Policy formulation support system, policy formulation support method, and program

Abstract

To provide a policy formulation support system, a method for supporting policy formulation, and a program that enable even an inexperienced person to easily formulate a policy.SOLUTION: The policy formulation support system includes: a request information acquisition unit for acquiring request information indicating a request of a user for a policy for sales promotion; a policy estimation unit for estimating a policy satisfying the request of the user indicated by the acquired request information on the basis of the relationship among policies implemented in the past, information indicating factors affecting formulation of the policies, and sales promotion performance resulting from implementation of the policies; and a policy output unit for outputting candidates of a policy satisfying the request of the user on the basis of the result of policy estimation.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a policy formulation support system, a policy formulation support method, and a program. [Background technology]

[0002] Traditionally, sales promotion measures have often been formulated by experienced personnel. For example, in the case of sales promotion at a retail store, personnel with extensive experience in retail store operations can formulate measures based on their past experience and issue instructions to others.

[0003] The following Patent Document 1 discloses a technology for supporting sales promotion activities in stores. With this technology, for example, data related to sales promotion measures formulated at a headquarters is packaged and sent to the computers of stores that carry out sales promotion activities within the organization, thereby enabling efficient and reliable sales promotion activities to be carried out. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-109185 Summary of the Invention [Problem to be solved by the invention]

[0005] However, if there are no experienced personnel at the policy formulation stage, the formulation of the policy itself becomes difficult. For this reason, it takes a considerable amount of time and experience to develop personnel who can gain experience and formulate effective policies.

[0006] In view of the above-mentioned problems, an object of the present invention is to provide a policy formulation support system, a policy formulation support method, and a program that enable even inexperienced people to easily formulate policies. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, one embodiment of the present invention provides a policy formulation support system that includes a request information acquisition unit that acquires request information indicating user requests for sales promotion measures, a policy estimation unit that estimates measures that will satisfy the user requests indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and the sales promotion results resulting from the implementation of the measures, and a policy output unit that outputs candidate measures that will satisfy the user requests based on the estimated results of the measures.

[0008] A policy formulation support method according to one embodiment of the present invention is a policy formulation support method executed by a computer, including a request information acquisition process for acquiring request information indicating user requests for sales promotion measures; a policy estimation process for estimating measures that will satisfy the user requests indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and sales promotion results due to the implementation of the measures; and a policy output process for outputting candidate measures that will satisfy the user requests based on the results of the estimated measures.

[0009] A program according to one aspect of the present invention causes a computer to function as: a request information acquisition means for acquiring request information indicating user requests for sales promotion measures; a measure estimation means for estimating measures that will satisfy the user requests indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors influencing the formulation of the measures, and the sales promotion results resulting from the implementation of the measures; and a measure output means for outputting candidate measures that will satisfy the user requests based on the results of the measure estimation. [Effects of the Invention]

[0010] According to the present invention, even an inexperienced person can easily formulate a policy. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of a configuration of a policy formulation support system according to an embodiment of the present invention. [Figure 2] 1 is a block diagram illustrating an example of a functional configuration of a policy formulation learning device according to an embodiment of the present invention. [Figure 3] 1 is a block diagram illustrating an example of a functional configuration of a policy formulation support device according to an embodiment of the present invention. [Figure 4] FIG. 10 is a sequence diagram illustrating an example of the flow of a policy learning process according to the present embodiment. [Figure 5] FIG. 10 is a sequence diagram illustrating an example of the flow of a policy formulation process according to the present embodiment. [Figure 6] FIG. 10 is a diagram illustrating an example of an example in which a user according to the present embodiment is a store staff member. [Figure 7] FIG. 10 is a diagram illustrating an example of an example in which a user according to the present embodiment is a person in charge at headquarters. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0013] <1. Structure of the policy formulation support system> The configuration of a policy formulation support system according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of a policy formulation support system according to this embodiment.

[0014] The policy formulation support system 1 shown in Fig. 1 is a system for supporting the formulation of policies for sales promotion. The policy formulation support system 1 supports the formulation of policies by the user by estimating policies that will satisfy the needs of the user (person in charge) based on the relationships between multiple pieces of information that affect the formulation of the policies and outputting candidate policies. The policy formulation support system 1 estimates policies based on the results of learning (machine learning) about the relationships between multiple pieces of information that affect the formulation of the policies, for example, using AI (Artificial Intelligence).

