JP5485454B1 - Sales promotion effect estimation device, order management device, sales promotion effect estimation method, sales promotion effect estimation program and system - Google Patents

Abstract

To provide a sales promotion effect estimation device capable of more appropriately estimating the sales promotion effect of content including information related to a product.
A first acquisition unit that acquires viewing history information of content that is broadcasted content that includes information related to a product, and that is related to the product based on the acquired viewing history information. A sales promotion effect estimation device comprising: an estimation unit that calculates an estimated value indicating an effect of promoting sales of the product from content including information to be performed.
[Selection] Figure 1

Description

The present invention relates to a sales promotion effect estimation device, an order management device, a sales promotion effect estimation method , a sales promotion effect estimation program, and a system .

  In recent years, the influence on the consumption trend by television programs provided by mass media has become remarkably large. 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.

  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.

JP 2003-316872 A

  However, in the product automatic order processing system described in Patent Document 1, since the program data of the television program before broadcasting is used, the details of the contents of the television program are not known, and a suitable order quantity is calculated. The necessary sales promotion effect cannot be accurately predicted. In addition, when the television program is a live broadcast or when 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 automatic product ordering system, The effect may be overestimated or underestimated.

  Therefore, the present invention has been made in view of the above-described problems of the prior art, and provides a sales promotion effect estimation device that can more appropriately estimate the sales promotion effect of content including information related to products. Is one of the purposes.

  One aspect of the present invention is the first acquisition unit that acquires the viewing history information of the content that is broadcast content and includes information related to the product, and based on the acquired viewing history information, A sales promotion effect estimation device comprising: an estimation unit that calculates an estimated value indicating an effect of promoting sales of the product from content including information related to the product.

  ADVANTAGE OF THE INVENTION According to this invention, the sales promotion effect estimation apparatus which can estimate the sales promotion effect of the content containing the information relevant to goods more appropriately can be provided.

It is a figure which shows the utilization condition of the sales promotion effect estimation system in 1st Embodiment. It is a figure which shows an example of the sales promotion effect information image in 1st Embodiment. It is a figure which shows an example of the ordering screen in 1st Embodiment. It is a figure which shows an example of the alert image in 1st Embodiment. It is a figure which shows an example of the report image in 1st Embodiment. It is an example of the figure by which the alert screen alrt was displayed on the handy terminal in 1st Embodiment. It is a figure which shows an example of the store goods table in 1st Embodiment. It is a figure which shows an example of the supplementary information table in 1st Embodiment. It is a figure which shows an example of the content information table in 1st Embodiment. It is a schematic block diagram which shows an example of a structure of the sales promotion effect estimation server in 1st Embodiment. It is a figure which shows an example of the introduction content specific information table in 1st Embodiment. It is a figure which shows an example of the content audience rating table in 1st Embodiment. It is an example of the sequence diagram explaining operation | movement until it produces | generates the suitable content audience rating table in 1st Embodiment. 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. It is a figure which shows an example of the sequence diagram explaining operation | movement until calculating the suitable order quantity in 1st Embodiment. 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. 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. 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. It is a figure which shows an example of the flowchart of the action pattern anticipated that a general customer takes. It is an example of the graph showing the exposure time to the content of goods, and sales. It is a figure which shows the utilization condition of the sales promotion effect estimation system in 2nd Embodiment. It is a conceptual diagram for demonstrating the calculation method of the appropriate score in 4th Embodiment. It is a conceptual diagram for demonstrating selection of the correlation content in 5th Embodiment. It is a figure which shows the utilization condition of the sales promotion effect estimation system in 7th Embodiment.

<First Embodiment>
The first embodiment will be described below with reference to the drawings.
FIG. 1 is a diagram showing a usage situation of the sales promotion effect estimation system. 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.

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). In addition, 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 to this, and may be an intranet, a dedicated line, 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. And can communicate with each other.

