Information processing device and information processing method

Abstract

To enable product placement from the consumer's perspective. [Solution] The information processing device 1 has an identification unit 132 that identifies the distribution of attributes that indicate the purchasing values ​​of multiple customers in the area to which the target store belongs, the attributes being attributes related to consumers' purchase of goods and attributes attached to goods, and a generation unit 134 that generates arrangement information indicating the arrangement of multiple goods in the sales area of ​​the target store based on the distribution of attributes identified by the identification unit 132 and the attributes corresponding to each of the multiple goods, and an output unit 135 that outputs the arrangement information generated by the generation unit 134.

Description

[Technical Field]

[0001] The present invention relates to an information processing apparatus and an information processing method. [Background Art]

[0002] Conventionally, in stores such as supermarkets and convenience stores, support for arranging a plurality of products in the store has been performed. For example, Patent Document 1 discloses an apparatus that generates a product display form based on sales for each product and sales for each position of a product shelf. [Prior Art Literature] [Patent Literature]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2010-33114 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] Product arrangement based on sales is product arrangement based on the perspective of the store side, and is not necessarily a product arrangement preferable for consumers.

[0005] Accordingly, the present invention has been made in view of these points, and an object of the present invention is to enable product arrangement from the perspective of consumers. [Means for Solving the Problem]

[0006] An information processing device according to a first aspect of the present invention has a specification unit that specifies the distribution of attributes indicating the purchasing values ​​of each of a plurality of customers in the area to which the target store belongs, wherein the attributes are attributes relating to the consumer's purchase of goods and are attributes attached to goods, and a generation unit that generates arrangement information indicating the arrangement of the plurality of goods in the sales area of ​​the target store based on the distribution of the attributes specified by the specification unit and the attributes corresponding to each of the plurality of goods, and an output unit that outputs the arrangement information generated by the generation unit.

[0007] The information processing device further includes a determination unit that determines, based on the distribution of the attributes, attributes with a relatively high proportion as priority attributes which are important in the sale of products in the sales area, and the generation unit may generate arrangement information that shows the arrangement of the plurality of products in the sales area of ​​the target store, with priority given to the products corresponding to the priority attributes determined by the determination unit.

[0008] The identification unit identifies the distribution corresponding to each of the multiple common stores which are multiple stores operated by a predetermined business operator, and identifies common stores whose distribution is similar to the distribution corresponding to the target store as approximate common stores. The determination unit may then determine the priority attribute based on the comparison result between the sales performance for each attribute of the target store and the sales performance for each attribute of the approximate common stores, and the distribution of attributes corresponding to each of the multiple customers in the area to which the target store identified by the identification unit belongs.

[0009] The determination unit may acquire policy information indicating measures related to the sale of products at the target store, which includes at least one of product information indicating products that are to be sold at the target store and information for identifying target attributes that are the attributes of customers for whom sales will be strengthened. The unit may then identify an attribute from among a plurality of attributes relating to consumer purchasing that corresponds to at least one of the products to be sold and the target attributes indicated by the policy information, and further determine the priority attribute based on the identified attribute.

[0010] The generation unit may acquire movement information indicating the movement of customers who visit the target store, identify locations in the sales area that customers frequently view based on the movement information, and generate placement information in which products with the priority attributes are preferentially placed in the identified locations.

[0011] The generation unit may refer to shelf-specific sales information that associates the location of each of the multiple product shelves in the target store with the sales of each of the multiple attributes on the product shelf, identify the location of the product shelf where the sales of the product corresponding to the priority attribute are relatively high, and generate the arrangement information that places the product shelf containing the product corresponding to the priority attribute at the identified location.

[0012] The generation unit may acquire store structure information indicating the location of fixed equipment in the target store, identify attributes corresponding to the fixed equipment, and generate the layout information based on the location of the fixed equipment and the identified attributes corresponding to the fixed equipment.

[0013] The generation unit may generate multiple arrangement plans for the multiple products in the sales area of ​​the target store based on the distribution of the attributes identified by the identification unit and the attributes corresponding to each of the multiple products, and use traffic flow information indicating customer traffic in the target store to simulate sales or customer dwell time for each of the multiple arrangement plans, and generate information as arrangement information indicating the arrangement plan that shows relatively high sales or customer dwell time in the target store.

[0014] The generation unit may further generate change plan information indicating a change plan to gradually change the layout of the sales floor from the current layout to the changed layout, based on the generated layout information, the changed layout which is the layout of the sales floors of the multiple products in the target store, the current layout which is the current layout of the sales floors of the multiple products in the target store, the resources of personnel responsible for arranging the products in the target store, and the inventory status of the multiple products, and the output unit may output the change plan information.

