 160 points, and the total proper score for information C is 36.5 points. The sales promotion effect estimation unit 110 selects the sales promotion content from the introduction content corresponding to the event content information type that is the sum of the highest appropriate scores.
In FIG. 22, since information A has the highest appropriate score, either “xxx” or “vvv”, which is the introduction content of information A, is selected as the sales promotion content. The sales promotion effect estimation unit 110 selects the introduction content having the highest appropriate score as the sales promotion content from the introduction content of the introduction content specific information type that is the sum of the highest appropriate scores.
Note that the processing related to the appropriate score of the sales promotion effect information image generation unit 112 is the same as that of the sales promotion effect estimation unit 110, and thus detailed description thereof is omitted.
 このように、第4の実施形態の販促効果推定サーバ4は、紹介コンテンツを視聴した消費者(視聴者)の視聴履歴情報の一例である視聴時間に基づいて、適正点数を算出することで販促コンテンツを選択する。
 適正点数は、世間での販促商品に対する消費者からの関心の高さを示すため、販促効果推定部110は、適正点数による選択によって、より好適な販促効果を示す係数を算出することができる。
As described above, the sales promotion effect estimation server 4 of the fourth embodiment calculates the appropriate score based on the viewing time that is an example of the viewing history information of the consumer (viewer) who viewed the introduction content. Select content.
Since the appropriate score indicates the level of consumer interest in the sales promotion product in the world, the sales promotion effect estimating unit 110 can calculate a coefficient indicating a more preferable sales promotion effect by selection based on the appropriate score.
 なお、第4の実施形態における重み付け係数は、内容別重み付け係数と経過時間別重み付け係数のみだったが、これに限られない。例えば、1分を超える放送時間の紹介コンテンツで、視聴者の他のコンテンツへの移動率が所定の割合以下の場合、紹介コンテンツは、目が離せないコンテンツであることを意味するので、購買意欲に高い影響があると考えられる。そのような場合を想定し、第4の実施形態における重み付け係数は、移動率による重み付け係数を含んでもよい。
 また、紹介コンテンツに関するツィート数が、他のコンテンツに関するツィート数に比べて高い場合、購買意欲に高い影響があると考えられる。そのような場合を想定し、第4の実施形態における重み付け係数は、ツィート数の多寡による重み付け係数を含んでもよい。
In addition, although the weighting coefficient in 4th Embodiment was only the weighting coefficient classified by content and the weighting coefficient classified by elapsed time, it is not restricted to this. For example, in the case of introduction content with a broadcast time exceeding 1 minute, if the movement rate of viewers to other content is less than a predetermined rate, it means that the introduction content is content that cannot be missed. It is thought that there is a high impact on Assuming such a case, the weighting coefficient in the fourth embodiment may include a weighting coefficient based on the movement rate.
Further, if the number of tweets related to the introduction content is higher than the number of tweets related to other content, it is considered that there is a great influence on the purchase intention. Assuming such a case, the weighting coefficient in the fourth embodiment may include a weighting coefficient based on the number of tweets.
 また、第4の実施形態における販促効果推定システム1は、算出した適正点数が0より大きい点数だったすべての紹介コンテンツに関して販促効果への影響を示す係数を算出し、算出したすべての販促効果への影響を示す係数を加算、あるいは乗算して得られた値を、最終的な販促効果への影響を示す係数としてもよい。 Further, the sales promotion effect estimation system 1 according to the fourth embodiment calculates a coefficient indicating the influence on the sales promotion effect for all the introduction contents whose calculated appropriate score is a score larger than 0, and to all the calculated sales promotion effects. A value obtained by adding or multiplying a coefficient indicating the influence of the above may be used as a coefficient indicating the influence on the final sales promotion effect.
<第5の実施形態>
 以下、第5の実施形態について説明する。第5の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第5の実施形態における販促効果推定部110は、販促コンテンツの視聴者と、視聴者が共通する度合いが高い他のコンテンツ(以下、相関コンテンツという)のコンテンツ情報に基づいて、他コンテンツ影響係数k6を算出するためのキーワードを抽出する。第5の実施形態において、説明を簡略化するため、販促商品を食品とするが、これに限られず、衣料品や電化製品等であってもよい。
<Fifth Embodiment>
The fifth embodiment will be described below. About the structure of the sales promotion effect estimation system in 5th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 according to the fifth embodiment is based on content information of other content (hereinafter referred to as correlation content) having a high degree of commonality between the viewer of the sales promotion content and the viewer, and the other content influence coefficient k6. The keyword for calculating is extracted. In the fifth embodiment, in order to simplify the description, the sales promotion product is food. However, the present invention is not limited to this, and may be clothing, electrical appliances, or the like.
 図23は、第5の実施形態における相関コンテンツの選択を説明するための概念図である。販促効果推定部110は、図23を用いて、相関コンテンツを選択する。図23は、各コンテンツの視聴の有無を示す視聴パターンと、テレビジョン受像機の数を対応付けた情報を示している。
 図23の2行目は、コンテンツ1~3の視聴状況全てが“視聴”である。そして、図23の最右列は、視聴状況毎の視聴台数を表示している。従って、図23の2行目の最右列の視聴状況毎の視聴台数は、コンテンツ1~3の全てを視聴したテレビジョン受像機の台数を表している。図23の3行目の場合には、最右列の視聴状況毎の視聴台数は、コンテンツ1及びコンテンツ2を両方視聴し、コンテンツ3を視聴していないテレビジョン受像機の台数である。図23の最下行は、コンテンツ毎の、視聴したテレビジョン受像機の総台数を表示している。
FIG. 23 is a conceptual diagram for explaining selection of correlated content in the fifth embodiment. The sales promotion effect estimation unit 110 selects correlated content using FIG. FIG. 23 shows information in which a viewing pattern indicating whether or not each content is viewed is associated with the number of television receivers.
In the second line of FIG. 23, all viewing situations of the contents 1 to 3 are “viewing”. The rightmost column in FIG. 23 displays the number of views for each viewing situation. Therefore, the number of views for each viewing situation in the rightmost column of the second row in FIG. 23 represents the number of television receivers that have viewed all of the contents 1 to 3. In the case of the third row in FIG. 23, the number of views for each viewing situation in the rightmost column is the number of television receivers that have both viewed content 1 and content 2 but have not viewed content 3. The bottom line in FIG. 23 displays the total number of television receivers viewed for each content.
 販促効果推定部110は、例えば、コンテンツ1を過去3日間において販促商品を紹介した最も視聴率の高かったコンテンツとし、コンテンツ2を過去3日間においてコンテンツ1の次に全国視聴率の高かった販促商品を紹介したコンテンツとする。そして、販促効果推定部110は、例えば、コンテンツ3を、過去3日間において販促商品と関連して料理に使用する食品(以下、関連食品という)を紹介したコンテンツとする。関連食品は、例えば、販促商品が“苺”だとすると、苺を使用したロールケーキが紹介された場合、ロールケーキに使用される生クリームや小麦粉である。 For example, the sales promotion effect estimation unit 110 sets the content 1 as the content with the highest audience rating that introduced the promotional product in the past 3 days, and the content 2 as the sales product with the highest national audience rating after the content 1 in the past 3 days. Is the content introduced. Then, for example, the sales promotion effect estimation unit 110 sets the content 3 as content that introduces food (hereinafter referred to as related food) that is used for cooking in association with the sales promotion product in the past three days. For example, if the promotional product is “mochi”, the related food is fresh cream or flour used in the roll cake when the roll cake using mochi is introduced.
 販促効果推定部110は、コンテンツ1及びコンテンツ2を、紹介コンテンツの紹介コンテンツ特定情報を格納している前述の紹介コンテンツ特定情報テーブルt1051と、全国のテレビジョン受像機から収集された前述の視聴ログとに基づいて選択する。コンテンツ3について、販促効果推定部110は、料理のレシピを紹介する所定のWebサイトから、販促商品を使ったレシピを検索し、検索したレシピから自然言語解析によって関連食品を抽出する。
