WO2014208662A1

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

Info

Publication number: WO2014208662A1
Application number: PCT/JP2014/066974
Authority: WO
Inventors: 広明近藤; 小笠原　大樹
Original assignee: シャープ株式会社
Priority date: 2013-06-28
Filing date: 2014-06-26
Publication date: 2014-12-31
Also published as: JP5485454B1; JP2015011577A

Abstract

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

Description

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

The present invention relates to a sales promotion effect estimation method, a sales promotion effect estimation device, a sales promotion effect estimation system, and a recording medium.
This application claims priority on June 28, 2013 based on Japanese Patent Application No. 2013-137312 for which it applied to Japan, and uses the content here.

In recent years, the impact on consumption trends by television programs provided by the mass media has been significantly increasing. In particular, products introduced on television programs tend to increase in sales volume after broadcasting. However, mass media's original product introduction by television programs is not originally a sales promotion activity intended by a product maker or other person who provides products. For this reason, it has been difficult to predict the order quantity of products introduced in a television program as a target of order in the conventional product order management system based on sales trend prediction.

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.

Japanese Patent Laid-Open No. 2003-233751

The automatic merchandise order processing system described in Patent Document 1 uses program data of a television program before broadcasting. Therefore, the details of the contents of the television program are not known, and the sales promotion (sales promotion) effect necessary to calculate a suitable order quantity cannot be accurately predicted.
In addition, if the television program is a live broadcast, or if the television program is not broadcast due to an extension of a baseball broadcast or the like, it is not only difficult to predict the sales promotion effect with this product automatic order processing system, but also the sales promotion. The effect may be overestimated or underestimated.

One aspect of the present invention is to provide a sales promotion effect estimation method capable of more appropriately estimating the sales promotion effect of content including information related to a product.

One aspect of the present invention relates to content content information describing the content of broadcast content, and relates to an event occurrence period that indicates a period in which an event that is at least a part of a program is occurring, and a product related to the event Content content information including information and content information is specified, content related to the event occurrence period is specified based on information about the product, and viewing history information of the content related to the specified event occurrence period And reading correspondence information that associates the viewing history information with the estimated value from the storage unit, and based on the obtained viewing history information, the effect of promoting the sale of the product played by the content related to the event occurrence period is obtained. It is the sales promotion effect estimation method which calculates the said estimated value to show.

According to one aspect of the present invention, it is possible to provide a sales promotion effect estimation method that can more appropriately estimate the sales promotion effect of content including information related to a product.

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 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 illustrating a usage situation of the sales promotion effect estimation system according to the first embodiment. The sales promotion effect estimation system 1 includes a handy terminal 2, a store apparatus 3, a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server. 10 is included.
In the sales promotion effect estimation system 1, for example, a handy terminal 2, a store apparatus 3, a store product server 5, and a store product supplement server 6 are installed in the store “Shp”.

The store apparatus 3, the store product server 5, and the store product supplement server 6 are connected to be communicable via a network such as a LAN (Local Area Network). Further, the handy terminal 2 is connected to the store apparatus 3 so as to be communicable with a wireless LAN or the like, for example.
The network NW is, for example, a network such as the Internet or a mobile communication network, but is not limited thereto. The network NW may be an intranet, a dedicated line, or the like, or an information communication network configured by a combination thereof.
For example, a store device 3, a sales promotion effect estimation server 4, a store product server 5, a store product supplement server 6, a POS server 7, a viewing log server 8, a content information server 9, and a content recording server 10 are connected to the network NW. Are in a state where they can communicate with each other.

The sales promotion effect estimation server 4 includes, for example, information relating to products that can be handled by the store “Shp”, or information that will be handled in the future (hereinafter referred to as store products), and content that includes information related to store products (hereinafter referred to as introduction content). ) (For example, a television program name, a radio program name, a broadcast date, etc. of the introduction content) is acquired from various servers connected to the network NW. Acquisition of introduction content will be described later.
Store merchandise is, for example, food, clothing, or electrical appliances. The content is, for example, a television program or a radio program itself. Note that the content is content that is divided when a television program broadcast by a television broadcast station is divided by time, a corner in a television program, or a time zone that spans multiple television programs. May be.
In addition, the content may be content that is divided when a radio program broadcast by a radio broadcasting station is divided by time, a corner in the radio program, or a time zone that spans multiple radio programs.

In the following description, the case where the content is a television program itself will be described. The content including information related to the store product includes, for example, content that introduces the store product, content that shows the store product, and content in which the name of the store product appears.
In the following description, the case where the content including information related to the store product is content in which the store product is introduced will be described. Moreover, when the information regarding a some store product is contained in a content, the sales promotion effect estimation server 4 performs the following processes for every store product.

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 a sales promotion effect information image according to the first embodiment.
As shown in FIG. 2, the sales promotion effect information image “img” is composed of, for example, images p1 to p11. The sales promotion effect estimation server 4 generates, as an image p1, an introduction content information image that displays information on the introduction content having the highest audience rating among the introduction contents that are considered to have influenced the sales promotion effect of the store product.
The audience rating may be the national audience rating or the audience rating in the area including the store “Shp” (hereinafter referred to as the regional audience rating). The audience rating may be a combination of the national audience rating and the regional audience rating, with priority given to either the national audience rating or the local audience rating. The sales promotion effect estimation server 4 generates a national audience rating image displaying the national audience rating as an image p2.
The sales promotion effect estimation server 4 generates a regional audience rating image displaying the regional audience rating as an image p3. The sales promotion effect estimation server 4 produces | generates the site information image which displays the information obtained from a website regarding a store product as the image p4.

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 is obtained by multiplying the cumulative time when the store product appears in the introduction content broadcast in the area including the store “Shp” by the number of television receivers viewing the introduction content. A total viewing time image displaying the total viewing time is generated as an image p10.
The sales promotion effect estimation server 4 generates, as an image p11, an introductory content detail image that displays the local audience rating of each introductory content together with the introductory content that ranks in the top three. Details of generation of the sales promotion effect information image “img” will be described later.

The store apparatus 3 is, for example, a computer in which a POS (Point Of Sale) application is installed. Further, the store apparatus 3 includes, for example, an input device such as a barcode reader or a keyboard, and a display device such as an operator display (operation display) or a customer display (customer display). The store apparatus 3 reads a barcode attached to a product (a product ID or the like is recorded) with a barcode reader.
Further, the store apparatus 3 accepts input of necessary information such as an order amount through a keyboard. The store apparatus 3 acquires the preferred order quantity of the store product and the introduction information from the sales promotion effect estimation server 4 via the network NW. Further, the store apparatus 3 acquires information related to store products and the above-described normal order quantity from the POS server 7.

The store apparatus 3 generates an order screen for the store product based on the acquired information about the store product, the preferred order quantity, and the introduction information. When the store apparatus 3 receives an operation for displaying an order screen for a store product selected by a user (for example, a store operator), the store device 3 is generated if the store product selected by the user is a product introduced in the introduction content. Display the ordering screen.
On the other hand, if the store product selected by the user is a product that is not introduced in the introduction content, the store apparatus 3 displays the order screen generated based on the acquired normal order quantity on the display of the store apparatus 3 as a default screen. To do. In addition, in 1st Embodiment, although the shop apparatus 3 demonstrated the case where the information regarding shop goods and the normal order quantity were acquired from the POS server 7, it is not restricted to this. For example, the user may input information related to store products and the normal order quantity with a keyboard or the like.