[0015] The multiple pieces of information that influence the formulation of measures include, for example, information on measure results, factor information, and sales promotion results information. Using this information, AI can learn what factors influenced what measures were implemented and what sales promotion results were obtained. For example, AI can analyze the factors that caused sales increases or decreases due to measures through learning. This enables AI to propose measures that will increase sales and not propose measures that will decrease sales.

[0016] The policy performance information is information indicating policies that have been implemented in the past. Examples of policies include promotions tailored to the customer demographic, changes to product shelf allocations (such as placement positions and number of faces), changes to the display of electronic shelf tags, and changes to the size of electronic shelf tags.

[0017] The factor information is information indicating factors that affect the formulation of a policy, and includes, for example, product information, sales environment information, and external factor information.

[0018] Product information is information about the product that is the target of the campaign. Product information includes, for example, the JAN (Japanese Article Number) code, product name, manufacturer name, specifications, and price. The JAN code is an example of product identification information, and is information unique to each product.

[0019] The sales environment information is information about the sales environment of a product, and includes, for example, electronic shelf label information, shelf allocation information, and the like.

[0020] The electronic shelf label information is information relating to electronic shelf labels that are installed in stores and display product information about products. The electronic shelf label information includes, for example, identification information of the electronic shelf label, information relating to the installation of the electronic shelf label, and information relating to the display of the electronic shelf label.

[0021] Shelf allocation information is information relating to the allocation of products. The shelf allocation information includes, for example, information such as the location of shelves set in a store, the shelves on which each product is placed, the position of the product on the shelf, and the number of faces of the product. Note that the shelf allocation information may differ depending on the store.

[0022] External factor information is information about external factors. For example, external factors are information about events outside the store that affect product sales in the store. Examples of external factors include weather, posts on social networking services (SNS), manufacturer campaigns, and media exposure.

[0023] Sales promotion performance information is information that indicates the sales promotion performance as a result of the implementation of a campaign. Sales promotion performance information includes, for example, sales information, customer attribute information, and inventory information. Sales information is information that indicates the sales performance as a result of the implementation of a campaign. Customer attribute information is information that indicates the attributes of customers who visit a store as a result of the implementation of a campaign. Inventory information is information that indicates changes in inventory as a result of the implementation of a campaign.

[0024] A user can obtain estimated results of candidate measures from the policy formulation support system 1 by inputting a request for a policy to the policy formulation support system 1. The user can formulate a policy by simply selecting a policy from the candidate measures obtained from the policy formulation support system 1. Thus, by using the policy formulation support system 1, even an inexperienced user can easily formulate a policy by simply inputting a request.

[0025] As shown in FIG. 1, the policy development support system 1 includes an administrator terminal 10, a user terminal 20, a sales management system 30, an electronic shelf label management system 40, an external factor system 50, a policy development learning device 60, and a policy development support device 70. The network NW may be configured to transmit and receive information using, for example, a LAN (Local Area Network), a WAN (Wide Area Network), a telephone network (such as a mobile phone network or a fixed telephone network), a regional IP (Internet Protocol) network, or the Internet.

[0026] (1) Administrator terminal 10 The administrator terminal 10 is a terminal operated by an administrator (business operator) to manage the policy development support system 1. The administrator terminal 10 is, for example, a smartphone, a tablet terminal, a PC (Personal Computer), a dedicated handheld terminal, etc. The administrator terminal 10 is communicably connected to the sales management system 30, the electronic shelf label management system 40, the external factor system 50, the policy development learning device 60, and the policy development support device 70 via the network NW.

[0027] In communication with the sales management system 30, the administrator terminal 10 transmits a request for linking learning data. The administrator operates the administrator terminal 10 to select information to be used as learning data from the information managed by the sales management system 30. After the selection, the administrator operates the administrator terminal 10 to transmit a linking request to the sales management system 30 to link the selected information to the policy formulation learning device 60 as learning data.

[0028] In communication with the electronic shelf label management system 40, the manager terminal 10 transmits a request for linking learning data. The manager operates the manager terminal 10 to select information to be used as learning data from the information managed by the electronic shelf label management system 40. After the selection, the manager operates the manager terminal 10 to transmit a linking request to the electronic shelf label management system 40 to link the selected information to the policy formulation learning device 60 as learning data.