[0015] The information processing device has a storage unit that stores replenishment characteristic information, which is the characteristic of each of the multiple products relating to the replenishment of each product, and store layout information, which includes information indicating the arrangement of equipment in the sales area of ​​the target store. The generation unit may generate arrangement information indicating the arrangement of the multiple products in the sales area of ​​the target store, based on the equipment arrangement indicated by the store layout information and the replenishment characteristics indicated by the replenishment characteristic information corresponding to each of the multiple products.

[0016] A second aspect of the present invention relates to an information processing method which includes the step of a computer identifying the distribution of attributes that indicate the purchasing values ​​of each of a plurality of customers in the area to which a target store belongs, wherein the attributes are attributes relating to consumers' purchase of goods and are attached to goods, and the method includes the step of generating arrangement information that indicates the arrangement of the plurality of goods in the sales area of ​​the target store based on the identified distribution of the attributes and the attributes corresponding to each of the plurality of goods, and the step of outputting the generated arrangement information. [Effects of the Invention]

[0017] According to this invention, the effect is that products can be arranged from the consumer's perspective. [Brief explanation of the drawing]

[0018] [Figure 1] This is a diagram illustrating the overview of the information processing system. [Figure 2] This diagram shows the functional configuration of an information processing device. [Figure 3] This figure shows an example of product information. [Figure 4] This figure shows an example of user information. [Figure 5] This figure shows an example of the distribution of attributes corresponding to target stores identified by the specific department. [Figure 6] This figure shows an example of the arrangement indicated by the arrangement information generated by the generation unit. [Figure 7]It is a flowchart showing a process flow related to an information processing apparatus. DETAILED DESCRIPTION OF THE INVENTION

[0019] [Overview of Information Processing Apparatus 1] FIG. 1 is a diagram showing an overview of the information processing apparatus 1. The information processing apparatus 1 is a computer that generates arrangement information indicating the arrangement of products in a store such as a supermarket or a convenience store. The information processing apparatus 1 is communicably connected to a user terminal 2 used by a store manager or the like as a user.

[0020] The information processing apparatus 1 stores, for each of a plurality of products, a product ID (Identification) serving as product identification information for identifying the product, in association with an attribute corresponding to the product among a plurality of attributes indicating values related to consumers' product purchasing.

[0021] The information processing apparatus 1 identifies the distribution of attributes indicating purchasing values of each of a plurality of customers in an area to which the target store belongs ((1) in FIG. 1). Here, the target store is a store operated by a predetermined business operator, and is a target store for which arrangement information indicating the arrangement of a plurality of products is generated.

[0022] The information processing apparatus 1 receives a request for generating arrangement information indicating the arrangement of products in the target store from the user terminal 2 ((2) in FIG. 1). Upon receiving the request for generating arrangement information, the information processing apparatus 1 generates arrangement information indicating the arrangement of a plurality of products in the sales floor of the target store based on the identified distribution of attributes and the attributes corresponding to each of the plurality of products ((3) in FIG. 1). Then, the information processing apparatus 1 outputs the generated arrangement information to the user terminal 2 ((4) in FIG. 1)

[0023] As described above, the information processing apparatus 1 generates arrangement information based on the distribution of attributes indicating the purchasing values of each of a plurality of customers in the area to which the target store belongs, so that products can be arranged from the consumer's perspective.

[0024] [Functional configuration of the information processing device 1] Next, the functional configuration of the information processing device 1 will be described. Figure 2 is a diagram showing the functional configuration of the information processing device 1. The information processing device 1 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0025] The communication unit 11 is a communication interface for sending and receiving data with user terminals 2, etc., via a communication network such as the Internet or a mobile phone line.

[0026] The memory unit 12 is a storage medium for storing various types of data and includes ROM (Read Only Memory) and RAM (Random Access Memory), etc. The memory unit 12 stores the program to be executed by the control unit 13. For example, the memory unit 12 stores a program that causes the control unit 13 to function as a receiving unit 131, a specifying unit 132, a decision unit 133, a generation unit 134, and an output unit 135.

[0027] Furthermore, the memory unit 12 stores product information for each of the multiple products, which associates the product ID, which is product identification information for identifying the product, with the attribute corresponding to the product from among multiple attributes that indicate the consumer's purchasing values. Figure 3 is a diagram showing an example of product information. As shown in Figure 3, the product ID is stored associated with the category to which the product belongs and a score indicating the degree of correspondence to each of the multiple attributes of the product.