FIG. 3 is a diagram illustrating an example of an ordering screen according to the first embodiment.
The store apparatus 3 generates an ordering screen “order” in which the acquired preferred order quantity is displayed in the order quantity “size”, and generates an alert image “ntc” based on the acquired introduction information. The alert image “ntc” is arranged as shown in FIG.
A detail button “btn” is arranged in the alert image “ntc”. When the user selects and determines the detail button “btn”, the sales promotion effect estimation server 4 acquires the sales promotion effect information image “img” for the store product from the sales promotion effect estimation server 4, and acquires the acquired sales promotion effect information image “img”. It is displayed on the display of the store apparatus 3.
Note that the store apparatus 3 may output a sound when the sales promotion effect information image “img” is accompanied by a sound. In the first embodiment, the store apparatus 3 places an order by the user selecting and determining the order button on the order screen “order”. However, the present invention is not limited to this. For example, the store apparatus 3 may automatically place an order for the acquired preferred order quantity without any user operation.

The store apparatus 3 extracts the audience rating of the introduction content from the acquired introduction information, and when the extracted audience rating exceeds a predetermined threshold, for example, the order amount of the store product introduced by the introduction content is increased. An alert image for prompting is generated, and the generated alert image is output to the handy terminal 2 and displayed.
The store apparatus 3 extracts the rate of change of the viewing rate of the introduction content from the introduction information, and if the extracted rate of change exceeds a predetermined threshold, the order amount of the store product introduced by the introduction content is increased. An alert image that prompts the user may be generated.
Further, the store apparatus 3 acquires the coefficient indicating the sales promotion effect described above, determines whether or not the acquired coefficient indicating the sales promotion effect exceeds a predetermined threshold, and generates an alert image based on the determination result. Good.

FIG. 4 is a diagram illustrating an example of an alert image according to the first embodiment.
The predetermined threshold value may be set in advance or may be set later by the user. Further, when the extracted audience rating exceeds a predetermined threshold, the store apparatus 3 may generate an alert image “alrt” immediately after that and output the generated alert image “alrt” to the handy terminal 2. However, it is not limited to this.
The store apparatus 3 displays information that prompts the customer to increase the order quantity of store products corresponding to the audience rating that exceeds a given threshold during the day until the given time of the day. Report images arranged in descending order may be generated, and the generated report images may be output to the handy terminal 2.

FIG. 5 in the first embodiment is a diagram illustrating an example of a report image.

The handy terminal 2 is a portable information terminal such as a business PDA (Personal Digital Assistant). When the handy terminal 2 acquires the alert screen or the report image “rprt” from the store apparatus 3, the handy terminal 2 displays the acquired image on the display, and adjusts the order quantity of the store product introduced to the user by the sales promotion program (for example, Increase order volume).

FIG. 6 is an example of a diagram in which an alert screen “alrt” is displayed on the handy terminal 2 in the first embodiment.

The POS server 7 is a server that controls the POS system. The POS server 7 receives product IDs from various servers and devices, and searches for store product information (hereinafter referred to as product information) such as store products indicated by the received product IDs, store product prices, and normal order quantities of store products. Then, the retrieved product information is output to various servers and devices.

The store product server 5 stores a store product table.

FIG. 7 is an example of the store product table t51 stored in the store product server 5 in the first embodiment.
As illustrated in FIG. 7, the store product table t51 stores, for example, a product ID for identifying a store product, a product name, a place of production, a price of the product, and the like, but is not limited thereto. For example, the store product table t51 may store the number of items in stock, the quantity already ordered, the sales target achievement rate, and the like.

The store product supplement server 6 stores supplement information associated with various product names and / or product IDs stored in the store product table t51 as a supplement information table. In the first embodiment, supplementary information is described as being associated with both a product ID and a product name, but may be associated with either one.
The supplemental information is, for example, a keyword related to a product (hereinafter referred to as a product keyword). The product keyword is, for example, a product type corresponding to the product name. Specifically, the product keyword corresponds to a variety or the like when the product is food, and a brand name or the like when the product is clothing. In the first embodiment, in order to simplify the description, a case where one product keyword is associated with each product name will be described. However, the present invention is not limited to this, and a plurality of product keywords are associated with one product. May be associated.

FIG. 8 is a diagram illustrating an example of the supplement information table t61 stored in the store product supplement server 6 according to the first embodiment.
The supplementary information table t61 stores a product keyword associated with the product ID and the product name. Further, the supplementary information table t61 is associated with the store product table t51 of FIG. 7 through the product ID and the product name.

The viewing log server 8 stores viewing logs collected from television receivers nationwide. The viewing log is information that stores, for example, a broadcast station identification ID that identifies a broadcast station that has been viewed and a time when the content is broadcast. The viewing log is collected from a television receiver for each country or region where the viewing log can be collected. Note that the viewing log may be recorded not only as a real-time viewing log but also as a view when the content is recorded or reserved for recording when viewing the content by the television receiver.

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

FIG. 9 is a diagram illustrating an example of the content information table t91 stored in the content information server 9 according to the first embodiment.
The content information table t91 includes, for each record, an identification ID, an event start time, an event end time, content (television program name), a corner name when an event occurs (hereinafter referred to as an event inclusion corner), and the contents of the event. Information to be represented (hereinafter referred to as event content information) and a broadcast station ID are stored in association with each other.
The content information is given an identification ID for identifying the information. For example, an event indicates an event such as a speech made by a performer or a video stream.

Information related to events includes, for example, the time at which an event occurred (hereinafter referred to as event start time), the time at which the event ended (hereinafter referred to as event end time), event content information, event inclusion corner, And information describing a broadcasting station ID for identifying a broadcasting station broadcasting a television program in which an event has occurred.
Event content information includes, for example, the name of the store introduced during the event, the name of the product, the remarks of the performer reflected during the event, the name of the performer, the movement of the performer, the facial expression of the performer, etc. Is recorded as text information. Although only a part of the content information table t91 is shown in FIG. 9, the content information table t91 actually stores all the content information corresponding to the content broadcast in the whole country or region.

The content recording server 10 records the content broadcast by each television broadcasting station nationwide and stores it as a content video that is a video for each content. The content recording server 10 transmits the content video to the sales promotion effect estimation server 4 in accordance with the content video acquisition request from the sales promotion effect estimation server 4.

FIG. 10 is a schematic block diagram showing an example of the configuration of the sales promotion effect estimation server 4 in the first embodiment.
The sales promotion effect estimation server 4 includes, for example, a communication unit 101, a store product acquisition unit 102, a product supplement information acquisition unit 104, an introduction content specification information acquisition unit 105, an introduction content specification information storage unit 106, an audience rating calculation unit 107, and a suitable content. Selection unit 108, sales promotion effect estimation unit 110, normal order quantity acquisition unit 111, sales promotion effect information image generation unit 112, sales promotion effect information image storage unit 113, user input information reception unit 114, user input information storage unit 115, and preferred order A quantity calculation unit 116 is included.

The communication unit 101 is, for example, a network card, and communicates with various servers through a LAN or a network NW. In addition, the communication unit 101 responds to an instruction (request) from the product supplement information acquisition unit 104, the introduction content specifying information acquisition unit 105, the normal order quantity acquisition unit 111, etc., the store product server 5, the store product supplement server 6, It communicates with each of the POS server 7, the viewing log server 8, the content information server 9, and the content recording server 10.