  The sales promotion effect estimation server 4 includes, for example, information related to products that can be handled by the store Shp, or products 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). Accompanying information (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, but is divided when a television program broadcast by a television broadcasting station is divided by time, a corner in a television program, or a plurality of It may be content in a time zone that spans television programs, or it may be divided into parts when a radio program broadcast by a radio station is divided by time, a corner in a radio program, or multiple radio programs It may also be content that spans time zones. In the following description, it is assumed that the content is a television program itself. 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, it is assumed that the content including information related to the store product is content that introduces the store product. 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.

  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.

  FIG. 2 is a diagram illustrating an example of the sales promotion effect information image. As shown in FIG. 2, the sales promotion effect information image img is comprised by the image p1-image p11, for example. 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), or a combination of these, giving priority to either the national audience or the regional audience rating. It may be a thing. 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.

  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.

  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 multiplies the total viewing time obtained by multiplying the introduction content broadcast in the area including the store Shp by the total time the store product appears and the number of television receivers viewing the introduction content. A total viewing time image for displaying 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.

  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 not introduced in the introduction content, the store apparatus 3 displays the order screen generated based on the acquired normal order quantity as a default screen on the display of the own apparatus. . In the present embodiment, the store apparatus 3 acquires the information related to the store product and the normal order quantity from the POS server 7. However, the present invention is not limited to this, and the user uses the keyboard to store the information related to the store product and the normal order quantity. It may be input by, for example.

  FIG. 3 is a diagram illustrating an example of an ordering screen. The store apparatus 3 generates an ordering screen order in which the acquired preferred order quantity is displayed in the order quantity size, generates an attention image ntc based on the acquired introduction information, and generates the generated attention image ntc. Arrange as shown in FIG. The details button btn is arranged in the alert image ntc. When the user selects and determines the details 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. Then, the acquired sales promotion effect information image img is displayed on the display of its own device. 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 present embodiment, the store apparatus 3 places an order when the user selects and determines an order button on the order screen order, but 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.

  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. 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 immediately after that and output the generated alert image to the handy terminal 2, but is not limited thereto. Absent. 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 is a diagram illustrating an example of a report image.

  The handy terminal 2 is, for example, a portable information terminal such as a business PDA. 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 by the sales promotion program to the user (for example, the order quantity) Increase). FIG. 6 is an example of a diagram in which an alert screen “alrt” is displayed on the handy terminal 2.

  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.

  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. As shown 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, etc., but is not limited to this. You may store quantity, a sales target achievement rate, etc.

  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 present embodiment, supplemental information is assumed to be associated with both the product ID and the 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 product type if the product is food, and a brand name if the product is clothing. In this embodiment, in order to simplify the description, one product keyword is associated with each product name. However, the present invention is not limited to this, and a plurality of product keywords are associated with one product. May be.

  FIG. 8 is a diagram illustrating an example of the supplement information table t61 stored in the store product supplement server 6. 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, for example, information stored by associating a broadcasting station identification ID for identifying a viewed broadcasting station and a time when the content is broadcast, and is a television for each country or region that can collect viewing logs. Collected from the receiver. It should be noted that the viewing log may be recorded not only as a real-time viewing log but also as recorded when the content is recorded or reserved for recording regarding viewing of content by the television receiver.

  The content information server 9 stores information (hereinafter referred to as content information) relating to the contents of various contents broadcast to television receivers nationwide as a content information table. The content information is, for example, information describing the content, and is information in which the content is associated with information related to an event (hereinafter referred to as an event) that occurred in the content.

  FIG. 9 is a diagram showing an example of the content information table t91 stored in the content information server 9. The content information table t91 represents, 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 event contents. Information (hereinafter referred to as event content information) and a broadcast station ID are stored in association with each other. The content information is assigned 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.

  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 store name and product name introduced during the event, the remarks of the performer reflected at the event, the name of the performer, the movement of the performer, the facial expression of the performer, etc. as text information It is what. Although only a part of the content information table t91 is depicted in FIG. 9, the content information table t91 actually stores all the content information corresponding to the content broadcasted nationwide or in the region.

  The content recording server 10 records content broadcasted by television broadcast stations 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,
Product supplement information acquisition unit 104, introduction content specific information acquisition unit 105, introduction content specific information storage unit 106, audience rating calculation unit 107, suitable content selection unit 108, sales promotion effect estimation unit 110, normal order quantity acquisition unit 111, sales promotion effect An information image generation unit 112, a sales promotion effect information image storage unit 113, a user input information reception unit 114, a user input information storage unit 115, and a preferred order quantity calculation unit 116 are included.