[0028] Attributes represent values ​​that consumers are likely to consider important when purchasing a product, such as health, exercise, convenience, satisfaction, and cost-effectiveness. The score indicates the degree of correspondence, and can be one of six integers from 0 to 6. For example, a health score of 5 indicates that the product is the most health-oriented product.

[0029] While a score indicating the degree of correspondence with each of the product's multiple attributes is associated with the product ID, this is not the only option. Label information indicating one or more attributes that the product corresponds to may also be associated with the product ID.

[0030] Furthermore, the memory unit 12 stores user information that associates the user ID, attributes, and behavioral history. Figure 4 shows an example of user information. The user ID is information that identifies a user, specifically, information used to identify a user. The attributes included in the user information are associated with a score that indicates the degree to which they correspond to the user's attributes. For example, a higher numerical value indicates a higher degree of correspondence to the attribute. In addition, in the user information, only one attribute (for example, the attribute with the highest degree of correspondence to the user) may be stored for each user ID, or attribute values ​​corresponding to only one attribute may be stored. The behavioral history is a history of the user's actions, such as the user's location history or purchase history.

[0031] The control unit 13 is, for example, a CPU (Central Processing Unit). The control unit 13 functions as a receiving unit 131, a identifying unit 132, a decision unit 133, a generation unit 134, and an output unit 135 by executing a program stored in the storage unit 12.

[0032] The reception unit 131 receives a request from the user terminal 2 to identify the distribution of attributes possessed by each of several customers in the area to which the target store belongs. The reception unit 131 also receives a request from the user terminal 2 to determine priority attributes, which are the attributes that are important in the sale of products in the sales area of ​​the target store. The reception unit 131 also receives a request from the user terminal 2 to generate placement information that shows the arrangement of several products in the sales area of ​​the target store.

[0033] The identification unit 132 identifies the distribution of attributes that indicate the purchasing values ​​of multiple customers in the area to which the target store belongs. When the receiving unit 131 receives a request to identify the attribute distribution, the identification unit 132 refers to the user information and product information stored in the storage unit 12 to identify the distribution of attributes that indicate the purchasing values ​​of multiple customers in the area to which the target store belongs. The identification unit 132 calculates the distribution of user attributes of the target store by performing, for example, the following three steps.

[0034] As the first step, the identification unit 132 refers to map information and the location of the target store to identify a store area, which is a predetermined range including the target store. For example, the identification unit 132 identifies the store area as an area with a radius of a predetermined distance from the store (e.g., 100 meters), the part of the road that the user travels on that is adjacent to the store, or the inside of the store.

[0035] In the second step, the identification unit 132 refers to the user's activity history stored in the user information (e.g., user location history) and the location and map information of the target store to identify users who were present in the store range corresponding to the target store during the analysis period. The analysis period may be a predetermined period (e.g., the most recent or previous year's week, month, or year), or it may be a period set by the manager of the target store via the reception unit 131.

[0036] As a third step, the identification unit 132 refers to user information and calculates the ratio of the attributes of each of the multiple users identified for the target store as the distribution of user attributes corresponding to the target store. The attribute distribution may be the ratio of one attribute assigned to each user, the ratio of the attribute with the highest attribute value among the multiple attributes assigned to each user, the ratio of the sum of the attribute values ​​of each of the multiple attributes assigned to each user, or the ratio of the statistical values ​​(e.g., mean, mode, median, etc.) of the attribute values ​​of each of the multiple attributes assigned to each user. Alternatively, for example, a threshold may be set for each attribute, and the identification unit 132 may assign "1" to the attribute if the attribute value of that attribute exceeds the threshold corresponding to that attribute, and assign "0" to the attribute if the attribute value does not exceed the threshold corresponding to that attribute, and calculate the ratio of the sum of the values ​​assigned to each attribute for each user as the distribution of user attributes.

[0037] Figure 5 shows an example of the distribution of attributes corresponding to the target stores identified by the identification unit 132. In the example shown in Figure 5, the distribution of nine attributes is shown, and it can be confirmed that "saving money" has the highest proportion.

[0038] When the reception unit 131 receives a request from the user terminal 2 to determine a priority attribute, the determination unit 133 determines the priority attribute. Specifically, based on the distribution of attributes of multiple customers in the area to which the target store belongs, as identified by the identification unit 132, the determination unit 133 determines the attribute with a relatively high proportion as the priority attribute, which is the attribute that will be given importance in the sale of goods at the target store. For example, in the example shown in Figure 5, the determination unit 133 determines "saving money," which is the attribute with the highest proportion in the attribute distribution corresponding to the target store, as the priority attribute. Here, the determination unit 133 may determine multiple priority attributes. In this case, the determination unit 133 may determine multiple attributes as priority attributes in order of their proportion in the attribute distribution, or it may determine all attributes whose proportion exceeds a predetermined threshold as priority attributes.