The store product acquisition unit 102 acquires, for example, the store product table t51 from the store product server 5, selects one product ID from the acquired store product table t51 one by one, and selects the selected product ID as a store product supplement information acquisition unit. To 104.
The store product acquisition unit 102 outputs the acquired product ID to the product supplement information acquisition unit 104. In the following, the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplementary information acquisition unit 104. However, when there are a plurality of product IDs, the same processing is performed for each product ID. Run repeatedly.
In the first embodiment, the store product acquisition unit 102 acquires the store product table t51 from the store product server 5 and selects the product IDs one by one from the acquired store product table t51. However, the present invention is not limited to this. Absent. The store product acquisition unit 102 acquires, for example, a store product that the user is trying to place an order from the store apparatus 3, searches the store product server 5 for the product ID of the acquired store product, and acquires the acquired product ID. , It may be output to the store product supplement information acquisition unit 104.
Hereinafter, the store product acquisition unit 102 will be described with respect to a case where only one product ID is output to the store supplemental information acquisition unit 104. However, when there are a plurality of product IDs, the following processing is repeatedly executed.

The product supplement information acquisition unit 104 acquires supplement information (product keyword) associated with the acquired product ID from the store product supplement server 6, for example. The product supplementary information acquisition unit 104 outputs the acquired product keyword to the introduction content specifying information acquisition unit 105.

The introductory content specifying information acquisition unit 105 acquires information (hereinafter referred to as introductory content specifying information) for specifying the content associated with the event detail information including the acquired product keyword from the content information server 9.
Hereinafter, a case where the introduction content is content specified by a television program name will be described. Here, a specific example of acquiring the introduction content specifying information will be described.
In the content information table t91 of FIG. 9, when a record with the identification ID “3434366” is seen, the keyword “strawberry” is included as event content information. When this “strawberry” is the product keyword of the sales promotion product, information included in this record is acquired as introduction content specifying information.

FIG. 11 is a diagram illustrating an example of the introduction content identification information table t1051 that stores the introduction content identification information acquired by the introduction content identification information acquisition unit 105 according to the first embodiment.
As illustrated in FIG. 11, the introduction content specifying information table t1051 is a table obtained by extracting the content including the product keyword from the content information table t91 illustrated in FIG. 9. The introduction content specific information acquisition unit 105 stores the acquired introduction content specification information in the introduction content specification information storage unit 106 as an introduction content specification information table t1051.
The introduction content specifying information storage unit 106 is a RAM (Random Access Memory), a register, or a recording medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The introductory content specific information storage unit 106 stores an introductory content specific information table t1051.

The audience rating calculation unit 107 reads the introduction content identification information table t1051 from the introduction content identification information storage unit 106. The audience rating calculation unit 107 acquires the viewing log of the introduction content from the viewing log server 8 based on the read introduction content specifying information table t1051.
The audience rating calculation unit 107 calculates the audience rating of the introduction content based on the acquired viewing log, and generates a content audience rating table.

FIG. 12 is an example of the content audience rating table t1071 in the first embodiment.
The content audience rating table t1071 stores the event inclusion corner including the introduction content, the television program name as the introduction content specifying information, the event start time and the event end time, and the national audience rating and the local audience rating of the introduction content. To do. Details of the audience rating calculation process will be described later.
Note that the audience rating calculation unit 107 has been described for calculating the audience rating, but the present invention is not limited to this. For example, the audience rating calculation unit 107 may calculate the rate of change of the audience rating. In this case, the content audience rating table t1071 stores the audience rating change rate together with the audience rating. The audience rating calculation unit 107 outputs the generated content audience rating table t1071 to the preferred content selection unit 108.

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. In addition, although the case where the user input information is the expected audience rating has been described, the present invention is not limited to this and may be the expected number of viewing televisions, the expected number of viewers, and the like. The predicted audience rate, the expected number of viewers, and the expected number of viewers here are examples of values for predicting the degree of content viewing in the claims.

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 a sequence diagram for explaining operations until the introduction content specifying information acquisition unit 105, the audience rating calculation unit 107, and the preferred content selection unit 108 generate a preferred content audience rating table according to the first embodiment. It is an example.
First, the introductory content specific information acquisition unit 105 acquires a product keyword of a sales promotion product (ST100).
Next, the introduction content specifying information acquisition unit 105 acquires the introduction content specifying information table t1051 based on the product keyword (ST101).
Next, introductory content specific information acquisition section 105 outputs introductory content specific information table t1051 to audience rating calculation section 107 (ST102).
Next, the audience rating calculation unit 107 selects introduction contents one by one from the acquired introduction content specifying information table t1051, and calculates the national audience rating and the regional audience rating of the selected introduction content (ST103). Details of the audience rating calculation will be described later.
Next, audience rating calculation section 107 generates content audience rating table t1071 (ST104).

Next, audience rating calculation section 107 outputs content audience rating table t1071 to content selection section 108 (ST105).
Next, the preferred content selection unit 108 repeatedly performs the processing from ST107 to ST108 for each record in the content audience rating table t1071 (ST106, ST109).
The preferred content selection unit 108 performs negative impression determination (ST107).
When the event content information of the selected introduction content is associated with the negative content information (ST107-Yes), the preferred content selection unit 108 transitions to ST108.
When the event content information of the introduction content selected from the content audience rating table t1071 does not correspond to the negative content information (ST107-No), the preferred content selection unit 108 performs the process of ST107 on the next record.
When the event content information of the introduction content for which the natural language analysis has been performed is associated with the negative content information in ST107, the suitable content selection unit 108 performs table optimization processing (ST108).

FIG. 14 is an example of a flowchart for explaining the operation of the audience rating calculation unit 107 in the first embodiment calculating the national audience rating and the local audience rating of the introduction content in ST103 of FIG.
First, the audience rating calculation unit 107 acquires the introduction content specifying information table t1051 (ST200).
Next, the audience rating calculation unit 107 acquires a viewing log of the introduction content (ST201).
Next, audience rating calculation section 107 repeatedly executes the processing from ST203 to ST206 for each introduction content in introduction content identification information table t1051 (ST202, ST207).

The audience rating calculation unit 107 determines whether or not the introduction content has ended (ST203).
When the introduction content has already ended (ST203-Yes), the audience rating calculation unit 107 transitions to ST204. When the introduction content has not yet ended (ST203-No), the audience rating calculation unit 107 performs the process of ST203 on the next introduction content.
In ST203, when the introduction content has ended, the audience rating calculation unit 107 divides the broadcast time of the introduction content into predetermined time intervals, and the television receiver that has watched the introduction content for each divided time interval. The total number of machines in the whole country and region is counted, and the total is calculated by summing up the number of machines counted for each divided time interval (ST204). In the first embodiment, the predetermined time interval is a one-minute interval in order to obtain the number of viewers per unit time.

Next, the audience rating calculation unit 107 divides the total number in ST204 by the broadcasting time of the introduction content, and the national and regional data per unit time (in the case of the first embodiment, per minute). The average number of viewers is calculated (ST205).
Next, the audience rating calculation unit 107 calculates the average number of viewers in the whole country and region, the number of all television receivers that can collect viewing logs in the whole country, and all televisions that can collect viewing logs in the region. By dividing by the number of John receivers, the national audience rating and regional audience rating of the introduction content are calculated (ST206).