[0029] In communication with the external factor system 50, the administrator terminal 10 transmits a request for linking learning data. The administrator operates the administrator terminal 10 to select information to be used as learning data from the information managed by the external factor system 50. After the selection, the administrator operates the administrator terminal 10 to transmit a linking request to the external factor system 50 to link the selected information to the policy formulation learning device 60 as learning data.

[0030] In communication with the policy formulation learning device 60, the administrator terminal 10 transmits a request for generating (learning) a policy estimation model. The administrator operates the administrator terminal 10 to transmit to the policy formulation learning device 60 a request for creating learning data settings, a request for learning policy formulation, a request for linking policy estimation models, and the like.

[0031] In communication with the policy development support device 70, the manager terminal 10 transmits and receives information for managing the policy development support device 70.

[0032] Various UIs (User Interfaces) are displayed on the administrator terminal 10 by an application (hereinafter also referred to as an "administrator app") that allows the administrator to manage the policy development support system 1. The administrator can manage the policy development support system 1 by operating the UI displayed on the administrator terminal 10 by the administrator app. The functions of the administrator app may be provided by installing the administrator app on the administrator terminal 10 (i.e., a native app), or may be provided by a Web system (i.e., a Web app). In the case of a Web app, the administrator app is managed by a server, and its functions are provided via a Web browser.

[0033] (2) User terminal 20 The user terminal 20 is a terminal that a user operates to use the policy development support system 1. The user terminal 20 is, for example, a smartphone, a tablet terminal, a PC, a dedicated handheld terminal, etc. The user terminal 20 is communicably connected to the policy development support device 70 via the network NW.

[0034] In communication with the policy development support device 70, the user terminal 20 transmits request information and receives policy information. The request information is information indicating the user's request for a sales promotion measure. The user operates the user terminal 20 to input the request information and transmit it to the measure formulation support device 70. Requests that can be input as request information include, for example, goals and conditions such as "I want to sell a product that I want to sell because it hasn't sold well," "I want to sell a product that I want to sell without changing its shelf position," and "I want to appeal to families." The policy information is information generated as information indicating candidate policies estimated by the policy formulation support device 70 based on request information transmitted from the user terminal 20. Examples of estimated policies include where to position the shelves on which products should be displayed, what content should be displayed on electronic shelf tags, what to do with the face, etc.

[0035] Various UIs are displayed on the user terminal 20 by an application (hereinafter also referred to as a "user app") that enables the user to use the policy development support system 1. The user can use the policy development support system 1 by operating the UI displayed on the user terminal 20 by the user app. The functions of the user application may be provided by installing the user application on the user terminal 20 (i.e., a native application), or may be provided by a Web system (i.e., a Web application). In the case of a Web application, the user application is managed by a server, and its functions are provided via a Web browser.

[0036] (3) Sales Management System 30 The sales management system 30 is a system for managing sales. Information managed by the sales management system 30 includes, for example, policy performance information and sales promotion performance information. The sales management system 30 is configured with, for example, one or more PCs or server devices (e.g., cloud servers). The sales management system 30 is communicably connected to the administrator terminal 10 and the policy formulation learning device 60 via a network NW.

[0037] In communication with the administrator terminal 10, the sales management system 30 receives a request for linking the learning data. In communication with the policy formulation learning device 60, the sales management system 30 transmits policy performance information, sales promotion performance information, and the like as learning data.

[0038] (4) Electronic shelf label management system 40 The electronic shelf label management system 40 is a system that manages electronic shelf labels. Information managed by the electronic shelf label management system 40 includes, for example, product information and sales environment information. The electronic shelf label management system 40 is configured by, for example, one or more PCs or server devices (e.g., cloud servers). The electronic shelf label management system 40 is communicably connected to the manager terminal 10 and the policy formulation learning device 60 via the network NW.

[0039] In communication with the manager terminal 10, the electronic shelf label management system 40 receives a linking request for learning data. In communication with the policy development learning device 60, the electronic shelf label management system 40 transmits product information, sales environment information, and the like as learning data.

[0040] (5) External Factor System 50 The external factor system 50 is a system that manages external factor information. The external factor system 50 is configured by, for example, one or more PCs or server devices (e.g., cloud servers). The external factor system 50 is communicably connected to the administrator terminal 10 and the policy formulation learning device 60 via a network NW.