 販促効果推定部110は、抽出した関連食品を紹介したコンテンツ(以下、関連食品紹介コンテンツという)をコンテンツ情報テーブルt91から抽出する。抽出された関連食品紹介コンテンツは、関連食品と対応付けられる。販促効果推定部110は、抽出した関連食品紹介コンテンツの視聴台数を、視聴ログから抽出し、最も視聴台数の多かった関連食品紹介コンテンツを、コンテンツ3とする。
The sales promotion effect estimation unit 110 converts the content 1 and the content 2 into the above-described introduction content identification information table t1051 storing the introduction content identification information of the introduction content and the above-described viewing log collected from television receivers nationwide. And select based on. For the content 3, the sales promotion effect estimation unit 110 searches for a recipe using the sales promotion product from a predetermined Web site that introduces a recipe for cooking, and extracts related foods from the searched recipe by natural language analysis.
The sales promotion effect estimation unit 110 extracts the content introducing the extracted related food (hereinafter referred to as related food introduction content) from the content information table t91. The extracted related food introduction content is associated with the related food. The sales promotion effect estimation unit 110 extracts the viewing number of the extracted related food introduction content from the viewing log, and sets the related food introduction content with the largest viewing number as the content 3.
 販促効果推定部110は、例えば、コンテンツ1を“あまいお”という苺を紹介したコンテンツであり、コンテンツ2が苺のランキングを紹介したコンテンツであり、コンテンツ3が生クリーム(上記の関連食品)を紹介したコンテンツである場合、他コンテンツ影響係数k6を算出するためのキーワードの抽出源となる他コンテンツの候補を、コンテンツ2及びコンテンツ3とする。販促効果推定部110は、コンテンツ2とコンテンツ3とのうち、コンテンツ1とともに視聴していた台数が多い方のコンテンツを、抽出源コンテンツとする。
 具体的には、図23の場合、コンテンツ1の総視聴台数が100台であり、コンテンツ1を視聴してはいないがコンテンツ2を視聴していた台数が20台であり、コンテンツ1を視聴していないがコンテンツ3を視聴していた台数が45台である。
 コンテンツ1とコンテンツ2とのいずれかを視聴していた台数N12は、次式(10)で表される。また、コンテンツ1とコンテンツ3とのいずれかを視聴していた台数N13は、次式(11)で表される。
The sales promotion effect estimation unit 110, for example, is a content that introduces the candy “Amaio” as the content 1, the content 2 is the content that introduces the ranking of the candy, and the content 3 is fresh cream (the above-mentioned related food). In the case of the introduced content, the other content candidates that are the keyword extraction source for calculating the other content influence coefficient k6 are the content 2 and the content 3. The sales promotion effect estimation unit 110 sets the content of the content 2 and the content 3 that has been viewed together with the content 1 as the extraction source content.
Specifically, in the case of FIG. 23, the total number of viewings of content 1 is 100, and the number of viewings of content 2 but not viewing of content 1 is 20; The number of contents 3 that have not been viewed is 45.
The number N12 of viewing either the content 1 or the content 2 is expressed by the following equation (10). Further, the number N13 of viewing either the content 1 or the content 3 is expressed by the following equation (11).
 N12=100+20=120(台)・・・(10) N12 = 100 + 20 = 120 (units) ... (10)
 N13=100+45=145(台)・・・(11) N13 = 100 + 45 = 145 (unit) ... (11)
 この場合、販促効果推定部110は、N13の方がN12よりも多いため、コンテンツ3を抽出源コンテンツとして選択することで、より好適な他コンテンツ影響係数k6を得ることができる。従って、販促効果推定部110は、コンテンツ3を抽出源コンテンツとして選択する。 In this case, since the sales promotion effect estimation unit 110 has more N13 than N12, it can obtain a more suitable other content influence coefficient k6 by selecting the content 3 as the extraction source content. Accordingly, the sales promotion effect estimation unit 110 selects the content 3 as the extraction source content.
 このように、第5の実施形態の販促効果推定サーバ4は、販促コンテンツとの相関が高い抽出源コンテンツを抽出することで、より好適な他コンテンツ影響係数k6を得ることができる。その結果として、より好適な販促効果を示す係数を算出することができる。 Thus, the sales promotion effect estimation server 4 of the fifth embodiment can obtain a more suitable other content influence coefficient k6 by extracting the extraction source content having a high correlation with the sales promotion content. As a result, a coefficient indicating a more preferable sales promotion effect can be calculated.
<第6の実施形態>
 以下、第6の実施形態について説明する。第6の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第6の実施形態における販促効果推定部110は、地域視聴率影響係数k1を算出する際に使用する予想視聴率を、例えば、放送された販促コンテンツが定期的に放送される場合の前回以前の放送の視聴率に基づいて算出する。従って、第6の実施形態における販促効果推定サーバ4は、予想視聴率をユーザ入力情報として受け付けるユーザ入力情報受付部114及びユーザ入力情報記憶部115を省略してよい。
<Sixth Embodiment>
The sixth embodiment will be described below. About the structure of the sales promotion effect estimation system in 6th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 in the sixth embodiment uses the expected audience rating used when calculating the regional audience rating influence coefficient k1, for example, before the previous time when the broadcasted promotional content is regularly broadcast. Calculated based on the audience rating of the broadcast. Therefore, the sales promotion effect estimation server 4 in the sixth embodiment may omit the user input information reception unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.
 販促効果推定部110は、例えば、一週間前に放送された販促コンテンツの平均視聴率を、予想視聴率として算出する。視聴率の算出処理は、図14で示した視聴率算出部107の視聴率算出処理と同様なので、詳細な説明を省略する。 The sales promotion effect estimation unit 110 calculates, for example, the average audience rating of the promotional content broadcast one week ago as the expected audience rating. Since the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculator 107 shown in FIG. 14, detailed description thereof is omitted.
 このように、第6の実施形態の販促効果推定サーバ4は、販促効果推定部110が予想視聴率を算出するので、ユーザの入力を要求することなく第1の実施形態と同様の効果を得ることができる。 As described above, the sales promotion effect estimation server 4 of the sixth embodiment obtains the same effect as that of the first embodiment without requiring user input because the sales promotion effect estimation unit 110 calculates the expected audience rating. be able to.
<第7の実施形態>
 以下、第7の実施形態について説明する。第7の実施形態における販促効果推定システムの構成については、図1及び図10を援用し、同じ機能部に対して同一の符号を付して説明する。
 第7の実施形態における販促効果推定部110は、地域視聴率影響係数k1を算出する際に使用した予想視聴率を、マスメディア等が各種コンテンツの予想視聴率を登録して提供するための予想視聴率提供サーバから取得する。従って、第7の実施形態における販促効果推定サーバ4は、予想視聴率をユーザ入力情報として受け付けるユーザ入力情報受付部114及びユーザ入力情報記憶部115を省略してよい。
<Seventh Embodiment>
The seventh embodiment will be described below. About the structure of the sales promotion effect estimation system in 7th Embodiment, FIG.1 and FIG.10 is used and the same code | symbol is attached | subjected and demonstrated about the same function part.
The sales promotion effect estimation unit 110 according to the seventh embodiment predicts the expected audience rating used when the regional audience rating influence coefficient k1 is calculated by the mass media and the like by registering the expected audience ratings of various contents. Obtained from the audience rating server. Therefore, the sales promotion effect estimation server 4 in the seventh embodiment may omit the user input information receiving unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.
 図24は、第7の実施形態における販促効果推定システム1の利用状況を示す図である。 FIG. 24 is a diagram showing a usage situation of the sales promotion effect estimation system 1 in the seventh embodiment.
 第7の実施形態における販促効果推定システム1は、販促効果推定システム1は、ハンディーターミナル2、店舗装置3、販促効果推定サーバ4、店舗商品サーバ5、店舗商品補足サーバ6、POSサーバ7、視聴ログサーバ8、コンテンツ情報サーバ9、コンテンツ記録サーバ10、及び予想視聴率提供サーバ12を含む。 The sales promotion effect estimation system 1 in the seventh embodiment is the same as the sales promotion effect estimation system 1, the handy terminal 2, the store apparatus 3, the sales promotion effect estimation server 4, the store product server 5, the store product supplement server 6, the POS server 7, viewing A log server 8, a content information server 9, a content recording server 10, and an expected audience rating providing server 12 are included.