FIG. 15 is an example of a sequence diagram illustrating operations until the sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 according to the first embodiment calculate the preferred order quantity.
First, the sales promotion effect estimation part 110 acquires a suitable content audience rating table (ST300).
Next, sales promotion effect estimation section 110 refers to the audience rating in the preferred content audience rating table, and selects the introduction content with the highest local audience rating as the promotional content (ST301). In the first embodiment, the sales promotion effect estimation unit 110 has described the case where the introduction content with the highest local audience rating is the sales promotion content. However, the present invention is not limited to this, and the promotion content with the highest national audience rating is promoted. It may be content.
Next, the sales promotion effect estimation part 110 acquires the introduction content specific information of the sales promotion content (ST302).

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 according to the first embodiment calculating the coefficient indicating the sales promotion effect in ST305 of FIG.
The coefficient indicating the sales promotion effect is obtained by multiplying, for example, a regional audience rating influence coefficient, an exposure viewing time influence coefficient, a daytime audience rating influence coefficient, a holiday audience rating influence coefficient, a POP influence coefficient, another content influence coefficient, and the like. Is a coefficient.
Details of the local audience rating influence coefficient, the exposure time duration influence coefficient, the daytime audience rating influence coefficient, the holiday audience rating influence coefficient, the POP influence coefficient, and the other content influence coefficient will be described below. In the following description, the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculation unit 107 shown in FIG.

First, the sales promotion effect estimation unit 110 calculates a local audience rating influence coefficient. The regional audience rating influence coefficient is, for example, a coefficient obtained by multiplying a value obtained by dividing the local audience rating of the promotional content by the above-mentioned expected audience rating that is user input information and a predetermined weight. .
Therefore, the regional audience rating influence coefficient is a value indicating that the sales promotion effect is larger if the actual audience rating is larger than the audience rating expected by the mass media. The predetermined weight is, for example, 0.8. The predetermined weight may be determined in advance or may be set later by the user. When the regional audience rating influence coefficient is expressed as k1, k1 is expressed by the following equation (1).

K1 = ((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 to the present, and counts the number of positive tweets and the number of negative tweets. It is a coefficient obtained by multiplying a value obtained by dividing the number by the number of negative tweets and a predetermined weight.
Assuming that the site influence coefficient is k11, k11 is expressed by the following equation (2). Note that 1 is added to the numerator and denominator, for example, to prevent k11 from becoming zero or impossible to calculate when the number of tweets is zero.

K11 = (number of positive tweets + 1) / (number of negative tweets + 1) (2)

Next, the sales promotion effect estimation unit 110 calculates a viewing time influence coefficient during exposure. The viewing time influence coefficient at the time of exposure is, for example, the total viewing time for the sales promotion content of the person who was watching the sales promotion content during the time when the store product introduced in the sales promotion content appears in the sales promotion content. It is a coefficient obtained by dividing by the average viewing time of the person who was watching the whole and multiplying the divided value by a predetermined weight. Assuming that the exposure time influence coefficient during exposure is k2, k2 is expressed by the following equation (3).

K2 = ((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), sales promotion effect estimating section 110 transitions to ST404. When the current day is a holiday (ST403-Yes), sales promotion effect estimating section 110 transitions to ST405.
In ST403, when the present is not a holiday, sales promotion effect estimating section 110 calculates a daytime audience rating influence coefficient (ST404). The daytime audience rating influence coefficient is obtained, for example, by dividing the average audience rating of all contents broadcast during the daytime by the average audience rating of all contents broadcast during a predetermined period. This is a coefficient obtained by multiplying the obtained value by a predetermined weight.
When the daytime audience rating influence coefficient is k3, k3 is expressed by the following equation (4).

K3 = ((average audience rating of all contents during the day) / (average audience rating of all contents broadcast during a given 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 coefficient is obtained, for example, by adding the average audience rating of all contents broadcast in the midnight hours and the average audience rating of all contents broadcast in the morning on Saturday. It is a coefficient obtained by dividing the obtained value by the average audience rating of all contents broadcast during a predetermined period and multiplying the value obtained by the division by a predetermined weight.
When the holiday audience rating influence coefficient is k4, k4 is expressed by the following equation (5).

k4 = (((average audience rating of all contents in the midnight) + (average audience rating of all contents on Saturday morning)) / (average audience rating of all contents broadcast in a predetermined period)) × (predetermined Weight) (5)

Next, the sales promotion effect estimation unit 110 calculates a POP influence coefficient (ST406). The POP influence coefficient is a coefficient representing a sales promotion effect that occurs when the POP is used. The POP influence coefficient is obtained by, for example, dividing the local audience rating of the content used in creating the POP by the average audience rating of all the contents broadcast during a predetermined period, and adding a predetermined weight to the value obtained by the division. This is a coefficient obtained by multiplication.
Assuming that the POP influence coefficient is k5, k5 is expressed by the following equation (6).

K5 = ((regional audience rating of the content used when creating the POP) / (average audience rating of all content broadcast during a given period)) × (predetermined weight) (6)

Next, the sales promotion effect estimation unit 110 calculates another content influence coefficient (ST407). The other content influence coefficient is, for example, a predetermined coefficient associated with a keyword introduced in content different from the sales promotion content (hereinafter referred to as other content) or a time when the sales promotion content is broadcast.

FIG. 17 is an example of a keyword table showing a list of predetermined coefficients associated with keywords related to store merchandise in the first embodiment.
As shown in FIG. 17, in the keyword table t1101, for example, a keyword of Christmas is associated with a time of December 24 before strawberry.
The sales promotion effect estimation unit 110 acquires keywords related to the store product introduced in the sales promotion content by the natural language analysis from the content information server 9.

For each acquired keyword, the sales promotion effect estimation unit 110 acquires the content introducing the acquired keyword from the content information server 9 and acquires the viewing log of the acquired content from the viewing log server 8.
The sales promotion effect estimation unit 110 calculates a national audience rating or a regional audience rating of the acquired content based on the acquired viewing log, and selects a keyword introduced in the content with the highest audience rating.
The sales promotion effect estimation unit 110 calculates the other content influence coefficient as shown in the keyword table t1101 based on the selected keyword and the current time. In the first embodiment, the other content influence coefficient is calculated from Expression (1) based on the audience rating of the content associated with the selected keyword.
Hereinafter, the other content influence coefficient is represented by k6.

Next, the sales promotion effect estimation part 110 calculates the coefficient which shows the sales promotion effect, for example by adding the calculated various coefficients. Assuming that the coefficient indicating the sales promotion effect is k, for example, k when the current day is a weekday and the POP is used is expressed by the following equation (7).
When POP is not used, the POP influence coefficient k5 is excluded from the following equation (7). Further, when calculating the coefficient k indicating the sales promotion effect, each coefficient may be multiplied by a predetermined weight, for example. Further, the coefficient k indicating the sales promotion effect may be calculated by multiplying each coefficient.

K = k1 + k11 + k2 + k3 + k5 + k6 (7)

FIG. 18 is an example of a flowchart illustrating an operation in which the sales promotion effect information image generation unit 112 according to the first embodiment generates the sales promotion effect information image “img”.
First, the sales promotion effect information image generation part 112 acquires a suitable content audience rating table, suitable order quantity, and normal order quantity (ST500).
Next, the sales promotion effect information image generation unit 112 refers to the suitable content audience rating table and selects the introduction content having the highest local audience rating as the sales promotion content (ST501).
Next, the sales promotion effect information image generation part 112 acquires the introduction content specific information table t1051 of the sales promotion content (ST502).
Next, the sales promotion effect information image generation part 112 acquires the viewing log of the selected sales promotion content (ST503).