[0039] The decision unit 133 determined the priority attribute based solely on the distribution of customer attributes in the area to which the target store belongs, but is not limited to this. For example, the decision unit 133 may also determine the priority attribute based on sales performance for each attribute at the store.

[0040] In this case, the identification unit 132 identifies the distribution of attributes corresponding to each of the multiple common stores, which are multiple stores operated by a predetermined business operator. For example, the identification unit 132 identifies the distribution of attributes corresponding to each of the multiple common stores by performing the processes from the first to the third steps described above for each of the multiple stores. The identification unit 132 then identifies common stores whose attribute distribution approximates the attribute distribution corresponding to the target store as approximate common stores.

[0041] The decision unit 133 determines priority attributes based on the comparison results of the sales performance for each attribute of the target store and the sales performance for each attribute of similar common stores, and the distribution of multiple attributes held by multiple customers at the target store identified by the identification unit 132. For example, the storage unit 12 stores store-specific sales information showing the sales performance for each attribute at each of the multiple common stores operated by a predetermined business operator. The decision unit 133 refers to the store-specific sales information and identifies the sales performance for each attribute of the target store and the sales performance for each attribute of similar common stores. Then, the decision unit 133 compares the sales performance for each attribute of the target store and the sales performance for each attribute of similar common stores and identifies multiple attributes that have a low sales ratio at the target store and a high sales ratio at similar common stores.

[0042] Furthermore, the determination unit 133 identifies multiple attributes with a large proportion in the distribution based on the distribution of multiple attributes possessed by multiple customers at the target store. Then, the determination unit 133 determines priority attributes based on multiple attributes with a large proportion in sales and multiple attributes with a large proportion in the distribution. For example, the determination unit 133 calculates a score for multiple attributes based on the sales ratio and also calculates a score based on the proportion in the distribution, and determines multiple attributes with a relatively large sum of these scores as priority attributes. In this way, the information processing device 1 can more easily determine as priority attributes the attributes of products that have high sales at similar common stores, low sales at the target store, and have room for improvement in sales, that is, the attributes of products that can be expected to increase sales at the target store.

[0043] Furthermore, the decision unit 133 may acquire policy information indicating measures related to the sale of products at the target store, which includes at least one of the following: product information indicating products whose sales will be strengthened at the target store, and information for identifying target attributes, which are the attributes of customers for whom sales will be strengthened. The decision unit 133 may then identify attributes from among several attributes related to consumer purchasing that correspond to at least one of the products whose sales will be strengthened and the target attributes indicated in the policy information, and further determine priority attributes based on the identified attributes.

[0044] The determination unit 133 calculates a score for multiple attributes, for example, based on the ratio of each attribute in the attribute distribution. The determination unit 133 weights the scores of the multiple attributes by multiplying the score of the attribute that corresponds to at least one of the sales-enhancing product and the target attribute by a coefficient greater than 1, for example. Then, it determines that multiple attributes with relatively large scores are priority attributes. In this way, the information processing device 1 can determine priority attributes while taking into account the measures of the target store.

[0045] When the receiving unit 131 receives a request from the user terminal 2 to generate placement information, the generation unit 134 generates placement information indicating the placement of multiple products in the sales area of ​​the target store. Based on the distribution of attributes identified by the identification unit 132 and the attributes corresponding to each of the multiple products, the generation unit 134 generates placement information indicating the placement of multiple products in the sales area of ​​the target store. For example, the generation unit 134 generates placement information indicating the placement of multiple products in the sales area of ​​the target store, prioritizing the placement of products corresponding to the priority attributes determined by the decision unit 133.

[0046] Specifically, first, the generation unit 134 acquires movement information showing the movement of customers within the target store. Movement information is, for example, video information showing the movement of customers within the store, captured by each of the multiple imaging devices installed within the target store. Based on the acquired movement information, the generation unit 134 identifies locations in the sales area of ​​the target store that customers frequently see or stop at, as the placement locations for products with priority attributes. Then, the generation unit 134 generates placement information that prioritizes the placement of products with priority attributes at the identified locations.

[0047] For example, the generation unit 134 identifies multiple products to be placed on the sales floor of the target store. These multiple products are, for example, designated in advance by the store's headquarters and stored in the storage unit 12 as placement product information. The generation unit 134 refers to the placement product information to identify the multiple products to be placed on the sales floor of the target store.