 予想視聴率提供サーバ12は、マスメディア等が提供する各種コンテンツに対する予想視聴率を記憶する。予想視聴率提供サーバ12は、NWを介して、販促効果推定サーバ4と通信可能に接続される。
 第7の実施形態における販促効果推定サーバ4の販促効果推定部110は、地域視聴率影響係数k1を算出するため、予想視聴率を予想視聴率提供サーバ12から取得する。
The expected audience rating providing server 12 stores the expected audience ratings for various contents provided by mass media and the like. The expected audience rating providing server 12 is communicably connected to the sales promotion effect estimating server 4 via the NW.
The sales promotion effect estimation unit 110 of the sales promotion effect estimation server 4 in the seventh embodiment acquires the expected audience rating from the expected audience rating providing server 12 in order to calculate the regional audience rating influence coefficient k1.
 このように、第7の実施形態の販促効果推定サーバ4は、ユーザ入力情報受付部114及びユーザ入力情報記憶部115を含まなくても、販促効果推定部110が、予想視聴率を、予想視聴率提供サーバ12から取得するので、第1の実施形態と同様の効果を得ることができる。 Thus, even if the sales promotion effect estimation server 4 of the seventh embodiment does not include the user input information reception unit 114 and the user input information storage unit 115, the sales promotion effect estimation unit 110 calculates the expected viewing rate. Since it acquires from the rate provision server 12, the effect similar to 1st Embodiment can be acquired.
 以上、この発明の各実施形態を、図面を参照して詳述してきたが、具体的な構成はこれらの各実施形態に限られるものではなく、この発明の要旨を逸脱しない限り、変更、置換、削除等されてもよい。 As mentioned above, although each embodiment of this invention has been described in detail with reference to the drawings, the specific configuration is not limited to each of these embodiments, and changes and substitutions are made without departing from the gist of this invention. , May be deleted.
 また、図1、図10、図21における販促効果推定システム1を構成する各部の機能を実現するためのプログラムを、コンピュータ読み取り可能な記録媒体に記録して、この記録媒体に記録されたプログラムをコンピュータシステムに読み込ませ、実行することにより販促効果推定システム1の実施を行ってもよい。なお、ここでいう「コンピュータシステム」とは、OS(Operation System)や周辺機器等のハードウェアを含む。 Moreover, the program for implement | achieving the function of each part which comprises the sales promotion effect estimation system 1 in FIG.1, FIG.10, FIG.21 is recorded on a computer-readable recording medium, The program recorded on this recording medium is recorded. The sales promotion effect estimation system 1 may be implemented by being read and executed by a computer system. The “computer system” here includes an OS (Operation System) and hardware such as peripheral devices.
 また、「コンピュータシステム」は、WWW(World Wide Web)システムを利用している場合であれば、ホームページ提供環境(あるいは表示環境)も含む。
 また、「コンピュータ読み取り可能な記録媒体」とは、フレキシブルディスク、光磁気ディスク、ROM(Read Only Memory)、CD(Compact Disk)-ROM等の可搬媒体、コンピュータシステムに内蔵されるハードディスク等の記憶装置のことをいう。さらに「コンピュータ読み取り可能な記録媒体」とは、インターネット等のネットワークや電話回線等の通信回線を介してプログラムを送信する場合の通信線のように、短時間、動的にプログラムを保持するもの、その場合のサーバやクライアントとなるコンピュータシステム内部の揮発性メモリのように、一定時間プログラムを保持しているものも含む。また上記プログラムは、前述した機能の一部を実現するためのものであっても良く、さらに前述した機能をコンピュータシステムにすでに記録されているプログラムとの組み合わせで実現できるものであっても良い。
Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW (World Wide Web) system is used.
The “computer-readable recording medium” means a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), a CD (Compact Disk) -ROM, or a hard disk built in a computer system. Refers to the device. Furthermore, the “computer-readable recording medium” is a medium that dynamically holds a program for a short time, such as a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line, In this case, it also includes those that hold a program for a certain period of time, such as a volatile memory inside a computer system serving as a server or client. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.
(付記1) 本発明の第1の態様は、放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定し、前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得し、前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する、販促効果推定方法である。 (Additional remark 1) The 1st aspect of this invention is content content information which described the content of the broadcast content, Comprising: The event generation period which shows the period in which the event which is at least one part in a program has generate | occur | produced, and the said The content related information including information related to the product related to the event and content information indicating the content is referenced, the content related to the event occurrence period is identified based on the information related to the product, and the content related to the identified event occurrence period Viewing history information of the content to be obtained, reading correspondence information associating the viewing history information with the estimated value from the storage unit, and based on the obtained viewing history information, the content played by the content related to the event occurrence period It is a sales promotion effect estimation method which calculates the said estimated value which shows the effect which promotes sales.
(付記2) 上記(付記1)に記載の販促効果推定方法であって、店舗毎に、当該店舗で取り扱い可能な店舗商品にする情報を取得し、前記店舗商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定し、前記店舗商品の需要量の算出に用いられる前記推定値を算出する、販促効果推定方法としてもよい。 (Additional remark 2) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: For each store, the information which makes the store product which can be handled in the said store is acquired, and event occurrence period based on the information regarding the said store product It is good also as a sales promotion effect estimation method which specifies the content relevant to, and calculates the said estimated value used for calculation of the demand amount of the said store goods.
(付記3) 上記(付記1)に記載の販促効果推定方法であって、店舗で前記イベント発生期間に関連するコンテンツが利用される場合に奏する効果であって、前記商品の販売を促進させる効果を示す前記推定値を算出する、販促効果推定方法としてもよい。 (Additional remark 3) It is the sales promotion effect estimation method as described in the above (Appendix 1), and is an effect exhibited when content related to the event occurrence period is used in a store, and an effect of promoting the sale of the product. It is good also as a sales promotion effect estimation method which calculates the said estimated value which shows.
(付記4) 上記(付記1)に記載の販促効果推定方法であって、前記対応情報は、店舗で前記イベント発生期間に関連するコンテンツが利用される場合と、店舗で前記イベント発生期間に関連するコンテンツが利用されない場合では、異なり、店舗で前記イベント発生期間に関連するコンテンツが利用される場合の需要量の算出に用いられる前記推定値と、店舗で前記イベント発生期間に関連するコンテンツが利用されない場合の需要量の算出に用いられる前記推定値と、を算出する、販促効果推定方法としてもよい。 (Additional remark 4) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The said correspondence information is related with the case where the content relevant to the said event occurrence period is used in a store, and the said event occurrence period in a store When the content to be used is not used, the estimated value used for calculating the demand amount when the content related to the event occurrence period is used at the store and the content related to the event occurrence period are used at the store It is good also as a sales promotion effect estimation method which calculates the said estimated value used for calculation of the demand amount when not being performed.
(付記5) 上記(付記1)に記載の販促効果推定方法であって、店舗を含む地域における視聴程度を示す地域視聴程度情報を取得し、前記取得した地域視聴程度情報に基づいて、前記店舗へ提供される前記推定値を算出する、販促効果推定方法としてもよい。 (Additional remark 5) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The local viewing degree information which shows the viewing degree in the area including a store is acquired, Based on the acquired local viewing degree information, the said store It is good also as a sales promotion effect estimation method which calculates the said estimated value provided to.