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. Here, a case where the predetermined format is set in advance in the sales promotion effect prediction server 4 for each image to be generated will be described. However, the present invention is not limited to this, and the user may be able to freely set later.
Hereinafter, the predetermined format when the sales promotion effect information image generation unit 112 generates each image is the vertical and horizontal widths of the image, background color, and character color for each image generated by the sales promotion effect information image generation unit 112. A case where a predetermined format such as is set in the sales promotion effect estimation server 4 in advance will be described.

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, the fluctuation of the cumulative viewing time within the same period as the fluctuation of the exposure time is exposed. An exposure time graph p6 is generated by superimposing the graph on the time variation graph.

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 having the top three places in the local audience rating from the preferred content audience rating table, and performs natural language analysis from the event content information corresponding to the extracted content. , Extract short text information representing the event. And the sales promotion effect information image generation part 112 produces | generates the introduction content content image p12 according to a predetermined format based on the extracted text information and the local audience rating of the corresponding introduction content.
Next, the sales promotion effect information image generation unit 112 generates the sales promotion effect information image “img” by arranging the various images generated in ST504 to ST515 in accordance with a predetermined format (ST515).

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 considered to have generality.
When a customer sees an advertisement using information of a television program (promotional content) installed in the store “Shp”, the customer performs the actions from ST600 to ST611. The customer sees the advertisement (ST600).
Next, the customer views the advertisement (ST601-program name) using the television program name (name of the promotional content) or the performer who introduced the promotional product that appeared in the promotional content (hereinafter referred to as the introduction person). Different actions are taken depending on whether the advertisement uses (referred to as ST601-introducing person).
When the viewed advertisement is an advertisement using the television program name in ST601, the customer's behavior transitions to ST602. When the viewed advertisement is an advertisement using an introduction person in ST601, the customer's behavior transitions to ST607.

Next, the customer's behavior is different depending on whether or not the television program is known (ST602). When the customer knows the television program (ST602-Yes), the customer transitions to ST603. When the customer does not know the television program (ST602-No), the customer transitions to ST606.
In ST602, when the user knows the television program, the customer's behavior is different depending on whether or not he / she was watching the television program (ST603). When the customer's behavior is watching a television program (ST603-Yes), the transition is made to ST604. When the customer's behavior is not watching the television program (ST603-No), the customer transitions to ST605.

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 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 considered that if the customer views the television program, the introduced store product is purchased with a higher probability.
Therefore, with the sales promotion effect estimation system 1 according to the first embodiment that uses the introduction content with the highest audience rating as the sales promotion content and calculates a suitable order quantity according to the audience rating of the sales promotion content, the user can carry out a more appropriate ordering operation. It can be carried out.

FIG. 20 is an example of a graph showing the relationship between the exposure time to the product content and the sales.
Specifically, FIG. 20 shows a histogram of the cumulative time in which the product A or the category (for example, product type) including the product A is introduced in the contents for each date, and the introduced product A It is the figure which showed in a line graph the change of the sales of this, and the change of the sales of the whole category.
As shown in FIG. 20, the sales of the product A and the sales of the entire category including the product A increase as the time (exposure time) for which the product A is introduced in the content increases. Such an increase in sales generally tends to occur in reality.
The sales promotion effect estimation system 1 uses the introductory content with the highest audience rating as the sales promotion content, and calculates the preferred order quantity according to the audience rating of the sales promotion content. Therefore, the sales order effect amount more appropriately reflects the sales promotion effect of the sales promotion content. calculate. Then, the user can perform more appropriate ordering work according to the calculated preferred order quantity.

In addition, although the sales promotion effect estimation system 1 demonstrated the case where the sales promotion effect information image was transmitted and displayed on the store apparatus 3 in the said 1st Embodiment, it is not restricted to this. The sales promotion effect estimation system 1 may, for example, send a sales promotion effect information image to a specific PC (Personal Computer) and display it, or send the sales promotion effect information image to a store manager or a person in charge of ordering by e-mail. Alternatively, a predetermined in-store broadcast may be broadcast.
In the first embodiment, the case where the sales promotion effect estimation system 1 includes only one store “Shp” has been described. However, the present invention is not limited to this, and a plurality of stores may be included. In that case, the sales promotion effect estimation server 4 may generate a suitable order quantity, a sales promotion effect information image, and the like for each store (in the case of the first embodiment).
Further, the sales promotion effect estimation server 4 may hold suitable order quantities and sales promotion effect information images generated for all stores, and the user may select information desired by the store device 3.
Further, the sales promotion effect estimation server 4 automatically distributes the preferred order quantity and the sales promotion effect information image generated for all the stores, and the preferred order quantity and the sales promotion effect information image associated with each store. You may make it do.

<Second Embodiment>
Hereinafter, the second embodiment will be described. About the structure of the sales promotion effect estimation system in 2nd Embodiment, FIG.1 and FIG.10 is used and the same code | symbol is attached | subjected and demonstrated about the same function part.
In the sales promotion effect estimation system 1 in the second embodiment, for example, the store apparatus 3 includes various functional units of the sales promotion effect estimation server 4 as the sales promotion effect estimation apparatus 11.

FIG. 21 is a diagram illustrating a usage situation of the sales promotion effect estimation system 1 according to the second embodiment. The sales promotion effect estimation device 11 displays an order screen “order” on the display of the sales promotion effect estimation device 11 based on the calculated preferred order quantity.
Moreover, the sales promotion effect estimation apparatus 11 displays the produced sales promotion effect information image on the display of the sales promotion effect estimation apparatus 11 by operation from a user. Further, the sales promotion effect estimation device 11 outputs and displays an alert image “alrt” on the handy terminal 2 when the audience rating of the sales promotion content exceeds a predetermined threshold.

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

<Third Embodiment>
Hereinafter, a third embodiment will be described. About the structure of the sales promotion effect estimation system in 3rd Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 and the preferred order quantity calculation unit 116 of the sales promotion effect estimation server 4 according to the third embodiment are configured such that when the store apparatus 3 generates an alert image and outputs the alert image to the handy terminal 2 Only when the predetermined threshold value used for the sales is exceeded, the coefficient indicating the sales promotion effect and the preferred order quantity are calculated. When the predetermined threshold value is not exceeded, the normal order quantity is set as the preferred order quantity and the store apparatus 3 and the sales promotion effect information The image is output to the image generation unit 112.

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 the structure of the sales promotion effect estimation system in 4th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 of the sales promotion effect estimation system 1 according to the fourth embodiment are configured to introduce content that is a candidate for sales promotion content broadcasted in a past predetermined period (for example, 3 days). On the other hand, based on the viewing time of consumers who watched the introductory content and the elapsed time since the introductory content was broadcast, an appropriate score indicating the level of consumer interest in the promotional product was calculated. To do.
The sales promotion effect estimation unit 110 and the sales promotion effect information image generation unit 112 select the sales promotion content from the introduction content according to the calculated appropriate score.

FIG. 22 is a conceptual diagram for explaining a method for calculating an appropriate score in the fourth embodiment.
The sales promotion effect estimation unit 110 calculates an appropriate score using FIG. In FIG. 22, the event content information type is information that categorizes how products are introduced.
The event content information type is, for example, information A if the information obtained by natural language analysis of the event content information is delicious if the food is eaten as it is, if the promotional product is food. If it is information that it is good for health, it becomes information B, and if it is information that the food is not delicious, it becomes information C.