  The communication unit 101 is a network card, for example, 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.

  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, a case where the store product acquisition unit 102 outputs only one product ID to the store supplemental information acquisition unit 104 will be described. However, when there are a plurality of product IDs, the same process is repeatedly executed for each product ID. To do. In the present embodiment, the store product acquisition unit 102 acquires the product ID 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. 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. In the following description, the store product acquisition unit 102 will explain the 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, for example, supplement information (product keyword) associated with the acquired product ID from the store product supplement server 6. 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) that specifies content associated with event content information including the acquired product keyword from the content information server 9. In the following description, the introduction content is assumed to be content specified by a television program name. 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 an identification ID of 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.

FIG. 11 is a diagram illustrating an example of the introduction content identification information table t1051 in which the introduction content identification information acquired by the introduction content identification information acquisition unit 105 is stored. As shown in FIG. 11, the introduction content specifying information table t1051 is obtained by extracting the content including the product keyword from the content information table t91 shown in FIG. 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. The content audience rating table t1071 stores the television program name, which is the introduction content specifying information, the event start time and the event end time, the event inclusion corner including the introduction content, and the nationwide audience rating and the regional audience rating of the introduction content. doing. Details of the audience rating calculation process will be described later. Although the audience rating calculation unit 107 calculates the audience rating, the present invention is not limited to this. For example, the rate of change of the audience rating may be calculated. 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.

  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.

  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).

  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.

  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. The user input information is the expected audience rating, but is not limited to this, and may be the expected number of viewing televisions, the expected number of viewers, and the like. The expected audience rate, the expected number of viewers, and the expected number of viewers mentioned here are values that predict 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. 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.

  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.

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.

  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.

  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 an example of a sequence diagram illustrating 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. 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).

  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 suitable 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 suitable 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).

  FIG. 14 is an example of a flowchart illustrating an operation in which the audience rating calculation unit 107 calculates 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).

  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 ended yet (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 present embodiment, the predetermined time interval is set to one minute interval in order to obtain the number of viewers per unit time.

  Next, the audience rating calculation unit 107 divides the total number in ST204 by the broadcasting time of the introductory content, and calculates the average number of viewers in the whole country and region per unit time (in this embodiment, per minute). (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 nationwide and regional audience rating of the introduction content is 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 calculate the preferred order quantity. First, the sales promotion effect estimation unit 110 acquires a suitable content audience rating table (ST300). Next, the sales promotion effect estimation unit 110 refers to the audience rating of the preferred content audience rating table, and introduces content with the highest local audience rating. Are selected as sales promotion contents (ST301). In this embodiment, the sales promotion effect estimation unit 110 uses the introduction content with the highest local audience rating as the sales promotion content, but is not limited thereto, and the introduction content with the highest national audience rating may be used as the sales promotion content. Next, the sales promotion effect estimation part 110 acquires the introduction content specific information of the sales promotion content (ST302).

  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.

  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).

  FIG. 16 is an example of a flowchart for explaining the operation of the sales promotion effect estimation unit 110 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. It is a coefficient to be obtained. 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.

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 greater 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 local audience rating influence coefficient is expressed as k1, k1 is expressed by the following equation.
k1 = ((regional audience rating of promotional content) / (expected audience rating)) × (predetermined weight) (1)

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 until the present, and counting 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. 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)

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.
k2 = ((total viewing time when product is exposed) / (average viewing time of promotional content)) × (predetermined weight) (3)

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), the sales promotion effect estimation part 110 transfers to ST404. When the present is a holiday (ST403-Yes), the sales promotion effect estimation part 110 transfers 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.
k3 = ((average audience rating of all contents during the day) / (average audience rating of all contents broadcast in a predetermined period)) × (predetermined weight) (4)

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 factor is, for example, the sum of the average audience rating of all content broadcasted at midnight and the average audience rating of all content broadcast on Saturday morning. Is a coefficient obtained by dividing the value obtained by dividing 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.
k4 = (((average audience rating of all contents in midnight) + (average audience rating of all contents on Saturday morning)) / (average audience rating of all contents broadcast in a predetermined period))) (predetermined Weight) ... (5)