(付記6) 上記(付記1)に記載の販促効果推定方法であって、放送されたコンテンツを再生する再生装置各々の前記視聴履歴情報を取得し、前記視聴履歴情報に基づいてイベント発生期間に関連するコンテンツの視聴時間を算出し、算出した視聴時間に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Appendix 6) The sales promotion effect estimation method according to (Appendix 1), wherein the viewing history information of each playback device that plays back the broadcasted content is acquired, and an event occurrence period is obtained based on the viewing history information. It is good also as a sales promotion effect estimation method which calculates the viewing time of a related content, and calculates the said estimated value based on the calculated viewing time.
(付記7) 上記(付記1)に記載の販促効果推定方法であって、放送されたコンテンツを再生する再生装置各々の前記視聴履歴情報を取得し、前記視聴履歴情報に基づいてイベント発生期間に関連するコンテンツのうち、前記商品に関連する情報が登場した時間帯におけるコンテンツの視聴時間を算出し、算出した視聴時間に基づいて前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary note 7) The sales promotion effect estimation method according to (Appendix 1) above, wherein the viewing history information of each playback device that plays back the broadcasted content is acquired, and an event occurrence period is obtained based on the viewing history information. Among the related contents, a sales promotion effect estimation method may be used in which the viewing time of content in a time zone in which information related to the product appears is calculated, and the estimated value is calculated based on the calculated viewing time.
(付記8) 上記(付記1)に記載の販促効果推定方法であって、店舗において利用される前記イベント発生期間に関連するコンテンツの視聴程度を示す情報に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Additional remark 8) It is the sales promotion effect estimation method as described in the above (Appendix 1), Comprising: The said estimated value is calculated based on the information which shows the viewing-and-listening degree of the content relevant to the said event occurrence period utilized in a store. It is good also as a sales promotion effect estimation method.
(付記9) 上記(付記1)に記載の販促効果推定方法であって、前記推定値を算出するための基準値を取得し、前記取得した視聴履歴情報の値と、前記取得した基準値とに基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Additional remark 9) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The reference value for calculating the said estimated value is acquired, The value of the acquired said viewing history information, The said acquired reference value, It is good also as a sales promotion effect estimation method which calculates the said estimated value based on.
(付記10) 上記(付記9)に記載の販促効果推定方法であって、ユーザからの数値の入力を受け付け、前記受け付けた数値を、前記基準値として取得する、販促効果推定方法としてもよい。 (Additional remark 10) It is good also as a sales promotion effect estimation method as described in the above (Appendix 9), Comprising: The numerical value input from a user is received and the received numerical value is acquired as said reference value.
(付記11) 上記(付記9)に記載の販促効果推定方法であって、前記放送されたコンテンツの視聴程度を予想した値を算出し、算出した前記視聴程度を予想した値を、前記基準値として取得する、販促効果推定方法としてもよい。 (Additional remark 11) It is the sales promotion effect estimation method as described in said (Appendix 9), Comprising: The value which estimated the viewing degree of the said broadcast content is calculated, The value which estimated the said viewing degree calculated is the said reference value It is good also as a sales promotion effect estimation method acquired as follows.
(付記12) 上記(付記11)に記載の販促効果推定方法であって、前記放送されたコンテンツが定期的に放送される場合の前回以前の放送の視聴履歴情報に基づいて、前記基準値を算出する、販促効果推定方法としてもよい。 (Supplementary Note 12) In the sales promotion effect estimation method described in (Appendix 11) above, the reference value is calculated based on viewing history information of the previous broadcast when the broadcasted content is regularly broadcast. It is good also as a sales promotion effect estimation method to calculate.
(付記13) 上記(付記9)に記載の販促効果推定方法であって、前記商品に関連する情報が含まれたコンテンツが放送される以前に予想された予想視聴履歴情報を、前記基準値として外部サーバから取得する、販促効果推定方法としてもよい。 (Supplementary note 13) The sales promotion effect estimation method described in (Appendix 9), wherein the expected viewing history information predicted before the content including the information related to the product is broadcast is used as the reference value. It is good also as a sales promotion effect estimation method acquired from an external server.
(付記14) 上記(付記1)に記載の販促効果推定方法であって、ユーザ操作を反映させてウェブサーバが提供する情報であって、前記商品に関連する情報が含まれたコンテンツに関連する情報に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary Note 14) The sales promotion effect estimation method described in (Appendix 1) above, which is information provided by a web server reflecting a user operation and related to content including information related to the product. It is good also as a sales promotion effect estimation method which calculates the said estimated value based on information.
(付記15) 上記(付記1)に記載の販促効果推定方法であって、時期と推定値を対応付ける対応情報を記憶部から読み出し、前記商品に関する情報が含まれたコンテンツが放送された時期に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary Note 15) The sales promotion effect estimation method described in (Appendix 1) above, wherein correspondence information that associates a time with an estimated value is read from a storage unit, and is based on a time when content including information about the product is broadcast Thus, it may be a sales promotion effect estimation method for calculating the estimated value.
(付記16) 上記(付記1)に記載の販促効果推定方法であって、取得した前記視聴履歴情報が、設定条件を満たすか否かを判定し、前記判定結果に基づいて、前記商品の需要量の調整を促す情報を出力する、販促効果推定方法としてもよい。 (Supplementary Note 16) The sales promotion effect estimation method according to (Appendix 1), wherein the acquired viewing history information determines whether or not a set condition is satisfied, and based on the determination result, the demand for the product It is good also as a sales promotion effect estimation method which outputs the information which prompts adjustment of quantity.
(付記17) 上記(付記1)に記載の販促効果推定方法であって、前記推定値が、設定条件を満たすか否かを判定し、前記判定結果に基づいて、前記商品の需要量の調整を促す情報を出力する、販促効果推定方法としてもよい。 (Additional remark 17) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: It determines whether the said estimated value satisfy | fills setting conditions, and adjusts the demand amount of the said goods based on the said determination result It is good also as a sales promotion effect estimation method which outputs the information which prompts.
(付記18) 上記(付記17)に記載の販促効果推定方法であって、前記判定結果が、前記設定条件を満たすと判定した場合に、前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary note 18) The sales promotion effect estimation method according to (Appendix 17), wherein the estimation value is calculated when it is determined that the determination result satisfies the setting condition. .
(付記19) 上記(付記16)に記載の販促効果推定方法であって、前記需要量の調整を促す情報を出力する商品とは異なる商品であって、前記需要量の調整を促す情報を出力する商品に関連する商品の需要量の調整を促す情報を併せて出力する、販促効果推定方法としてもよい。 (Supplementary note 19) The sales promotion effect estimation method according to (Appendix 16), which is a product different from a product that outputs information that prompts adjustment of the demand amount, and outputs information that prompts adjustment of the demand amount It is good also as a sales promotion effect estimation method which outputs together the information which demands adjustment of the demand amount of the goods relevant to the goods to do.
(付記20) 上記(付記1)に記載の販促効果推定方法であって、前記推定結果に基づいて、前記商品の需要量を算出する、販促効果推定方法としてもよい。 (Additional remark 20) It is a sales promotion effect estimation method as described in the above (Appendix 1), Comprising: It is good also as a sales promotion effect estimation method which calculates the demand amount of the said goods based on the said estimation result.