The broadcast end time represents the broadcast end time of each introduction content. The viewing time by the first to fourth viewers represents the time of viewing each introduction content of each of the first to fourth viewers. The content-specific weighting coefficient is an index representing the degree of influence on the sales promotion effect assigned to the event content information type of each introduction content.
The sales promotion effect estimation unit 110 performs natural language analysis on the event content information of the introduction content, and assigns a predetermined weighting coefficient to the introduction content as a weighting coefficient for each content based on the strength of the relevance to the viewer's willingness to purchase. . Specifically, for example, if the sales promotion effect estimation unit 110 determines that it is a late night laughing content as a result of the natural language analysis of the introduction content “vvv”, the weighting coefficient is 0.5.

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 FIG. 22, there are only four viewers, the first to fourth viewers, but this is an example.
For example, for the introductory content “xxx”, the appropriate score is calculated as follows: the total viewing time of the first to fourth viewers is 320 seconds, the weighting factor by content is 1, and the weighting by elapsed time is Since the coefficient is 0.82, the appropriate score is expressed by the following equation (9) and is 262.

320 × 1 × 0.82 ≒ 262 ... (9)

For example, the sales promotion effect estimation unit 110 calculates an appropriate score for all the introduction contents in the past three days, and calculates a total score for each event content information type. In FIG. 22, the total appropriate score of the information A is 298.9 points because it is the total correct score of the two contents of the introduction contents “xxx” and “vvv”.
Similarly, the total appropriate score for information B is 160 points, and the total proper score for information C is 36.5 points. The sales promotion effect estimation unit 110 selects the sales promotion content from the introduction content corresponding to the event content information type that is the sum of the highest appropriate scores.
In FIG. 22, since information A has the highest appropriate score, either “xxx” or “vvv”, which is the introduction content of information A, is selected as the sales promotion content. The sales promotion effect estimation unit 110 selects the introduction content having the highest appropriate score as the sales promotion content from the introduction content of the introduction content specific information type that is the sum of the highest appropriate scores.
Note that the processing related to the appropriate score of the sales promotion effect information image generation unit 112 is the same as that of the sales promotion effect estimation unit 110, and thus detailed description thereof is omitted.

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

<Fifth Embodiment>
The fifth embodiment will be described below. About the structure of the sales promotion effect estimation system in 5th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 according to the fifth embodiment is based on content information of other content (hereinafter referred to as correlation content) having a high degree of commonality between the viewer of the sales promotion content and the viewer, and the other content influence coefficient k6. The keyword for calculating is extracted. In the fifth embodiment, in order to simplify the description, the sales promotion product is food. However, the present invention is not limited to this, and may be clothing, electrical appliances, or the like.

FIG. 23 is a conceptual diagram for explaining selection of correlated content in the fifth embodiment. The sales promotion effect estimation unit 110 selects correlated content using FIG. FIG. 23 shows information in which a viewing pattern indicating whether or not each content is viewed is associated with the number of television receivers.
In the second line of FIG. 23, all viewing situations of the contents 1 to 3 are “viewing”. The rightmost column in FIG. 23 displays the number of views for each viewing situation. Therefore, the number of views for each viewing situation in the rightmost column of the second row in FIG. 23 represents the number of television receivers that have viewed all of the contents 1 to 3. In the case of the third row in FIG. 23, the number of views for each viewing situation in the rightmost column is the number of television receivers that have both viewed content 1 and content 2 but have not viewed content 3. The bottom line in FIG. 23 displays the total number of television receivers viewed for each content.

For example, the sales promotion effect estimation unit 110 sets the content 1 as the content with the highest audience rating that introduced the promotional product in the past 3 days, and the content 2 as the sales product with the highest national audience rating after the content 1 in the past 3 days. Is the content introduced. Then, for example, the sales promotion effect estimation unit 110 sets the content 3 as content that introduces food (hereinafter referred to as related food) that is used for cooking in association with the sales promotion product in the past three days. For example, if the promotional product is “mochi”, the related food is fresh cream or flour used in the roll cake when the roll cake using mochi is introduced.

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, for example, is a content that introduces the candy “Amaio” as the content 1, the content 2 is the content that introduces the ranking of the candy, and the content 3 is fresh cream (the above-mentioned related food). In the case of the introduced content, the other content candidates that are the keyword extraction source for calculating the other content influence coefficient k6 are the content 2 and the content 3. The sales promotion effect estimation unit 110 sets the content of the content 2 and the content 3 that has been viewed together with the content 1 as the extraction source content.
Specifically, in the case of FIG. 23, the total number of viewings of content 1 is 100, and the number of viewings of content 2 but not viewing of content 1 is 20; The number of contents 3 that have not been viewed is 45.
The number N12 of viewing either the content 1 or the content 2 is expressed by the following equation (10). Further, the number N13 of viewing either the content 1 or the content 3 is expressed by the following equation (11).

N12 = 100 + 20 = 120 (units) ... (10)

N13 = 100 + 45 = 145 (unit) ... (11)

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

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

<Sixth Embodiment>
The sixth embodiment will be described below. About the structure of the sales promotion effect estimation system in 6th Embodiment, FIG.1 and FIG.10 is used and it attaches | subjects and demonstrates the same code | symbol with respect to the same function part.
The sales promotion effect estimation unit 110 in the sixth embodiment uses the expected audience rating used when calculating the regional audience rating influence coefficient k1, for example, before the previous time when the broadcasted promotional content is regularly broadcast. Calculated based on the audience rating of the broadcast. Therefore, the sales promotion effect estimation server 4 in the sixth embodiment may omit the user input information reception unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.

The sales promotion effect estimation unit 110 calculates, for example, the average audience rating of the promotional content broadcast one week ago as the expected audience rating. Since the audience rating calculation process is the same as the audience rating calculation process of the audience rating calculator 107 shown in FIG. 14, detailed description thereof is omitted.

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 the structure of the sales promotion effect estimation system in 7th Embodiment, FIG.1 and FIG.10 is used and the same code | symbol is attached | subjected and demonstrated about the same function part.
The sales promotion effect estimation unit 110 according to the seventh embodiment predicts the expected audience rating used when the regional audience rating influence coefficient k1 is calculated by the mass media and the like by registering the expected audience ratings of various contents. Obtained from the audience rating server. Therefore, the sales promotion effect estimation server 4 in the seventh embodiment may omit the user input information receiving unit 114 and the user input information storage unit 115 that receive the expected audience rating as user input information.

FIG. 24 is a diagram showing a usage situation of the sales promotion effect estimation system 1 in the seventh embodiment.

The sales promotion effect estimation system 1 in the seventh embodiment is the same as the sales promotion effect estimation system 1, the handy terminal 2, the store apparatus 3, the sales promotion effect estimation server 4, the store product server 5, the store product supplement server 6, the POS server 7, viewing A log server 8, a content information server 9, a content recording server 10, and an expected audience rating providing server 12 are included.

The expected audience rating providing server 12 stores the expected audience ratings for various contents provided by mass media and the like. The expected audience rating providing server 12 is communicably connected to the sales promotion effect estimating server 4 via the NW.
The sales promotion effect estimation unit 110 of the sales promotion effect estimation server 4 in the seventh embodiment acquires the expected audience rating from the expected audience rating providing server 12 in order to calculate the regional audience rating influence coefficient k1.

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.

As mentioned above, although each embodiment of this invention has been described in detail with reference to the drawings, the specific configuration is not limited to each of these embodiments, and changes and substitutions are made without departing from the gist of this invention. , May be deleted.