[0041] The external factor information includes, for example, information about the weather, information about social media, information about manufacturer campaigns, and information about media exposure. Information about the weather can be obtained, for example, from the website of the Japan Meteorological Agency. Information about social media can be obtained, for example, from information posted on the social media. Information about manufacturer campaigns can be obtained from the manufacturer's website. Information about media exposure can be obtained from the media's website. Thus, the external factor system 50 may be one or more systems depending on the type of external factor information.

[0042] In communication with the administrator terminal 10, the external factor system 50 receives a request for linking learning data. In communication with the policy formulation learning device 60, the external factor system 50 transmits external factor information and the like as learning data.

[0043] (6) Policy formulation learning device 60 The policy formulation learning device 60 is a device that generates a policy estimation model. The policy formulation learning device 60 is configured, for example, by one or more PCs or server devices (e.g., cloud servers). The policy formulation learning device 60 is communicably connected to the manager terminal 10, the sales management system 30, the electronic shelf label management system 40, and the external factor system 50 via the network NW.

[0044] In communication with the administrator terminal 10, the policy formulation learning device 60 receives a request for generating (learning) a policy estimation model. In communication with the sales management system 30, the policy formulation learning device 60 receives policy performance information, sales promotion performance information, and the like as learning data. In communication with the electronic shelf label management system 40, the policy formulation learning device 60 receives product information, sales environment information, and the like as learning data. In communication with the external factor system 50, the policy formulation learning device 60 receives external factor information and the like as learning data. In communication with the policy formulation support device 70, the policy formulation learning device 60 transmits a policy estimation model.

[0045] (7) Policy formulation support device 70 The policy formulation support device 70 is a device that supports the formulation of policies by users. The policy formulation support device 70 is configured, for example, by one or more PCs or server devices (e.g., cloud servers). The policy formulation support device 70 is communicably connected to the administrator terminal 10, the user terminal 20, and the policy formulation learning device 60 via a network NW.

[0046] In communication with the administrator terminal 10, the policy development support device 70 transmits and receives information for managing the policy development support device 70. In communication with the user terminal 20, the policy development support device 70 receives request information and transmits policy information. In communication with the policy formulation learning device 60, the policy formulation support device 70 receives a policy estimation model.

[0047] <2. Functional configuration of the policy formulation learning device> The configuration of the policy formulation support system 1 according to this embodiment has been described above. Next, the functional configuration of the policy formulation learning device 60 according to this embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the functional configuration of the policy formulation learning device 60 according to this embodiment. As shown in FIG. 2, the policy formulation learning device 60 includes a communication unit 610, a storage unit 620, and a control unit 630.

[0048] (1) Communications Department 610 The communication unit 610 has a function of transmitting and receiving various information. The communication unit 610 is communicably connected to the manager terminal 10, the sales management system 30, the electronic shelf label management system 40, and the external factor system 50 via the network NW, and transmits and receives various information.

[0049] (2) Storage section 620 The storage unit 620 has a function of storing various types of information. The storage unit 620 is configured by a storage medium provided as hardware in the policy formulation learning device 60, such as a hard disk drive (HDD), a solid state drive (SSD), a flash memory, an electrically erasable programmable read-only memory (EEPROM), a random access read / write memory (RAM), a read-only memory (ROM), or any combination of these storage media. As shown in FIG. 2, the storage unit 620 stores a learning dataset DS created by a data processing unit 632 (described later), a policy estimation model MD generated by a learning unit 633 (described later), and the like.

[0050] (3) Control unit 630 The control unit 630 has a function of controlling the overall operation of the policy formulation learning device 60. The control unit 630 is realized, for example, by causing a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) that the policy formulation learning device 60 has as hardware to execute a program. As shown in FIG. 2, the control unit 630 includes a data acquisition unit 631, a data processing unit 632, a learning unit 633, and an output processing unit 634.

[0051] (3-1) Data Acquisition Unit 631 The data acquisition unit 631 has a function of acquiring various data. For example, the data acquisition unit 631 acquires learning data that the communication unit 610 receives from the sales management system 30, the electronic shelf label management system 40, and the external factor system 50.

[0052] (3-2) Data processing unit 632 The data processing unit 632 has a function of performing various types of data processing. For example, the data processing unit 632 creates a training dataset DS based on the training data acquired by the data acquisition unit 631.