(付記21) 上記(付記1)に記載の販促効果推定方法であって、前記推定結果に基づく情報と、前記商品に関連する情報が含まれたコンテンツの情報とを含む画像を生成する、販促効果推定方法としてもよい。 (Appendix 21) The sales promotion effect estimation method according to (Appendix 1), wherein the sales promotion effect estimation method generates an image including information based on the estimation result and content information including information related to the product. It is good also as an effect estimation method.
(付記22) 上記(付記20)に記載の販促効果推定方法であって、前記算出された需要量に基づいて、前記商品を発注する、販促効果推定方法としてもよい。 (Supplementary Note 22) The sales promotion effect estimation method described in (Appendix 20), wherein the product is ordered based on the calculated demand amount.
(付記23) 上記(付記1)に記載の販促効果推定方法であって、ユーザからの発注量の入力を受け付け、前記受け付けた発注量で、商品を発注する、販促効果推定方法としてもよい。 (Additional remark 23) It is good also as a sales promotion effect estimation method as described in the above (Appendix 1), Comprising: The order quantity input from a user is received and goods are ordered with the received order quantity.
(付記24) 上記(付記1)に記載の販促効果推定方法であって、前記推定値に応じた順序に基づく情報を出力する、販促効果推定方法としてもよい。 (Additional remark 24) It is good also as a sales promotion effect estimation method as described in the above (Appendix 1) and outputting the information based on the order according to the said estimated value.
(付記25) 上記(付記1)に記載の販促効果推定方法であって、前記推定値に応じて、前記商品の順位付けを行い、順位を示す情報を出力する、販促効果推定方法としてもよい。 (Supplementary Note 25) The sales promotion effect estimation method according to (Appendix 1), wherein the product is ranked according to the estimated value, and information indicating the ranking is output. .
(付記26) 上記(付記1)に記載の販促効果推定方法であって、前記イベント発生期間に関連するコンテンツにおいて前記商品が取り扱われている時間に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary note 26) The sales promotion effect estimation method according to (Appendix 1), wherein the estimation value is calculated based on a time during which the product is handled in the content related to the event occurrence period. An estimation method may be used.
(付記27) 上記(付記1)に記載の販促効果推定方法であって、前記イベント発生期間に関連するコンテンツの放送時点を示す情報に基づいて、前記推定値を算出する、販促効果推定方法としてもよい。 (Supplementary note 27) The sales promotion effect estimation method according to (Appendix 1), wherein the estimation value is calculated based on information indicating the broadcast time of content related to the event occurrence period. Also good.
(付記28) 本発明の第2の態様は、放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定する特定部と、前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得する取得部と、前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する推定部と、を備える販促効果推定装置である。 (Additional remark 28) The 2nd aspect of this invention is the content content information which described the content of the broadcast content, Comprising: The event generation | occurrence | production period which shows the period in which the event which is at least one part in a program has generate | occur | produced, and the said A specific unit that identifies content related to an event occurrence period based on information related to a product by referring to content content information including information related to a product related to an event and content information indicating content, and the specified event occurrence An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content A promotion effect estimation device comprising a.
(付記29) 本発明の第3の態様は、放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定する特定部と、前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得する取得部と、前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する推定部と、前記推定値に基づいて算出された需要量を表示する表示部と、を備える販促効果推定システムである。 (Supplementary Note 29) The third aspect of the present invention is content content information describing the content of broadcast content, and an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, and the event occurrence period A specific unit that identifies content related to an event occurrence period based on information related to a product by referring to content content information including information related to a product related to an event and content information indicating content, and the specified event occurrence An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content A promotion effect estimation system and a display unit for displaying the demand amount calculated based on the estimated value.
(付記30) 本発明の第4の態様は、コンピュータに、放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照させ、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定させ、前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得させ、前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出させ、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出させる、ためのプログラムを記録したコンピュータ読み取り可能な記録媒体である。 (Additional remark 30) The 4th aspect of this invention is the content generation | occurrence | production information which described the content of the content broadcast on the computer, Comprising: The event generation | occurrence | production which shows the period when the event which is at least one part in a program has generate | occur | produced The content occurrence information including the period and information related to the product related to the event and the content information indicating the content are referred to, the content related to the event occurrence period is specified based on the information related to the product, and the specified event occurrence Content related to the event occurrence period is obtained by acquiring viewing history information of content related to the period, reading correspondence information associating the viewing history information with the estimated value from the storage unit, and based on the acquired viewing history information Calculate the estimated value indicating the effect of promoting the sale of the product played by A computer-readable recording medium recording a program for.
 本発明の一態様は、商品に関連する情報が含まれたコンテンツの販促効果を、より適切に推定することができる販促効果推定装置などに適用することができる。 One embodiment of the present invention can be applied to a sales promotion effect estimation device that can more appropriately estimate the sales promotion effect of content including information related to a product.
1・・・販促効果推定システム 2・・・ハンディーターミナル 3・・・店舗装置 4・・・販促効果推定サーバ 5・・・店舗商品サーバ 6・・・店舗商品補足サーバ 7・・・POSサーバ 8・・・視聴ログサーバ 9・・・コンテンツ情報サーバ 10・・・コンテンツ記録サーバ 11・・・販促効果推定装置 12・・・予想視聴率提供サーバ 101・・・通信部 102・・・店舗商品取得部 104・・・商品補足情報取得部 105・・・紹介コンテンツ特定情報取得部 106・・・紹介コンテンツ特定情報記憶部 107・・・視聴率算出部 108・・・好適コンテンツ選択部 110・・・好適発注量算出部 111・・・通常発注量取得部 112・・・販促効果情報画像生成部 113・・・販促効果情報画像記憶部 114・・・ユーザ入力情報受付部 115・・・ユーザ入力情報記憶部 116・・・販促効果推定部 DESCRIPTION OF SYMBOLS 1 ... Sales promotion effect estimation system 2 ... Handy terminal 3 ... Store apparatus 4 ... Sales promotion effect estimation server 5 ... Store product server 6 ... Store product supplement server 7 ... POS server 8 ... viewing log server 9 ... content information server 10 ... content recording server 11 ... promotion effect estimation device 12 ... expected audience rating providing server 101 ... communication unit 102 ... store product acquisition Section 104: Product supplement information acquisition section 105 ... Introduction content specific information acquisition section 106 ... Introduction content specific information storage section 107 ... Audience rating calculation section 108 ... Suitable content selection section 110 ... Preferred order quantity calculation unit 111 ... Normal order quantity acquisition unit 112 ... Sales promotion effect information image generation unit 113 ... Sales promotion effect Broadcast image storage unit 114 ... user input information reception unit 115 ... user input information storage unit 116 ... promotional effect estimator