[0048] The generation unit 134 identifies products from among the identified products that are associated with the priority attribute determined by the decision unit 133. The generation unit 134 inputs information about product shelves, such as the size and load capacity of each of the multiple product shelves in the sales area of ​​the target store, information showing the floor layout of the sales area of ​​the target store, information showing the identified multiple products, and products associated with the priority attribute to the large-scale language model, and instructs it to generate placement information that shows the sales area arrangement prioritizing the products associated with the priority attribute. Then, the generation unit 134 generates the placement information by obtaining the placement information from the large-scale language model. The generation unit 134 may also input past placement information showing past product arrangements in the target store to the large-scale language model, allowing it to learn examples of product shelf arrangements in the target store, before generating the placement information.

[0049] Here, the placement information may not include the specific location of each individual product, but rather store layout information that indicates the location of product shelves corresponding to each category of products, and the location of special product shelves such as a "health-conscious corner" where product groups corresponding to priority attributes are grouped together. Figure 6 is a diagram showing an example of placement information generated by the generation unit 134. The example shown in Figure 6 shows an example of store layout when the priority attribute is "saving money," and it can be seen that the placement locations of products related to "saving money" are indicated in various places within the store.

[0050] The generation unit 134 may refer to shelf-specific sales information that associates the location of each of several product shelves in the target store with the sales of each of several attributes on the product shelf, and identify the location of the product shelf where sales of products corresponding to the priority attribute are relatively high as the priority location where products corresponding to the priority attribute should be placed preferentially. The generation unit 134 may then generate placement information that places product shelves with products corresponding to the priority attribute at the identified priority location.

[0051] In this case, the generation unit 134 inputs information indicating the identified priority location, information about the product shelves indicating the size, load capacity, etc., of each of the multiple product shelves, information indicating the identified multiple products, and products associated with the priority attribute, and instructs the large-scale language model to generate arrangement information in which product shelves displaying products corresponding to the priority attribute are placed at the identified priority location. In this way, the information processing device 1 can generate arrangement information that promotes the sale of the priority attribute in the target store.

[0052] Furthermore, the generation unit 134 may acquire store structure information indicating the location of fixed equipment in the target store and identify attributes corresponding to the fixed equipment. Here, fixed equipment includes, for example, product shelves such as a prepared food section adjacent to a prepared food processing facility, fresh food shelves with refrigeration capabilities, a fresh fish section adjacent to a fresh fish preparation area, and a meat section adjacent to a meat processing plant. The store structure information also includes information indicating the location, size, and purpose of the fixed equipment.

[0053] The generation unit 134 identifies attributes that are pre-associated with these fixed equipment. For example, the generation unit 134 identifies pre-associated attributes such as "convenience" for the prepared food section, and "cooking enthusiast" and "quality" for the meat and fish sections. The generation unit 134 then generates layout information based on the location of the fixed equipment and the attributes corresponding to the identified fixed equipment.

[0054] For example, the generation unit 134 further inputs store structure information corresponding to fixed equipment and information indicating attributes associated with said fixed equipment into the large-scale language model, and also inputs instruction information that instructs the system to preferentially place products corresponding to said attributes, thereby generating placement information. In this way, the information processing device 1 can generate placement information that preferentially places products with attributes suitable for the fixed equipment into the fixed equipment.

[0055] Furthermore, the generation unit 134 may generate multiple layout plans for multiple products in the sales area of ​​the target store based on the distribution of attributes identified by the identification unit 132 and the attributes corresponding to each of the multiple products. For example, the generation unit 134 may be instructed to generate multiple layout plans that show the sales area layout prioritizing products associated with priority attributes in the large-scale language model. The generation unit 134 then obtains multiple layout plans from the large-scale language model.

[0056] The generation unit 134 then uses traffic flow information, which shows the flow of customers in the target store, to simulate sales or customer dwell time for each of the multiple layout options in which multiple products are placed in the target store. For each of the multiple layout options, the generation unit 134 inputs the layout option and traffic flow information into a large-scale language model and simulates sales and customer dwell time. Alternatively, the generation unit 134 may use a simulation tool that simulates sales and customer dwell time based on the layout option and traffic flow information to simulate sales and customer dwell time. The generation unit 134 then generates information as layout information that indicates the layout option with relatively high sales or customer dwell time in the target store. In this way, the information processing device 1 can select an appropriate layout option from among the multiple layout options.

[0057] Furthermore, the storage unit 12 may store replenishment characteristic information, which indicates the characteristics of each of the multiple products related to replenishment, and store layout information, which includes information indicating the placement of equipment. The information indicating the placement of equipment is information indicating at least one of the entrances and exits in the sales area and back room of the target store, the routes within the store, and the physical constraints of the product shelves. The location of the back room entrances and exits, and the traffic flow and route information within the store are obtained, for example, from the store layout information. The physical constraints of the product shelves are the size of the product shelves (width, height, depth), load capacity, etc., and are stored in the storage unit 12 in advance as information related to the product shelves.