[0053] (3-3) Learning Department 633 The learning unit 633 has a function of generating a trained model through machine learning. For example, the learning unit 633 uses the training dataset DS created by the data processing unit 632 to learn about the relationship between multiple pieces of information that affect the formulation of measures. In learning about the relationship, the learning unit 633 learns the correspondence between measures implemented in the past (measure performance information) indicated in the training dataset DS, information indicating factors that affect the formulation of the measures (factor information), and sales promotion performance due to the implementation of the measures (sales promotion performance information). Through this learning, the learning unit 633 generates a measure estimation model MD (trained model) that, when request information is input, can estimate and output measures that satisfy the requests indicated by the request information.

[0054] (3-4) Output processing unit 634 The output processing unit 634 has a function of performing processes related to the output of various information. For example, the output processing unit 634 transmits the policy estimation model MD generated by the learning unit 633 from the communication unit 610 to the policy formulation support device 70.

[0055] <3. Functional configuration of the policy formulation support device> The functional configuration of the policy formulation learning device 60 according to this embodiment has been described above. Next, the functional configuration of the policy formulation support device 70 according to this embodiment will be described with reference to Fig. 3. Fig. 3 is a block diagram showing an example of the functional configuration of the policy formulation support device 70 according to this embodiment. As shown in FIG. 3, the policy development support device 70 includes a communication unit 710, a storage unit 720, and a control unit 730.

[0056] (1) Communications Unit 710 The communication unit 710 has a function of transmitting and receiving various information. The communication unit 710 is communicably connected to the administrator terminal 10, the user terminal 20, and the policy formulation learning device 60 via the network NW, and transmits and receives various information.

[0057] (2) Storage section 720 The storage unit 720 has a function of storing various types of information. The storage unit 720 is configured by a storage medium provided as hardware in the policy development support device 70, such as an HDD, SSD, flash memory, EEPROM, RAM, ROM, or any combination of these storage media. As shown in FIG. 3, the storage unit 720 stores the policy estimation model MD generated by the policy formulation learning device 60 and the like.

[0058] (3) Control unit 730 The control unit 730 has a function of controlling the overall operation of the policy development support device 70. The control unit 730 is realized, for example, by causing a CPU or GPU provided as hardware in the policy development support device 70 to execute a program. As shown in FIG. 3, the control unit 730 includes a request information acquisition unit 731, a measure estimation unit 732, and a measure output unit 733.

[0059] (3-1) Request information acquisition unit 731 The request information acquisition unit 731 has a function of acquiring request information. The request information acquisition unit 731 acquires the request information that the communication unit 710 receives from the user terminal 20.

[0060] (3-2) Policy estimation section 732 The measure estimation unit 732 has a function of estimating measures. Based on the relationship between the measure performance information, the factor information, and the sales promotion performance information, the measure estimation unit 732 estimates measures that will satisfy the user's requests indicated by the request information acquisition unit 731. The measure estimation unit 732 inputs the request information acquired by the request information acquisition unit 731 into the measure estimation model MD stored in the storage unit 720, and thereby acquires at least one measure output from the measure estimation model MD as candidate measures.

[0061] The measure estimation model MD performs learning using sales environment information as one of the factor information. Therefore, the measure estimation unit 732 can estimate measures for the product sales environment as measures to satisfy user needs. Measures for the product sales environment include, for example, measures related to product shelving and measures related to the installation or display of electronic shelf labels. Examples of strategies for product shelf allocation include, "If a product will sell no matter which shelf it is placed on, it does not need to be placed in a good position on the shelf because the product itself has a high appeal," "It is effective to place product A next to the ○○ sales area during the XX time period," "When there is a △△ event, it should be placed near the □□ sales area," and changes to the recommended number of faces. Examples of measures regarding the installation or display of electronic shelf tags include measures such as "If the position of the product on the shelf is not changed, then just use larger shelf tags (which will increase sales by making them easier to see)" and changing to a recommended shelf tag size.

[0062] Furthermore, the policy estimation model MD performs learning using external factor information as one of the factor information. Therefore, the policy estimation unit 732 can estimate a policy that takes external factors into consideration as a policy to satisfy user needs. For example, if there is a product that has become a hot topic on social media, the policy estimation unit 732 estimates policies such as increasing the number of faces for the product and placing related products nearby.

[0063] Furthermore, the measure estimation model MD is trained using sales results as one of the sales promotion performance information. Therefore, the measure estimation unit 732 may not only estimate candidate measures, but also estimate the expected sales if the estimated measures are implemented.