Moreover, the program for implement | achieving the function of each part which comprises the sales promotion effect estimation system 1 in FIG.1, FIG.10, FIG.21 is recorded on a computer-readable recording medium, The program recorded on this recording medium is recorded. The sales promotion effect estimation system 1 may be implemented by being read and executed by a computer system. The “computer system” here includes an OS (Operation System) and hardware such as peripheral devices.

Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW (World Wide Web) system is used.
The “computer-readable recording medium” means a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), a CD (Compact Disk) -ROM, or a hard disk built in a computer system. Refers to the device. Furthermore, the “computer-readable recording medium” is a medium that dynamically holds a program for a short time, such as a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line, In this case, it also includes those that hold a program for a certain period of time, such as a volatile memory inside a computer system serving as a server or client. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

(Additional remark 1) The 1st aspect of this invention is content content information which described the content of the broadcast content, Comprising: The event generation period which shows the period in which the event which is at least one part in a program has generate | occur | produced, and the said The content related information including information related to the product related to the event and content information indicating the content is referenced, the content related to the event occurrence period is identified based on the information related to the product, and the content related to the identified event occurrence period Viewing history information of the content to be obtained, reading correspondence information associating the viewing history information with the estimated value from the storage unit, and based on the obtained viewing history information, the content played by the content related to the event occurrence period It is a sales promotion effect estimation method which calculates the said estimated value which shows the effect which promotes sales.

(Additional remark 2) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: For each store, the information which makes the store product which can be handled in the said store is acquired, and event occurrence period based on the information regarding the said store product It is good also as a sales promotion effect estimation method which specifies the content relevant to, and calculates the said estimated value used for calculation of the demand amount of the said store goods.

(Additional remark 3) It is the sales promotion effect estimation method as described in the above (Appendix 1), and is an effect exhibited when content related to the event occurrence period is used in a store, and an effect of promoting the sale of the product. It is good also as a sales promotion effect estimation method which calculates the said estimated value which shows.

(Additional remark 4) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The said correspondence information is related with the case where the content relevant to the said event occurrence period is used in a store, and the said event occurrence period in a store When the content to be used is not used, the estimated value used for calculating the demand amount when the content related to the event occurrence period is used at the store and the content related to the event occurrence period are used at the store It is good also as a sales promotion effect estimation method which calculates the said estimated value used for calculation of the demand amount when not being performed.

(Additional remark 5) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The local viewing degree information which shows the viewing degree in the area including a store is acquired, Based on the acquired local viewing degree information, the said store It is good also as a sales promotion effect estimation method which calculates the said estimated value provided to.

(Appendix 6) The sales promotion effect estimation method according to (Appendix 1), wherein the viewing history information of each playback device that plays back the broadcasted content is acquired, and an event occurrence period is obtained based on the viewing history information. It is good also as a sales promotion effect estimation method which calculates the viewing time of a related content, and calculates the said estimated value based on the calculated viewing time.

(Supplementary note 7) The sales promotion effect estimation method according to (Appendix 1) above, wherein the viewing history information of each playback device that plays back the broadcasted content is acquired, and an event occurrence period is obtained based on the viewing history information. Among the related contents, a sales promotion effect estimation method may be used in which the viewing time of content in a time zone in which information related to the product appears is calculated, and the estimated value is calculated based on the calculated viewing time.

(Additional remark 8) It is the sales promotion effect estimation method as described in the above (Appendix 1), Comprising: The said estimated value is calculated based on the information which shows the viewing-and-listening degree of the content relevant to the said event occurrence period utilized in a store. It is good also as a sales promotion effect estimation method.

(Additional remark 9) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: The reference value for calculating the said estimated value is acquired, The value of the acquired said viewing history information, The said acquired reference value, It is good also as a sales promotion effect estimation method which calculates the said estimated value based on.

(Additional remark 10) It is good also as a sales promotion effect estimation method as described in the above (Appendix 9), Comprising: The numerical value input from a user is received and the received numerical value is acquired as said reference value.

(Additional remark 11) It is the sales promotion effect estimation method as described in said (Appendix 9), Comprising: The value which estimated the viewing degree of the said broadcast content is calculated, The value which estimated the said viewing degree calculated is the said reference value It is good also as a sales promotion effect estimation method acquired as follows.

(Supplementary Note 12) In the sales promotion effect estimation method described in (Appendix 11) above, the reference value is calculated based on viewing history information of the previous broadcast when the broadcasted content is regularly broadcast. It is good also as a sales promotion effect estimation method to calculate.

(Supplementary note 13) The sales promotion effect estimation method described in (Appendix 9), wherein the expected viewing history information predicted before the content including the information related to the product is broadcast is used as the reference value. It is good also as a sales promotion effect estimation method acquired from an external server.

(Supplementary Note 14) The sales promotion effect estimation method described in (Appendix 1) above, which is information provided by a web server reflecting a user operation and related to content including information related to the product. It is good also as a sales promotion effect estimation method which calculates the said estimated value based on information.

(Supplementary Note 15) The sales promotion effect estimation method described in (Appendix 1) above, wherein correspondence information that associates a time with an estimated value is read from a storage unit, and is based on a time when content including information about the product is broadcast Thus, it may be a sales promotion effect estimation method for calculating the estimated value.

(Supplementary Note 16) The sales promotion effect estimation method according to (Appendix 1), wherein the acquired viewing history information determines whether or not a set condition is satisfied, and based on the determination result, the demand for the product It is good also as a sales promotion effect estimation method which outputs the information which prompts adjustment of quantity.

(Additional remark 17) It is the sales promotion effect estimation method as described in said (Appendix 1), Comprising: It determines whether the said estimated value satisfy | fills setting conditions, and adjusts the demand amount of the said goods based on the said determination result It is good also as a sales promotion effect estimation method which outputs the information which prompts.

(Supplementary note 18) The sales promotion effect estimation method according to (Appendix 17), wherein the estimation value is calculated when it is determined that the determination result satisfies the setting condition. .

(Supplementary note 19) The sales promotion effect estimation method according to (Appendix 16), which is a product different from a product that outputs information that prompts adjustment of the demand amount, and outputs information that prompts adjustment of the demand amount It is good also as a sales promotion effect estimation method which outputs together the information which demands adjustment of the demand amount of the goods relevant to the goods to do.

(Additional remark 20) It is a sales promotion effect estimation method as described in the above (Appendix 1), Comprising: It is good also as a sales promotion effect estimation method which calculates the demand amount of the said goods based on the said estimation result.

(Appendix 21) The sales promotion effect estimation method according to (Appendix 1), wherein the sales promotion effect estimation method generates an image including information based on the estimation result and content information including information related to the product. It is good also as an effect estimation method.

(Supplementary Note 22) The sales promotion effect estimation method described in (Appendix 20), wherein the product is ordered based on the calculated demand amount.

(Additional remark 23) It is good also as a sales promotion effect estimation method as described in the above (Appendix 1), Comprising: The order quantity input from a user is received and goods are ordered with the received order quantity.

(Additional remark 24) It is good also as a sales promotion effect estimation method as described in the above (Appendix 1) and outputting the information based on the order according to the said estimated value.

(Supplementary Note 25) The sales promotion effect estimation method according to (Appendix 1), wherein the product is ranked according to the estimated value, and information indicating the ranking is output. .

(Supplementary note 26) The sales promotion effect estimation method according to (Appendix 1), wherein the estimation value is calculated based on a time during which the product is handled in the content related to the event occurrence period. An estimation method may be used.

(Supplementary note 27) The sales promotion effect estimation method according to (Appendix 1), wherein the estimation value is calculated based on information indicating the broadcast time of content related to the event occurrence period. Also good.