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. When the POP influence coefficient is k5, k5 is expressed by the following equation.
k5 = ((regional audience rating of content used at the time of POP creation) / (average audience rating of all content broadcast during a predetermined period))) × (predetermined weight) (6)

  Next, sales promotion effect estimating section 110 calculates other content influence coefficients (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. As shown in FIG. 17, in the keyword table t1101, for example, for a strawberry, a keyword of Christmas is associated with a time of December 24th. 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.

  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 the national or 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 present embodiment, the other content influence coefficient is calculated from the 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.

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. When the POP is not used, the POP influence coefficient k5 is excluded from the following formula. 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)

  FIG. 18 is an example of a flowchart illustrating an operation in which the sales promotion effect information image generation unit 112 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).

  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. 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, and is assumed to be set in advance in the sales promotion effect prediction server 4 for each image to be generated, but is not limited thereto. However, 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. It is assumed that a predetermined format such as is set in the sales promotion effect estimation server 4 in advance.

  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.

  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. .

  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, calculates the variation in the cumulative viewing time within the same period as the variation in the exposure time. An exposure time graph p6 is generated by superimposing the graph on the graph representing the variation in exposure time.

  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.

  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.

  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 whose regional audience rating is in the top three from the suitable content audience rating table, and performs natural language analysis from the event content information corresponding to the extracted content. Short text information representing an event is extracted, and an introduction content content image p12 is generated 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 part 112 arrange | positions the various images produced | generated by ST504-ST515 according to a predetermined format, and produces | generates the sales promotion effect information image img (ST515).

  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.

  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 convinced that it has generality. When a customer sees an advertisement using information on 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). Depending on the advertisement using (referred to as ST601-introducing person), different actions are taken. 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.

  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's behavior 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). The customer's behavior transitions to ST604 when watching a television program (ST603-Yes). When the customer's behavior is not watching the television program (ST603-No), the customer transitions to ST605.

  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.

  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's 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).

  From the above, when a store product is introduced in a television program, it is understood that if the customer is watching 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.

  FIG. 20 shows a histogram of the cumulative time that the product A or a category (for example, product type) including the product A is introduced in the contents for each date, and the change in the sales of the introduced product A on the histogram. It is the figure which put the change of the sales of the whole category in the form of a line graph. As shown in FIG. 20, it can be seen that the sales of the product A and the sales of the entire category including the product A increase with an increase in the time (exposure time) that the product A is introduced in the content. Such an increase in sales generally tends to occur in reality. Accordingly, the sales promotion effect estimation system 1 uses the introduction 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 favorable order that more appropriately reflects the sales promotion effect of the sales promotion content. Calculate the amount. Then, the user can perform more appropriate ordering work according to the calculated preferred order quantity.

In addition, in the said 1st Embodiment, although the sales promotion effect estimation system 1 shall transmit and display the sales promotion effect information image to the shop apparatus 3, 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.
Further, in the present 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 do that.

<Second Embodiment>
Hereinafter, the second embodiment will be described. About a structure, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part. In the sales promotion effect estimation system 1 according to 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. 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 device itself based on the calculated preferred order quantity. Moreover, the sales promotion effect estimation apparatus 11 displays the produced | generated sales promotion effect information image on the display of an own apparatus by operation from a user. Furthermore, the sales promotion effect estimation apparatus 11 outputs and displays the alert image allt on the handy terminal 2 when the audience rating of the sales promotion content exceeds a predetermined threshold.

  Thus, the sales promotion effect estimation system 1 of 2nd Embodiment is provided with the store apparatus 3 with the function part of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11, 1st Embodiment. The same effect can be obtained.

<Third Embodiment>
Hereinafter, a third embodiment will be described. About a structure, 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.

  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.

<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.

  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.

<Fourth Embodiment>
Hereinafter, a fourth embodiment will be described. About a structure, 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.