[0064] (3-3) Policy output unit 733 The measure output unit 733 has a function of outputting measures. The measure output unit 733 outputs candidate measures that satisfy the user's requests, based on the measure estimation result by the measure estimation unit 732. Note that, when the measure estimation unit 732 has also estimated expected sales, the measure output unit 733 may output the expected sales together with the candidate measures. The policy output unit 733 generates policy information indicating candidate policies or sales projections based on the estimation result by the policy estimation unit 732. The policy output unit 733 transmits the generated policy information to the user terminal 20 via the communication unit 710 and causes the user terminal 20 to display it.

[0065] <4. Processing flow> The functional configuration of the policy formulation support device 70 according to this embodiment has been described above. Next, the flow of processing according to this embodiment will be described with reference to FIGS.

[0066] (1) Policy learning process The flow of the policy learning process according to this embodiment will be described with reference to Fig. 4. Fig. 4 is a sequence diagram showing an example of the flow of the policy learning process according to this embodiment.

[0067] 4, first, the sales management system 30 links (transmits) learning data to the policy formulation learning device 60 (step S101). When the sales management system 30 receives a linking request from the administrator terminal 10, it transmits, for example, policy performance information, sales promotion performance information, etc. as learning data to the policy formulation learning device 60.

[0068] Next, the electronic shelf label management system 40 links (transmits) the learning data to the policy formulation learning device 60 (step S102). When the electronic shelf label management system 40 receives a linking request from the manager terminal 10, it transmits, for example, product information, sales environment information, etc. as learning data to the policy formulation learning device 60.

[0069] Next, the external factor system 50 links (transmits) the learning data to the policy formulation learning device 60 (step S103). When the external factor system 50 receives a linking request from the administrator terminal 10, it transmits, for example, external factor information to the policy formulation learning device 60 as learning data.

[0070] The processing order from step S101 to step S103 is not limited to the order shown in FIG. 4, and may be any order.

[0071] The data acquisition unit 631 of the policy formulation learning device 60 acquires learning data (step S104). The data acquisition unit 631 acquires, as learning data, policy performance information, sales promotion performance information, product information, sales environment information, external factor information, and the like linked in steps S101 to S103. Next, the data processing unit 632 of the policy formulation learning device 60 creates a learning dataset DS based on the learning data acquired by the data acquisition unit 631 (step S105). Next, the learning unit 633 of the policy formulation learning device 60 learns about policy formulation based on the learning dataset DS created by the data processing unit 632 (step S106). Next, the learning unit 633 generates a policy estimation model MD based on the learning result (step S107). Next, the learning unit 633 stores the generated policy estimation model in the storage unit 620 (step S108).

[0072] Next, the output processing unit 634 of the policy formulation learning device 60 links (transmits) the policy estimation model MD to the policy formulation support device 70 (step S109). When the communication unit 610 receives a link request from the administrator terminal 10, the output processing unit 634 transmits the policy estimation model MD stored in the storage unit 620 to the policy formulation support device 70. The policy formulation support device 70 stores the policy estimation model MD received by the communication unit 710 from the policy formulation learning device 60 in the storage unit 720 (step S110).

[0073] (2) Policy formulation process The flow of the policy formulation process according to this embodiment will be described with reference to Fig. 5. Fig. 5 is a sequence diagram showing an example of the flow of the policy formulation process according to this embodiment.

[0074] As shown in FIG. 5, first, the user inputs a request for a measure to the user terminal 20 (step S201). The user terminal 20 transmits request information indicating the request input by the user to the policy development support device 70 (step S202).

[0075] The request information acquisition unit 731 of the policy development support device 70 acquires the request information received by the communication unit 710 from the user terminal 20 (step S203). The policy estimation unit 732 of the policy formulation support device 70 estimates a policy based on the request information acquired by the request information acquisition unit 731, using the policy estimation model MD stored in the storage unit 720 (step S204). The policy output unit 733 of the policy formulation support device 70 generates policy information based on the estimation result output by the policy estimation unit 732 (step S205). The policy output unit 733 transmits the generated policy information to the user terminal 20 via the communication unit 710 (step S206).