[0058] Replenishment characteristics include information such as replenishment frequency, product characteristics, product packaging, and replenishment unit. Replenishment frequency is determined based on the number of times a product is replenished on the shelves per unit period (e.g., day, week, etc.) or the number of units sold identified from POS (Point of Sales) data. Product characteristics are information registered in the store's product master, such as the "weight" and "size (volume)" of each product. For heavy products (e.g., beverages, rice) or large-volume products, information indicating that they are difficult to replenish may be added as a product characteristic due to the extremely high transportation burden. Packaging and replenishment units are information indicating the storage method (e.g., cardboard boxes or cases) in which the product is stored in the back room and the unit in which it is replenished at one time (e.g., one case of 6 x 2L PET bottles).

[0059] The generation unit 134 may generate layout information based on the store layout information stored in the storage unit 12, which indicates the equipment layout showing entrances and exits, routes, product shelf locations, and physical constraints in the target store, and the replenishment characteristics indicated by the replenishment characteristics information corresponding to each of the multiple products. For example, the generation unit 134 identifies the equipment layout showing entrances and exits, routes, product shelf locations, and physical constraints in the store based on the store layout information, and identifies the replenishment characteristics of the products based on the replenishment characteristics information stored in the storage unit 12.

[0060] The generation unit 134 then inputs information about the product shelves, information indicating multiple identified products, and information indicating products associated with priority attributes to the large-scale language model, as well as the identified equipment layout and product replenishment characteristics, and instructs the model to generate layout information that prioritizes the placement of products associated with priority attributes. In this case, the generation unit 134 may also instruct the large-scale language model to generate layout information that takes into account the equipment layout and replenishment characteristics information by instructing the large-scale language model to generate layout information that takes the equipment layout and replenishment characteristics information into account.

[0061] Furthermore, the generation unit 134 may accept a choice of whether to prioritize generating layout information that is expected to increase sales by emphasizing attribute-based layouts, or generating layout information that can reduce costs by emphasizing efficient stocking. Alternatively, the generation unit 134 may accept a ratio of emphasis between attribute-based layouts and layouts that prioritize efficient stocking, and cause a large-scale language model to generate layout information based on that ratio. In this way, the information processing device 1 can generate layout information that also takes into account efficient stocking.

[0062] The generation unit 134 may also identify similar stores with similar distributions of customer attributes, obtain layout information of the identified similar stores, and generate placement information based on that layout information. In this case, the identification unit 132 calculates the distribution of user attributes for each of the multiple stores by performing the three steps described above for each of the multiple stores. In this case, the target store may be a store that has not yet opened, and the distribution of user attributes may be calculated based on the location of the target store. The generation unit 134 then compares the distribution of attributes of the target store with the distribution of attributes of each of the multiple stores and identifies similar stores with similar attribute distributions.

[0063] In this way, when opening a new store, the information processing device 1 can generate a layout that corresponds to the distribution of user attributes around the new store, based on the layout of a similar store. The generation unit 134 may also accept attributes that are important for the new store and instruct the large-scale language model to create a layout for the new store based on the important attributes and the layout information of the similar store. In this way, the information processing device 1 can generate placement information that corresponds to the distribution of user attributes around the new store and is suitable for the strategy of the new store.

[0064] The output unit 135 outputs the layout information generated by the generation unit 134. The output unit 135 outputs the layout information generated by the generation unit 134 to the user terminal 2 that sent the layout information generation request. However, even if the output unit 135 outputs the layout information, it may not be possible to immediately change to the layout of the products indicated by the layout information due to the workload of moving product shelves, rearranging products on product shelves, or the inventory status of the products. In this case, the generation unit 134 may specify the current layout, which is the arrangement of the sales floors for multiple products in the target store at the present time.

[0065] For example, the memory unit 12 stores current placement information, which shows the current arrangement of products on the shelves, and inventory information, which shows the inventory status of multiple products. The generation unit 134 refers to the memory unit 12 to refer to the current placement information and inventory information to identify the current placement and the inventory status of multiple products. It also identifies the personnel resources required to arrange products in the target store. For example, the generation unit 134 identifies personnel resources by receiving information indicating personnel resources from the user terminal 2 via the reception unit 131.