  FIG. 22 is a conceptual diagram for explaining a method for calculating an appropriate score. The sales promotion effect estimation part 110 calculates an appropriate score using the conceptual diagram of 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. 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 natural language analysis of the introduction content vvv, the weighting coefficient is 0.5.

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”.
(Weighting coefficient by elapsed time) = 1- (Elapsed time) / 70 (8)

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 the conceptual diagram of FIG. 22, there are only four viewers, the first to fourth viewers, but this is just 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 content-based weighting coefficient is 1, and the elapsed time-based weighting coefficient is 0. Since it is 82, the appropriate number of points is expressed by the following equation (9) and is 262.
320 × 1 × 0.82≈262 (9)

  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 the conceptual diagram of FIG. 22, the total appropriate score of 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 the example of the conceptual diagram of 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.

  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.

  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.

  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 summing or multiplying coefficients indicating the influence of the above may be used as a coefficient indicating the influence on the final sales promotion effect.

<Fifth Embodiment>
The fifth embodiment will be described below. About a structure, 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 present embodiment, in order to simplify the description, the sales promotion product is food, but the present invention is not limited to this, and clothing, electrical appliances, and the like may be used.

  FIG. 23 is a conceptual diagram for explaining selection of correlated content. The sales promotion effect estimation part 110 selects a correlation content using the conceptual diagram of FIG. The conceptual diagram of FIG. 23 is 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 the conceptual diagram of FIG. 23, all viewing situations of the contents 1 to 3 are “viewing”. The second right column of the conceptual diagram displays the number of views for each viewing situation. Therefore, in the second row of the conceptual diagram, the number of views for each viewing situation in the right-right column represents the number of television receivers that have viewed all of the contents 1 to 3. In the third row of the conceptual diagram of FIG. 23, the number of views for each viewing situation in the right-right column is the number of television receivers viewing both content 1 and content 2 but not viewing content 3. The bottom line of the conceptual diagram of FIG. 23 displays the total number of television receivers viewed for each content.

  The sales promotion effect estimation unit 110, for example, selects the content 1 with the highest audience rating that introduced the promotional product in the past 3 days, and the content 2 with the sales promotion product with the highest national audience rating after the content 1 in the past 3 days. The introduced content. 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. The related food is, for example, a fresh cream or flour used for a roll cake when a roll cake using the strawberry is introduced if the promotional product is “boil”.

  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.

The sales promotion effect estimation unit 110 includes, for example, content 1 that introduces the candy “Amaio”, content 2 that introduces the ranking of candy, and content 3 that introduces fresh cream (the above-mentioned related food). In some cases, content 2 and content 3 are candidates for other content that is a keyword extraction source for calculating the other content influence coefficient k6. 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 the conceptual diagram 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 watched is 45. The number N12 that was viewing either the content 1 or the content 2 is represented by the following equation (10), and the number N13 that was viewing either the content 1 or the content 3 is the following equation (11): It is represented by
N12 = 100 + 20 = 120 (units) (10)
N13 = 100 + 45 = 145 (units) (11)

  In this case, the sales promotion effect estimation unit 110 can obtain a more suitable other content influence coefficient k6 by selecting the content 3 as the extraction source content because N13 is greater than N12. Accordingly, the sales promotion effect estimation unit 110 selects the content 3 as the extraction source content.

  Thus, the sales promotion effect estimation server 4 of 5th Embodiment can obtain the more suitable other content influence coefficient k6 by extracting the extraction source content with high correlation with a sales promotion content, As a result, Thus, a coefficient indicating a more preferable sales promotion effect can be calculated.

<Sixth Embodiment>
The sixth embodiment will be described below. About a structure, 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.

  For example, the sales promotion effect estimation unit 110 calculates 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.

  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.

<Seventh Embodiment>
The seventh embodiment will be described below. About a structure, 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 sixth 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 illustrating a usage situation of the sales promotion effect estimation system 1 according to 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.

  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.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and changes, substitutions, deletions, and the like are possible without departing from the gist of the present invention. May be.

  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. Here, the “computer system” includes hardware such as an OS (Operation System) and peripheral devices.

Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used.
The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Furthermore, the “computer-readable recording medium” dynamically holds a program for a short time like 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, a volatile memory in a computer system serving as a server or a client in that case, and a program that holds a program for a certain period of time are also included. 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.