Claims (30)

  1.  放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定し、
     前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得し、
     前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する、
     販促効果推定方法。
    Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content Information and content content information that includes information, identify content related to the event occurrence period based on information about the product,
    Obtaining viewing history information of content related to the identified event occurrence period;
    Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information To calculate,
    Promotional effect estimation method.
  2.  請求項1に記載の販促効果推定方法であって、
     店舗毎に、当該店舗で取り扱い可能な店舗商品にする情報を取得し、前記店舗商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定し、
     前記店舗商品の需要量の算出に用いられる前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    For each store, obtain information on the store product that can be handled in the store, identify content related to the event occurrence period based on the information about the store product,
    Calculating the estimated value used to calculate the demand for the store product;
    Promotional effect estimation method.
  3.  請求項1に記載の販促効果推定方法であって、
     店舗で前記イベント発生期間に関連するコンテンツが利用される場合に奏する効果であって、前記商品の販売を促進させる効果を示す前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Calculating the estimated value indicating the effect of promoting the sale of the product, which is an effect exhibited when content related to the event occurrence period is used in a store;
    Promotional effect estimation method.
  4.  請求項1に記載の販促効果推定方法であって、
     前記対応情報は、店舗で前記イベント発生期間に関連するコンテンツが利用される場合と、店舗で前記イベント発生期間に関連するコンテンツが利用されない場合では、異なり、
     店舗で前記イベント発生期間に関連するコンテンツが利用される場合の需要量の算出に用いられる前記推定値と、店舗で前記イベント発生期間に関連するコンテンツが利用されない場合の需要量の算出に用いられる前記推定値と、を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    The correspondence information is different when content related to the event occurrence period is used at a store and when content related to the event occurrence period is not used at a store,
    Used to calculate the demand when the content related to the event occurrence period is used in the store, and to calculate the demand when the content related to the event occurrence period is not used in the store Calculating the estimated value;
    Promotional effect estimation method.
  5.  請求項1に記載の販促効果推定方法であって、
     店舗を含む地域における視聴程度を示す地域視聴程度情報を取得し、
     前記取得した地域視聴程度情報に基づいて、前記店舗へ提供される前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Get local viewing level information showing the level of viewing in the area including the store,
    Based on the acquired regional viewing degree information, the estimated value provided to the store is calculated.
    Promotional effect estimation method.
  6.  請求項1に記載の販促効果推定方法であって、
     放送されたコンテンツを再生する再生装置各々の前記視聴履歴情報を取得し、
     前記視聴履歴情報に基づいてイベント発生期間に関連するコンテンツの視聴時間を算出し、算出した視聴時間に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Obtaining the viewing history information of each playback device that plays the broadcast content;
    Calculating the viewing time of content related to the event occurrence period based on the viewing history information, and calculating the estimated value based on the calculated viewing time;
    Promotional effect estimation method.
  7.  請求項1に記載の販促効果推定方法であって、
     放送されたコンテンツを再生する再生装置各々の前記視聴履歴情報を取得し、
     前記視聴履歴情報に基づいてイベント発生期間に関連するコンテンツのうち、前記商品に関連する情報が登場した時間帯におけるコンテンツの視聴時間を算出し、算出した視聴時間に基づいて前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Obtaining the viewing history information of each playback device that plays the broadcast content;
    Of the content related to the event occurrence period based on the viewing history information, the viewing time of the content in the time zone in which the information related to the product appears is calculated, and the estimated value is calculated based on the calculated viewing time ,
    Promotional effect estimation method.
  8.  請求項1に記載の販促効果推定方法であって、
     店舗において利用される前記イベント発生期間に関連するコンテンツの視聴程度を示す情報に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Calculating the estimated value based on information indicating the degree of viewing of content related to the event occurrence period used in the store;
    Promotional effect estimation method.
  9.  請求項1に記載の販促効果推定方法であって、
     前記推定値を算出するための基準値を取得し、
     前記取得した視聴履歴情報の値と、前記取得した基準値とに基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Obtaining a reference value for calculating the estimated value;
    Calculating the estimated value based on the acquired viewing history information value and the acquired reference value;
    Promotional effect estimation method.
  10.  請求項9に記載の販促効果推定方法であって、
     ユーザからの数値の入力を受け付け、前記受け付けた数値を、前記基準値として取得する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 9,
    Receiving an input of a numerical value from a user, and acquiring the received numerical value as the reference value;
    Promotional effect estimation method.
  11.  請求項9に記載の販促効果推定方法であって、
     前記放送されたコンテンツの視聴程度を予想した値を算出し、
     算出した前記視聴程度を予想した値を、前記基準値として取得する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 9,
    Calculate a value that predicts the viewing level of the broadcasted content,
    Obtaining a value that predicts the calculated degree of viewing as the reference value;
    Promotional effect estimation method.
  12.  請求項11に記載の販促効果推定方法であって、
     前記放送されたコンテンツが定期的に放送される場合の前回以前の放送の視聴履歴情報に基づいて、前記基準値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 11,
    Based on the viewing history information of the previous broadcast when the broadcast content is regularly broadcast, the reference value is calculated.
    Promotional effect estimation method.
  13.  請求項9に記載の販促効果推定方法であって、
     前記商品に関連する情報が含まれたコンテンツが放送される以前に予想された予想視聴履歴情報を、前記基準値として外部サーバから取得する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 9,
    Obtaining the expected viewing history information predicted before the content including information related to the product is broadcast from the external server as the reference value,
    Promotional effect estimation method.
  14.  請求項1に記載の販促効果推定方法であって、
     ユーザ操作を反映させてウェブサーバが提供する情報であって、前記商品に関連する情報が含まれたコンテンツに関連する情報に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Calculating the estimated value based on information provided by a web server reflecting a user operation and related to content including information related to the product;
    Promotional effect estimation method.
  15.  請求項1に記載の販促効果推定方法であって、
     時期と推定値を対応付ける対応情報を記憶部から読み出し、前記商品に関する情報が含まれたコンテンツが放送された時期に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Correspondence information that associates the estimated value with the time is read from the storage unit, and the estimated value is calculated based on the time when the content including the information related to the product is broadcast.
    Promotional effect estimation method.
  16.  請求項1に記載の販促効果推定方法であって、
     取得した前記視聴履歴情報が、設定条件を満たすか否かを判定し、