[0066] The generation unit 134 then generates change plan information that shows a change plan to gradually change the layout of the sales floor from the current layout to the changed layout, based on the changed layout, which is the layout of the sales floors for multiple products in the target store as indicated by the generated layout information, the current layout, which is the current layout of the sales floors for multiple products in the target store, the resources of personnel responsible for arranging products in the target store, and the inventory status of multiple products.

[0067] For example, the generation unit 134 inputs the post-change layout, the current layout, personnel resources, and the inventory status of multiple products into a large-scale language model, and generates intermediate layout information that shows multiple change states of the layout information from the current layout to the post-change layout, and calculates the personnel and change time required to change to the layout information shown in each of the multiple change states. Here, the generation unit 134 instructs the large-scale language model to generate multiple intermediate layout information that can be handled with the input personnel resources and the inventory status of multiple products.

[0068] The generation unit 134 then acquires intermediate placement information and information indicating the personnel and time required to change the placement information to match the multiple change states, as change plan information. The output unit 135 outputs the placement information generated by the generation unit 134 and the change plan information. In this way, the information processing device 1 can suppress excessive load and inventory shortages that occur when changing the placement of products.

[0069] [Processing flow in Information Processing Device 1] Next, we will explain the processing flow in the information processing device 1. Figure 7 is a flowchart showing the processing flow related to the information processing device 1.

[0070] First, when the receiving unit 131 receives a request from the user terminal 2 to identify the distribution of attributes, the identification unit 132 identifies the distribution of attributes that indicate the purchasing values ​​of each of the multiple customers in the area to which the target store belongs (S1). Next, when the receiving unit 131 receives a request from the user terminal 2 to determine the priority attribute, the determination unit 133 determines the priority attribute based on the distribution of the identified attribute (S2).

[0071] Next, when the reception unit 131 receives a request from the user terminal 2 to generate placement information, the generation unit 134 acquires movement information indicating the movement of customers within the store (S3). Based on the acquired movement information, the generation unit 134 identifies the placement locations of products with priority attributes (S4).

[0072] Next, the generation unit 134 generates placement information in which products with priority attributes are preferentially placed in the specified locations (S5). Subsequently, the output unit 135 outputs the placement information generated by the generation unit 134 to the user terminal 2 (S6).

[0073] [Differentiation] In the above-described embodiment, the receiving unit 131 receives a request to specify the distribution of attributes, in which case the specifying unit 132 specifies the distribution of attributes; the receiving unit 131 receives a request to determine the priority attributes, in which case the determining unit 133 determines the priority attributes; and the generating unit 134 generates the placement information in response to a request to generate placement information. However, the embodiment is not limited to this. The receiving unit 131 may also be configured such that, upon receiving a request to generate placement information from the user terminal 2, the specifying unit 132 specifies the distribution of attributes, the determining unit 133 determines the priority attributes, and the generating unit 134 generates the placement information.

[0074] [Effects of this embodiment] As explained above, the information processing device 1 displays the purchasing values ​​of multiple customers in the area to which the target store belongs, and identifies consumer attributes related to product purchases that are attached to products. Then, based on the distribution of the identified attributes and the attributes corresponding to each of the multiple products, the information processing device 1 generates placement information showing the arrangement of multiple products in the sales area of ​​the target store, and outputs the generated placement information. In this way, the information processing device 1 can arrange products from the consumer's perspective.

[0075] Furthermore, this invention will make it possible to contribute to Goal 9 of the United Nations-led Sustainable Development Goals (SDGs), "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation."

[0076] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of its gist. For example, all or part of the apparatus can be configured by functionally or physically distributing and integrating in any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combinations are combined with the effects of the original embodiments. [Explanation of Symbols]

[0077] 1. Information Processing Device 2 User terminals 11 Communications Department 12 Storage section 13 Control Unit 131 Reception Department 132 Specific part 133 Decision Section 134 Generation part 135 Output section

Claims

1. It has a specific section that identifies the distribution of attributes indicating consumer values ​​regarding product purchases, which are held by multiple users in the area to which the target store belongs. The aforementioned attributes are attributes that are applied to both users and products. The identification unit identifies multiple users who were present in the area to which the target store belongs, based on historical information regarding the user's location, and identifies the ratio of the attributes possessed by each of the identified multiple users as the distribution of the attributes corresponding to the target store. A generation unit generates placement information indicating the arrangement of the multiple products in the sales area of ​​the target store, based on the attributes that have a relatively high proportion in the distribution of the aforementioned attributes, the attributes corresponding to each of the multiple products placed in the target store, and information regarding the sales area of ​​the target store. An output unit that outputs the arrangement information generated by the generation unit, An information processing device having

2. The system further includes a determination unit that determines, based on the distribution of the aforementioned attributes, the attributes with a relatively high proportion as priority attributes, which are the attributes that are given importance in the sale of products at the sales area. The generation unit generates placement information indicating the arrangement of a plurality of products in the sales area of ​​the target store, prioritizing the placement of products corresponding to the priority attributes determined by the determination unit. The information processing apparatus according to claim 1.