(1) One aspect of the present invention is a first acquisition unit that acquires viewing history information of broadcast content that includes information related to a product,
Based on the acquired viewing history information, an estimation unit that calculates an estimated value indicating an effect of promoting sales of the product from content including information related to the product;
Is a sales promotion effect estimation device.
(2) Moreover, the other aspect of this invention is the sales promotion effect estimation apparatus as described in (1), Comprising: The 2nd acquisition part which acquires the reference value for calculating the estimated value which shows the said effect is provided. The estimation unit is a sales promotion effect estimation device that calculates an estimated value indicating the effect based on the acquired value of the viewing history information and the acquired reference value.
(3) Moreover, the other aspect of this invention is the sales promotion effect estimation apparatus as described in (2), Comprising: The said 2nd acquisition part receives the input of the numerical value from a user, The said received numerical value is It is a sales promotion effect estimation apparatus acquired as the reference value.

(4) Further, another aspect of the present invention is the sales promotion effect estimation device according to (2), including a first calculation unit that calculates a value that predicts a viewing degree of the broadcasted content. The second acquisition unit is a sales promotion effect estimation device that acquires, as the reference value, a value predicted by the first calculation unit for the degree of viewing.
(5) According to another aspect of the present invention, there is provided the sales promotion effect estimation device according to (4), wherein the first calculation unit is the previous time when the broadcasted content is regularly broadcast. The sales promotion effect estimation device calculates the reference value based on previous broadcast viewing history information.

(6) Moreover, another aspect of the present invention is the sales promotion effect estimation device according to (2), wherein the second acquisition unit broadcasts content including information related to the product. It is a sales promotion effect estimation apparatus which acquires the anticipated viewing history information anticipated previously from an external server as said reference value.
(7) Moreover, the other aspect of this invention is the sales promotion effect estimation apparatus as described in any one of (1) to (6), Comprising: The said estimation part reflects user operation, Web server Is a sales promotion effect estimation device that estimates the effect based on information related to content including information related to the product.

(8) Moreover, the other aspect of this invention is the sales promotion effect estimation apparatus as described in any one of (1) to (7), Comprising: The said estimation part contained the information regarding the said goods. It is a sales promotion effect estimation apparatus which estimates the said effect based on the period when the content was broadcast.
(9) According to another aspect of the present invention, in the sales promotion effect estimation device according to any one of (1) to (8), the viewing history information acquired by the first acquisition unit is , A sales promotion effect estimation device comprising: a determination unit that determines whether or not a setting condition is satisfied; and an alert unit that outputs information for prompting adjustment of the order quantity of the product based on a determination result of the determination unit. .

(10) Moreover, the other aspect of the present invention is the sales promotion effect estimation device according to any one of (1) to (9), wherein the estimated value indicating the effect satisfies a setting condition A sales promotion effect estimation device comprising: a determination unit that determines whether or not; and an alert unit that outputs information that prompts adjustment of the order quantity of the product based on a determination result of the determination unit.
(11) Moreover, the other aspect of this invention is the sales promotion effect estimation apparatus as described in (9), Comprising: When the said estimation part determines with the determination result of the said determination part satisfy | filling the said setting conditions, A sales promotion effect estimation device for calculating an estimated value indicating an effect of promoting the sale of the product.

(12) According to another aspect of the present invention, in the sales promotion effect estimation device according to any one of (9) to (11), the alert unit is information that prompts the adjustment of the order quantity. This is a sales promotion effect estimation device that outputs information that prompts adjustment of the order quantity of a product that is different from the product that outputs the information and that prompts adjustment of the order quantity.
(13) According to another aspect of the present invention, there is provided the sales promotion effect estimation device according to any one of (1) to (12), and based on an estimation result of the estimation unit, It is a sales promotion effect estimation apparatus provided with the 2nd calculation part which calculates order quantity.