[0076] The user terminal 20 displays candidate measures, which are the estimation results, based on the measure information received from the measure development support device 70 (step S207). The user checks the candidate measures displayed on the user terminal 20 (step S208). The user formulates a measure by determining a measure to be implemented from among the candidate measures (step S209).

[0077] The processing flow according to this embodiment has been described above. As described above, the policy formulation support system 1 according to this embodiment includes a request information acquisition unit 731 that acquires request information indicating user requests for sales promotion measures, a policy estimation unit 732 that estimates measures that will satisfy the user requests indicated by the acquired request information based on the relationship between measures implemented in the past, information indicating factors that influence the formulation of the measures, and the sales promotion results resulting from the implementation of the measures, and a policy output unit 733 that outputs candidate measures that will satisfy the user requests based on the results of the estimated measures.

[0078] With this configuration, a user can obtain estimated results of candidate policies from the policy formulation support system 1 by inputting a request for a policy to the policy formulation support system 1. The user can formulate a policy by simply selecting a policy from the candidate policies obtained from the policy formulation support system 1. In this way, the user can formulate a policy by simply inputting a request to the policy formulation support system 1. Therefore, the policy formulation support system 1 according to this embodiment enables even an inexperienced person to easily formulate a policy.

[0079] <5. Example> This concludes the description of the present embodiment. Next, an example of the present embodiment will be described with reference to FIGS.

[0080] (1) If the user is a store representative A case where the user is a store staff member will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of an example where the user according to this embodiment is a store staff member. In the example shown in Fig. 6, it is assumed that electronic shelf labels 80 are installed in a store, and measures regarding the display of the electronic shelf labels 80 are to be formulated.

[0081] 6, the store staff inputs a request to the user terminal 20. The user terminal 20 transmits request information indicating the request input by the user to the policy development support device . The policy formulation support device 70 estimates candidate policies based on the request information received from the user terminal 20, and transmits policy information indicating the estimated results to the user terminal 20.

[0082] The store staff checks the policy information displayed on the user terminal 20 and decides which policy to implement from among the candidate policies. The user terminal 20 transmits information about the measures that the store staff member has decided to implement to the electronic shelf label management system 40. Based on the received information about the measures, the electronic shelf label management system 40 reflects the details of the measures on the displays of the electronic shelf labels 80 installed in the store.

[0083] (2) If the user is a person in charge at headquarters A case where the user is a person in charge at headquarters (headquarters) will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of an example where the user according to this embodiment is a person in charge at headquarters. In the example shown in Fig. 7, electronic shelf labels 80 are installed in multiple stores managed by the headquarters, and measures regarding the display of the electronic shelf labels 80 are to be formulated.

[0084] 7, the person in charge at the headquarters inputs a request to the user terminal 20. The user terminal 20 transmits request information indicating the request input by the user to the policy development support device . The policy formulation support device 70 estimates candidate policies based on the request information received from the user terminal 20, and transmits policy information indicating the estimated results to the user terminal 20.

[0085] The person in charge at the headquarters checks the policy information displayed on the user terminal 20 and decides which policy to implement from among the candidate policies. The user terminal 20 transmits information about the measures that the person in charge at headquarters has decided to implement to the electronic shelf label management system 40. Based on the received information about the measures, the electronic shelf label management system 40 collectively reflects the details of the measures on the displays of the electronic shelf labels 80 installed in multiple stores (Store A, Store B, . . . , Store N).

[0086] <6. Variations> An example of the present embodiment has been described above. Next, a modified example of the present embodiment will be described. Note that each modified example described below may be applied to the embodiment alone or in combination with the embodiment. Furthermore, each modified example may be applied in place of the configuration described in the embodiment, or may be applied in addition to the configuration described in the embodiment.

[0087] In the above-described embodiment, an example has been described in which the policy formulation support system 1 includes the policy formulation learning device 60 having a policy formulation learning function and the policy formulation support device 70 having a policy estimation function, but the present invention is not limited to such an example. For example, the policy formulation support system 1 may include a single device having both a policy formulation learning function and a policy estimation function, instead of the policy formulation learning device 60 and the policy formulation support device 70.

[0088] In the above-described embodiment, an example has been described in which learning data is linked from the sales management system 30, the electronic shelf label management system 40, and the external factor system 50 to the policy formulation learning device 60, but the present invention is not limited to such an example. For example, learning data may be acquired from each system by an administrator and linked to the policy formulation learning device 60 from the administrator terminal 10.