     前記判定結果に基づいて、前記商品の需要量の調整を促す情報を出力する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    It is determined whether the acquired viewing history information satisfies a setting condition,
    Based on the determination result, information that prompts adjustment of the demand amount of the product is output.
    Promotional effect estimation method.
  17.  請求項1に記載の販促効果推定方法であって、
     前記推定値が、設定条件を満たすか否かを判定し、
     前記判定結果に基づいて、前記商品の需要量の調整を促す情報を出力する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Determining whether the estimated value satisfies a setting condition;
    Based on the determination result, information that prompts adjustment of the demand amount of the product is output.
    Promotional effect estimation method.
  18.  請求項17に記載の販促効果推定方法であって、
     前記判定結果が、前記設定条件を満たすと判定した場合に、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 17,
    When it is determined that the determination result satisfies the setting condition, the estimated value is calculated.
    Promotional effect estimation method.
  19.  請求項16に記載の販促効果推定方法であって、
     前記需要量の調整を促す情報を出力する商品とは異なる商品であって、前記需要量の調整を促す情報を出力する商品に関連する商品の需要量の調整を促す情報を併せて出力する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 16,
    The product that is different from the product that outputs the information that prompts the adjustment of the demand amount and that outputs information that prompts the adjustment of the demand amount of the product related to the product that outputs the information that prompts the adjustment of the demand amount.
    Promotional effect estimation method.
  20.  請求項1に記載の販促効果推定方法であって、
     前記推定結果に基づいて、前記商品の需要量を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Based on the estimation result, a demand amount of the product is calculated.
    Promotional effect estimation method.
  21.  請求項1に記載の販促効果推定方法であって、
     前記推定結果に基づく情報と、前記商品に関連する情報が含まれたコンテンツの情報とを含む画像を生成する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Generating an image including information based on the estimation result and content information including information related to the product;
    Promotional effect estimation method.
  22.  請求項20に記載の販促効果推定方法であって、
     前記算出された需要量に基づいて、前記商品を発注する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 20,
    Order the product based on the calculated demand.
    Promotional effect estimation method.
  23.  請求項1に記載の販促効果推定方法であって、
     ユーザからの発注量の入力を受け付け、
     前記受け付けた発注量で、商品を発注する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Accepts order quantity input from users,
    Order products with the accepted order quantity,
    Promotional effect estimation method.
  24.  請求項1に記載の販促効果推定方法であって、
     前記推定値に応じた順序に基づく情報を出力する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Outputting information based on the order according to the estimated value;
    Promotional effect estimation method.
  25.  請求項1に記載の販促効果推定方法であって、
     前記推定値に応じて、前記商品の順位付けを行い、順位を示す情報を出力する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    In accordance with the estimated value, the products are ranked, and information indicating the ranking is output.
    Promotional effect estimation method.
  26.  請求項1に記載の販促効果推定方法であって、
     前記イベント発生期間に関連するコンテンツにおいて前記商品が取り扱われている時間に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Calculating the estimated value based on the time the product is handled in the content related to the event occurrence period;
    Promotional effect estimation method.
  27.  請求項1に記載の販促効果推定方法であって、
     前記イベント発生期間に関連するコンテンツの放送時点を示す情報に基づいて、前記推定値を算出する、
     販促効果推定方法。
    The sales promotion effect estimation method according to claim 1,
    Calculating the estimated value based on information indicating the broadcast time of the content related to the event occurrence period;
    Promotional effect estimation method.
  28.  放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定する特定部と、
     前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得する取得部と、
     前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する推定部と、
     を備える販促効果推定装置。
    Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content A specific unit that identifies content related to the event occurrence period based on information about the product, referring to content content information including information,
    An acquisition unit for acquiring viewing history information of content related to the specified event occurrence period;
    Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information An estimator for calculating
    A sales promotion effect estimation device.
  29.  放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照し、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定する特定部と、
     前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得する取得部と、
     前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出し、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出する推定部と、
     前記推定値に基づいて算出された需要量を表示する表示部と、
     を備える販促効果推定システム。
    Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content A specific unit that identifies content related to the event occurrence period based on information about the product, referring to content content information including information,
    An acquisition unit for acquiring viewing history information of content related to the specified event occurrence period;
    Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information An estimator for calculating
    A display unit for displaying the demand amount calculated based on the estimated value;
    Promotional effect estimation system with
  30.  コンピュータに、
     放送されたコンテンツの内容を記述したコンテンツ内容情報であって、番組内の少なくとも一部分であるイベントが発生している期間を示すイベント発生期間と当該イベントに関連する商品に関する情報と、コンテンツを示すコンテンツ情報と、を含むコンテンツ内容情報を参照させ、商品に関する情報に基づいてイベント発生期間に関連するコンテンツを特定させ、
     前記特定したイベント発生期間に関連するコンテンツの視聴履歴情報を取得させ、
     前記視聴履歴情報と推定値を対応付ける対応情報を記憶部から読み出させ、前記取得した視聴履歴情報に基づいて、前記イベント発生期間に関連するコンテンツの奏する前記商品の販売を促進させる効果を示す前記推定値を算出させる、
     ためのプログラムを記録したコンピュータ読み取り可能な記録媒体。
    On the computer,
    Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content Information, and content content information including information is used to identify content related to the event occurrence period based on information about the product,
    Obtaining viewing history information of content related to the specified event occurrence period;
    Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the effect of promoting the sale of the product played by the content related to the event occurrence period is based on the acquired viewing history information Let the estimate be calculated,
    A computer-readable recording medium on which a program for recording is recorded.
PCT/JP2014/066974 2013-06-28 2014-06-26 Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium WO2014208662A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2013137312A JP5485454B1 (en) 2013-06-28 2013-06-28 Sales promotion effect estimation device, order management device, sales promotion effect estimation method, sales promotion effect estimation program and system
JP2013-137312 2013-06-28