(14) According to another aspect of the present invention, there is provided the sales promotion effect estimation device according to any one of (1) to (13), the information based on the estimation result of the estimation unit, and the product It is a sales promotion effect estimation apparatus provided with the production | generation part which produces | generates the image containing the information of the content in which the information relevant to is included.
(15) According to another aspect of the present invention, the sales promotion effect estimation device according to (14) that cites (13) or (13) and the order quantity calculated by the second calculation unit, An order management apparatus comprising an ordering unit that orders products.

(16) According to another aspect of the present invention, the sales promotion effect estimation device according to any one of (1) to (15), a reception unit that receives an input of an order quantity from a user, and the reception An order management apparatus comprising an ordering unit for ordering a predetermined order quantity.
(17) Further, according to another aspect of the present invention, the viewing history information of content that is broadcasted content including information related to a product is acquired, and based on the acquired viewing history information, It is a sales promotion effect estimation method which calculates the estimated value which shows the effect which promotes the sale of the said goods from the content in which the information relevant to goods is included.
(18) According to another aspect of the present invention, a computer is made to acquire viewing history information of a content that is broadcast and includes information related to a product, and based on the acquired viewing history information. And a sales promotion effect estimation program for calculating an estimated value indicating an effect of promoting sales of the product from content including information related to the product.

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 Unit 104 ... product supplement information acquisition unit 105 ... introduction content specific information acquisition unit 106 ... introduction content specific information storage unit 107 ... audience rating calculation unit 108 ... suitable content selection unit 110 ... Preferred order quantity calculation unit 111 ... Normal order quantity acquisition unit 112 ... Sales promotion effect information image generation unit 113 ... Sales promotion effect information image storage unit 114... User input information reception unit 115... User input information storage unit 116.

Claims (26)