3. The identifying unit identifies the distribution corresponding to each of the multiple common stores which are multiple stores operated by a predetermined business operator, and identifies common stores whose distribution is similar to the distribution corresponding to the target store as approximate common stores. The determination unit determines the priority attribute based on the comparison result between the sales performance of the target store for each attribute and the sales performance of similar common stores for each attribute, and the distribution of attributes corresponding to each of the multiple customers in the area to which the target store belongs, as identified by the identification unit. The information processing apparatus according to claim 2.

4. The determination unit acquires policy information indicating measures related to the sale of products at the target store, which includes at least one of product information indicating products whose sales will be strengthened at the target store, and information for identifying target attributes which are the attributes of customers whose sales will be strengthened. The unit identifies an attribute from among a plurality of attributes relating to consumer purchasing that corresponds to at least one of the products whose sales will be strengthened and the target attributes indicated by the policy information, and further determines the priority attribute based on the identified attribute. The information processing apparatus according to claim 2.

5. The generation unit acquires movement information indicating the movement of customers who visit the target store as information about the sales floor of the target store, identifies locations in the sales floor that customers frequently view based on the movement information, and generates placement information in which products with the priority attributes are preferentially placed in the identified locations. The information processing apparatus according to claim 2.

6. The generation unit refers to shelf-specific sales information as information about the sales floor of the target store, which associates the location of each of the multiple product shelves in the target store with the sales of each of the multiple attributes on the product shelf, identifies the location of the product shelf where the sales of the product corresponding to the priority attribute are relatively high, and generates the arrangement information which arranges the product shelf with the product corresponding to the priority attribute at the identified location. The information processing apparatus according to claim 2.

7. The generation unit acquires store structure information indicating the location of fixed equipment in the target store as information related to the sales floor of the target store, identifies attributes pre-associated with the fixed equipment, and generates the arrangement information based on the location of the fixed equipment and the attributes corresponding to the identified fixed equipment. The information processing apparatus according to claim 1.

8. The generation unit generates multiple layout plans for the multiple products in the sales area of ​​the target store based on the distribution of the attributes identified by the identification unit, the attributes corresponding to each of the multiple products, and information regarding the sales area of ​​the target store. Using customer flow information that indicates the flow of customers in the target store, the generation unit simulates the sales or customer dwell time for each of the multiple layout plans when the multiple products are placed in the target store, and generates information as layout information that indicates the layout plan with relatively high sales or customer dwell time in the target store. The information processing apparatus according to claim 1.

9. The generation unit further generates change plan information that indicates a change plan to gradually change the layout of the sales floor from the current layout to the changed layout, based on the changed layout, which is the layout of the sales floors for the multiple products in the target store as indicated by the generated layout information, the current layout, which is the current layout of the sales floors for the multiple products in the target store, the resources of personnel responsible for arranging the products in the target store, and the inventory status of the multiple products. The output unit outputs the change plan information. The information processing apparatus according to claim 1.

10. It has a storage unit that stores replenishment characteristic information, which is the replenishment characteristic of each of several products, and store layout information, which includes information showing the arrangement of equipment in the sales area of ​​the target store. The generation unit generates arrangement information indicating the arrangement of the multiple products in the sales area of ​​the target store, based on the equipment arrangement indicated by the store layout information as information relating to the sales area of ​​the target store, and the replenishment characteristics indicated by the replenishment characteristics information corresponding to each of the multiple products. The information processing apparatus according to claim 1.

11. A computer executes The process includes a step of identifying the distribution of attributes that indicate consumer values ​​regarding product purchases, which are held by multiple users in the area to which the target store belongs. The aforementioned attributes are attributes that are applied to both users and products. In the aforementioned identification step, the computer identifies multiple users who were present in the area to which the target store belongs, based on historical information regarding the user's location, and identifies the ratio of the attributes possessed by each of the identified multiple users as the distribution of the attributes corresponding to the target store. The aforementioned computer executes, A step of generating placement information indicating the arrangement of the multiple products in the sales area of ​​the target store, based on the attributes that have a relatively high proportion in the distribution of the attributes, the attributes corresponding to each of the multiple products placed in the target store, and information regarding the sales area of ​​the target store. The steps include outputting the generated arrangement information, An information processing method having

Images