Publications (1)

Publication Number Publication Date
WO2014208662A1 true WO2014208662A1 (en) 2014-12-31

Family

ID=50792152

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2014/066974 WO2014208662A1 (en) 2013-06-28 2014-06-26 Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium

Country Status (2)

Country Link
JP (1) JP5485454B1 (en)
WO (1) WO2014208662A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021149678A (en) * 2020-03-19 2021-09-27 ヤフー株式会社 Information processing apparatus, information processing method, and program

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7023392B2 (en) * 2020-06-28 2022-02-21 ラクスル株式会社 Devices, methods and programs for visualizing the effects of TV commercials
CN116547685A (en) * 2020-11-18 2023-08-04 索尼集团公司 Information processing device, information processing method, and program
JP7265082B2 (en) * 2021-03-12 2023-04-25 株式会社電通 ADVERTISING EFFECT MEASURING SYSTEM, ADVERTISING EFFECT MEASURING DEVICE, AD EFFECT MEASURING METHOD AND PROGRAM

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003006511A (en) * 2001-06-20 2003-01-10 Toshiba Tec Corp Merchandise information providing system
JP2004127017A (en) * 2002-10-03 2004-04-22 Ntt Data Corp Sales management device and method
JP2004334388A (en) * 2003-05-02 2004-11-25 Fujitsu Ltd Sales prediction method
JP2007148627A (en) * 2005-11-25 2007-06-14 Toshiba Tec Corp Sales prediction server and sales prediction program

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003006511A (en) * 2001-06-20 2003-01-10 Toshiba Tec Corp Merchandise information providing system
JP2004127017A (en) * 2002-10-03 2004-04-22 Ntt Data Corp Sales management device and method
JP2004334388A (en) * 2003-05-02 2004-11-25 Fujitsu Ltd Sales prediction method
JP2007148627A (en) * 2005-11-25 2007-06-14 Toshiba Tec Corp Sales prediction server and sales prediction program

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021149678A (en) * 2020-03-19 2021-09-27 ヤフー株式会社 Information processing apparatus, information processing method, and program
JP7211998B2 (en) 2020-03-19 2023-01-24 ヤフー株式会社 Information processing device, information processing method, and program

Also Published As

Publication number Publication date
JP2015011577A (en) 2015-01-19
JP5485454B1 (en) 2014-05-07

Similar Documents

Publication Publication Date Title
US8745648B2 (en) Methods and apparatus to monitor advertisement exposure
JP4910000B2 (en) Listing advertisement sending device and method
JP6494475B2 (en) Advertisement distribution apparatus and advertisement distribution method
US20120253920A1 (en) System and method for viewership validation based on cross-device contextual inputs
WO2014208662A1 (en) Sales promotion effect estimation method, sales promotion effect estimation device, sales promotion effect estimation system, and recording medium
US20120331514A1 (en) Method and apparatus for providing image-associated information
JP6290535B2 (en) Video information analysis system
JP5751730B2 (en) Sales promotion effect estimation device, display device, sales promotion effect estimation method, sales promotion effect estimation program, and system
JP5480427B1 (en) Content creation apparatus, content creation method, content creation program, and content providing system
JP5243136B2 (en) Information processing apparatus, information processing system, information processing method, and program
JP2019092067A (en) Information processing apparatus, information processing method, information processing system, and program
JP5243137B2 (en) Information processing apparatus, information processing system, information processing method, and program
KR20140010679A (en) System and method for recommendation
KR20120032290A (en) Providing personalized poi information using client information and client terminal implementing the same
JP2008092526A (en) Digital broadcast reproducing device, viewing history collection system, and viewing history collection method
JP2010092372A (en) Device and method for analyzing advertisement, device and method for generating advertisement information, and programs for advertisement analysis and advertisement information generation
CN102812722A (en) Information processing program, device, and method
JP2011048738A (en) Recommend device, recommend method, and recommend program
JP5600501B2 (en) RECOMMENDATION DEVICE, RECOMMENDATION METHOD, AND PROGRAM
JP2019200572A (en) Notification method, notification program and notification device
JP2003259329A (en) Auction program provider apparatus, sponsor deciding method, and sponsor deciding program
JP7251104B2 (en) ADVERTISING MANAGEMENT DEVICE, PROGRAM, ADVERTISING DISTRIBUTION SYSTEM AND ADVERTISING MANAGEMENT METHOD
JP2011048845A (en) Recommend device, recommend method, and recommend program
JP2015507784A (en) Advertisement providing apparatus and method for providing advertisement
JP5637954B2 (en) RECOMMENDED PROGRAM PRESENTATION DEVICE AND ITS PROGRAM

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14818462

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 14818462

Country of ref document: EP

Kind code of ref document: A1