Content content information describing the content of the broadcasted content , including an event occurrence period indicating a period in which the event is occurring for each of a plurality of events in the program, information on products related to the event, and the event A specific unit that refers to content content information including content information indicating related content, and identifies content related to the event occurrence period based on information about the product;
A first acquisition unit that acquires viewing history information of content related to the specified event occurrence period ;
Reads the corresponding information that associates the estimated value and the viewing history information from the storage unit, based on the acquired viewing history information, said indicating the effect of promoting the sale of the commodity that response rate of content associated with the prior Symbol event occurrence period An estimation unit for calculating an estimated value;
A sales promotion effect estimation device. The sales promotion effect estimation device according to claim 1,
The specifying unit acquires information on store products that can be handled at the store for each store, specifies content related to the event occurrence period based on information about the store products,
The estimation unit calculates the estimated value used for calculating the demand amount of the store product .
Promotional effect estimation device . The sales promotion effect estimation device according to claim 1 or 2,
The estimation unit is an effect produced when content related to the event occurrence period is used in a store, and calculates the estimated value indicating an effect of promoting the sale of the product.
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 3,
The correspondence information is different between a case where content related to the event occurrence period is used at a store and a case where content related to the event occurrence period is not used at a store.
The estimation unit includes the estimated value used for calculating a demand amount when content related to the event occurrence period is used in a store, and a demand amount when content related to the event occurrence period is not used in the store. Calculating the estimated value used to calculate
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 4,
The first acquisition unit acquires regional viewing degree information indicating a viewing degree in a region including a store,
The estimation unit calculates the estimated value provided to the store based on the acquired regional viewing degree information.
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 5,
The first acquisition unit acquires the viewing history information of each playback device that plays back the broadcasted content,
The estimating unit calculates a viewing time of content related to an event occurrence period based on the viewing history information, and calculates the estimated value based on the calculated viewing time;
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 6,
The first acquisition unit acquires the viewing history information of each playback device that plays back the broadcasted content,
The estimation unit calculates a viewing time of content in a time zone in which information related to the product appears among contents related to an event occurrence period based on the viewing history information, and based on the calculated viewing time Calculate an estimate,
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 7,
The estimation unit calculates the estimated value based on information indicating a degree of viewing of content related to the event occurrence period used in a store.
Promotional effect estimation device . The sales promotion effect estimation device according to any one of claims 1 to 8 ,
A second acquisition unit for acquiring a reference value for calculating the pre Ki推 value,
The estimating unit, the value of the acquired viewing history information, based on a reference value which the acquired and before calculating the Ki推 value,
Promotional effect estimation device. The sales promotion effect estimation device according to claim 9 ,
The second acquisition unit receives an input of a numerical value from a user, and acquires the received numerical value as the reference value.
Promotional effect estimation device. The sales promotion effect estimation device according to claim 9 ,
A first calculation unit that calculates a value that predicts a viewing degree of the broadcast content;
The second acquisition unit acquires, as the reference value, a value predicted by the first calculation unit for the degree of viewing;
Promotional effect estimation device. The sales promotion effect estimation device according to claim 11 ,
The first calculation unit calculates the reference value based on viewing history information of the previous broadcast when the broadcasted content is broadcast regularly.
Promotional effect estimation device. The sales promotion effect estimation device according to claim 9 ,
The second acquisition unit acquires, from the external server, the expected viewing history information predicted before the content including information related to the product is broadcast, as the reference value.
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 13 ,
The estimation unit is information provided by a web server reflecting a user operation, and calculates the estimated value based on information related to content including information related to the product.
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 14 ,
The estimation unit reads correspondence information associating a time with an estimated value from the storage unit, and calculates the estimated value based on a time when the content including information on the product is broadcast.
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 15 ,
A determination unit that determines whether the viewing history information acquired by the first acquisition unit satisfies a setting condition;
Based on the determination result of the determination unit, an alert unit that outputs information that prompts adjustment of the demand amount of the product;
A sales promotion effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 16 ,
Before Ki推 value is a determination section for determining whether or not setting condition is satisfied,
Based on the determination result of the determination unit, an alert unit that outputs information that prompts adjustment of the demand amount of the product;
A sales promotion effect estimation device. The sales promotion effect estimation device according to claim 17 ,
The estimating unit, the determination unit of the judgment result, when it is determined that the setting condition is satisfied, pre-calculated Ki推 value,
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 16 to 18 ,
The alert section is a different product from the product to output information prompting adjustment of the demand, the information prompting adjustment of the demand for products related to the product to output information prompting adjustment of the demand Output together,
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 19 ,
A second calculating unit that calculates a demand amount of the product based on an estimation result of the estimating unit;
Promotional effect estimation device. The sales promotion effect estimation device according to any one of claims 1 to 20 ,
A generation unit that generates an image including information based on an estimation result of the estimation unit and content information including information related to the product;
Promotional effect estimation device. The sales promotion effect estimation device according to claim 21 that cites claim 20 or claim 20 ,
An ordering unit that orders the product based on the demand amount calculated by the second calculation unit;
An order management device comprising: The sales promotion effect estimation device according to any one of claims 1 to 22 ,
A reception unit for receiving an input of an order quantity from a user;
An ordering unit for ordering products with the received order quantity;
An order management device comprising: Content content information describing the content of the broadcasted content , indicating an event occurrence period indicating a period in which the event has occurred for each of a plurality of events in the program, and information and contents relating to a product related to the event Content content information including content 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 ;
Reads the corresponding information that associates the estimated value and the viewing history information from the storage unit, based on the acquired viewing history information, said indicating the effect of promoting the sale of the commodity that response rate of content associated with the prior Symbol event occurrence period Calculate an estimate,
Promotional effect estimation method. On the computer,
Content content information describing the content of the broadcasted content , indicating an event occurrence period indicating a period in which the event has occurred for each of a plurality of events in the program, and information and contents relating to a product related to the event The content information including the content information is referenced, the content related to the event occurrence period is specified based on the information about the product,
Obtaining viewing history information of content related to the identified event occurrence period ;
To read the correspondence information that associates the estimated value and the viewing history information from the storage unit, based on the viewing history information said to acquire the effect of promoting the sale of the commodity that response rate of content associated with the prior Symbol event occurrence period to calculate the estimated value indicating,
Promotional effect estimation program. Content content information describing the content of the broadcasted content, indicating an event occurrence period indicating a period in which the event has occurred for each of a plurality of events in the program, and information and contents relating to a product related to the event A specific unit that refers to content content information including content information and identifies content related to the event occurrence period based on information about the product;
A first acquisition unit that acquires 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;
A system comprising:

Images