(Additional remark 28) The 2nd aspect of this invention is the content content information which described the content of the broadcast content, Comprising: The event generation | occurrence | production period which shows the period in which the event which is at least one part in a program has generate | occur | produced, and the said A specific unit that identifies content related to an event occurrence period based on information related to a product by referring to content content information including information related to a product related to an event and content information indicating content, and the specified event occurrence An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content A promotion effect estimation device comprising a.

(Supplementary Note 29) The third aspect of the present invention is content content information describing the content of broadcast content, and an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, and the event occurrence period A specific unit that identifies content related to an event occurrence period based on information related to a product by referring to content content information including information related to a product related to an event and content information indicating content, and the specified event occurrence An acquisition unit that acquires viewing history information of content related to a period, and correspondence information that associates the viewing history information with an estimated value are read from the storage unit, and the event generation period is related based on the acquired viewing history information An estimation unit that calculates the estimated value indicating the effect of promoting the sale of the product played by the content A promotion effect estimation system and a display unit for displaying the demand amount calculated based on the estimated value.

(Additional remark 30) The 4th aspect of this invention is the content generation | occurrence | production information which described the content of the content broadcast on the computer, Comprising: The event generation | occurrence | production which shows the period when the event which is at least one part in a program has generate | occur | produced The content occurrence information including the period and information related to the product related to the event and the content information indicating the content are referred to, the content related to the event occurrence period is specified based on the information related to the product, and the specified event occurrence Content related to the event occurrence period is obtained by acquiring viewing history information of content related to the period, reading correspondence information associating the viewing history information with the estimated value from the storage unit, and based on the acquired viewing history information Calculate the estimated value indicating the effect of promoting the sale of the product played by A computer-readable recording medium recording a program for.

One embodiment of the present invention can be applied to a sales promotion effect estimation device that can more appropriately estimate the sales promotion effect of content including information related to a product.

DESCRIPTION OF SYMBOLS 1 ... Sales promotion effect estimation system 2 ... Handy terminal 3 ... Store apparatus 4 ... Sales promotion effect estimation server 5 ... Store product server 6 ... Store product supplement server 7 ... POS server 8 ... viewing log server 9 ... content information server 10 ... content recording server 11 ... promotion effect estimation device 12 ... expected audience rating providing server 101 ... communication unit 102 ... store product acquisition Section 104: Product supplement information acquisition section 105 ... Introduction content specific information acquisition section 106 ... Introduction content specific information storage section 107 ... Audience rating calculation section 108 ... Suitable content selection section 110 ... Preferred order quantity calculation unit 111 ... Normal order quantity acquisition unit 112 ... Sales promotion effect information image generation unit 113 ... Sales promotion effect Broadcast image storage unit 114 ... user input information reception unit 115 ... user input information storage unit 116 ... promotional effect estimator

Claims

Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content Information and content content information that includes information, identify content related to the event occurrence period based on information about the product,
Obtaining viewing history information of content related to the identified event occurrence period;
Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information To calculate,
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
For each store, obtain information on the store product that can be handled in the store, identify content related to the event occurrence period based on the information about the store product,
Calculating the estimated value used to calculate the demand for the store product;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Calculating the estimated value indicating the effect of promoting the sale of the product, which is an effect exhibited when content related to the event occurrence period is used in a store;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
The correspondence information is different when content related to the event occurrence period is used at a store and when content related to the event occurrence period is not used at a store,
Used to calculate the demand when the content related to the event occurrence period is used in the store, and to calculate the demand when the content related to the event occurrence period is not used in the store Calculating the estimated value;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Get local viewing level information showing the level of viewing in the area including the store,
Based on the acquired regional viewing degree information, the estimated value provided to the store is calculated.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Obtaining the viewing history information of each playback device that plays the broadcast content;
Calculating the viewing time of content related to the event occurrence period based on the viewing history information, and calculating the estimated value based on the calculated viewing time;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Obtaining the viewing history information of each playback device that plays the broadcast content;
Of the content related to the event occurrence period based on the viewing history information, the viewing time of the content in the time zone in which the information related to the product appears is calculated, and the estimated value is calculated based on the calculated viewing time ,
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Calculating the estimated value based on information indicating the degree of viewing of content related to the event occurrence period used in the store;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Obtaining a reference value for calculating the estimated value;
Calculating the estimated value based on the acquired viewing history information value and the acquired reference value;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 9,
Receiving an input of a numerical value from a user, and acquiring the received numerical value as the reference value;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 9,
Calculate a value that predicts the viewing level of the broadcasted content,
Obtaining a value that predicts the calculated degree of viewing as the reference value;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 11,
Based on the viewing history information of the previous broadcast when the broadcast content is regularly broadcast, the reference value is calculated.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 9,
Obtaining the expected viewing history information predicted before the content including information related to the product is broadcast from the external server as the reference value,
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Calculating the estimated value based on information provided by a web server reflecting a user operation and related to content including information related to the product;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Correspondence information that associates the estimated value with the time is read from the storage unit, and the estimated value is calculated based on the time when the content including the information related to the product is broadcast.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
It is determined whether the acquired viewing history information satisfies a setting condition,
Based on the determination result, information that prompts adjustment of the demand amount of the product is output.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Determining whether the estimated value satisfies a setting condition;
Based on the determination result, information that prompts adjustment of the demand amount of the product is output.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 17,
When it is determined that the determination result satisfies the setting condition, the estimated value is calculated.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 16,
The product that is different from the product that outputs the information that prompts the adjustment of the demand amount and that outputs information that prompts the adjustment of the demand amount of the product related to the product that outputs the information that prompts the adjustment of the demand amount.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Based on the estimation result, a demand amount of the product is calculated.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Generating an image including information based on the estimation result and content information including information related to the product;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 20,
Order the product based on the calculated demand.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Accepts order quantity input from users,
Order products with the accepted order quantity,
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Outputting information based on the order according to the estimated value;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
In accordance with the estimated value, the products are ranked, and information indicating the ranking is output.
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Calculating the estimated value based on the time the product is handled in the content related to the event occurrence period;
Promotional effect estimation method.
The sales promotion effect estimation method according to claim 1,
Calculating the estimated value based on information indicating the broadcast time of the content related to the event occurrence period;
Promotional effect estimation method.
Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content A specific unit that identifies content related to the event occurrence period based on information about the product, referring to content content information including information,
An acquisition unit for acquiring viewing history information of content related to the specified event occurrence period;
Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information An estimator for calculating
A sales promotion effect estimation device.
Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content A specific unit that identifies content related to the event occurrence period based on information about the product, referring to content content information including information,
An acquisition unit for acquiring viewing history information of content related to the specified event occurrence period;
Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the estimated value indicating an effect of promoting the sale of the product played by the content related to the event occurrence period based on the acquired viewing history information An estimator for calculating
A display unit for displaying the demand amount calculated based on the estimated value;
Promotional effect estimation system with
On the computer,
Content content information describing the content of the broadcast content, an event occurrence period indicating a period in which an event that is at least a part of the program is occurring, information relating to a product related to the event, and content indicating the content Information, and content content information including information is used to identify content related to the event occurrence period based on information about the product,
Obtaining viewing history information of content related to the specified event occurrence period;
Correspondence information that associates the viewing history information with an estimated value is read from a storage unit, and the effect of promoting the sale of the product played by the content related to the event occurrence period is based on the acquired viewing history information Let the estimate be calculated,
A computer-readable recording medium on which a program for recording is recorded.