[0089] The above describes the modified example of this embodiment. In addition, some or all of the policy formulation support system 1, administrator terminal 10, user terminal 20, sales management system 30, electronic shelf label management system 40, external factor system 50, policy formulation learning device 60, and policy formulation support device 70 in the above-described embodiment may be realized by a computer. In this case, a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read into and executed by a computer system. Note that the term "computer system" here includes hardware such as an OS and peripheral devices. Additionally, "computer-readable recording media" refers to portable media such as flexible disks, optical magnetic disks, ROMs, CD-ROMs, etc., and storage devices such as hard disks built into computer systems. Furthermore, "computer-readable recording media" may also include devices that dynamically store programs for a short period of time, such as communication lines when transmitting programs via networks such as the Internet or communication lines such as telephone lines, and devices that store programs for a certain period of time, such as volatile memory within computer systems that serve as servers or clients in such cases. Furthermore, the above program may be one that realizes part of the above-mentioned functions, or may be one that can realize the above-mentioned functions in combination with a program already recorded in a computer system, or may be one that is realized using a programmable logic device such as an FPGA (Field Programmable Gate Array).

[0090] The embodiments of the present invention have been described in detail above with reference to the drawings, but the specific configuration is not limited to that described above, and various design changes can be made within the scope of the gist of the present invention. [Explanation of symbols]

[0091] 1...policy formulation support system, 10...administrator terminal, 20...user terminal, 60...policy formulation learning device, 70...policy formulation support device, 610...communication unit, 620...storage unit, 630...control unit, 631...data acquisition unit, 632...data processing unit, 633...learning unit, 634...output processing unit, 710...communication unit, 720...storage unit, 730...control unit, 731...request information acquisition unit, 732...policy estimation unit, 733...policy output unit, MD...policy estimation model, NW...network

Claims

1. a request information acquisition unit that acquires request information indicating user requests for sales promotion measures; a measure estimation unit that estimates the measure that satisfies the user's request indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and sales promotion results due to the implementation of the measures; and a measure output unit that outputs candidate measures that satisfy the user's requests based on the estimated measures; A policy formulation support system equipped with:

2. the information indicating factors influencing the formulation of the measures includes product information regarding the products that are the targets of the measures and sales environment information regarding the sales environment of the products; the measure estimation unit estimates a measure for a sales environment of the product as the measure to satisfy the user's request; The policy formulation support system according to claim 1.

3. the sales environment information includes information regarding installation or display of an electronic shelf label on which product information of the product is displayed, the measure estimation unit estimates a measure related to installation or display of the electronic shelf label as a measure for the sales environment of the product; The policy formulation support system according to claim 2.

4. The sales environment information includes information regarding the shelf layout of the product, the measure estimation unit estimates a measure regarding shelf allocation of the product as a measure for the sales environment of the product; The policy formulation support system according to claim 2.

5. The information indicating factors that influence the formulation of the policy includes external factor information regarding external factors, the measure estimation unit estimates a measure that takes the external factors into consideration as the measure that satisfies the user's request; The policy formulation support system according to claim 1.

6. The sales promotion results resulting from the implementation of the measures include sales information indicating sales results, the measure estimation unit estimates expected sales if the estimated measure is implemented; the measure output unit outputs the sales forecast together with the measure candidates. The policy formulation support system according to claim 1.

7. a storage unit that stores a trained model that has learned the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and sales promotion results due to the implementation of the measures; Furthermore, The policy estimation unit inputs the request information acquired by the request information acquisition unit into the trained model, and thereby acquires at least one or more of the policies output from the trained model as candidates for the policies. The policy formulation support system according to claim 1.

8. a request information acquisition step of acquiring request information indicating user requests for sales promotion measures; a measure estimation process for estimating the measure that satisfies the user's request indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and sales promotion results due to the implementation of the measures; a measure output step of outputting candidate measures that satisfy the user's requests based on the estimated measures; A policy formulation support method executed by a computer, comprising:

9. Computer, a request information acquisition means for acquiring request information indicating user requests for sales promotion measures; a measure estimation means for estimating the measure that satisfies the user's request indicated by the acquired request information based on the relationship between the measures implemented in the past, information indicating factors that influence the formulation of the measures, and sales promotion results resulting from the implementation of the measures; a measure output means for outputting candidate measures that satisfy the user's requests based on the estimated measures; A program to function as a

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