Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method, and an information processing program that can perform more accurate analysis of a trade area.SOLUTION: An information processing device according to the present application includes a reception unit, an analysis unit, and a provision unit. The reception unit receives designation of a plurality of stores. The analysis unit performs estimation processing of estimating a trade area of each of the plurality of stores whose designation has been received by the reception unit, and comparison processing of comparing trade area information between the plurality of stores based on the trade area information of each of the plurality of stores estimated by the estimation processing. The provision unit provides map information including information indicating the trade area of each of the plurality of stores estimated by the estimation processing and information indicating the comparison result of the comparison processing.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Conventionally, a business district analysis for formulating a business strategy in a store has been performed. For example, Patent Document 1 proposes a technique for analyzing a business district specified from a client device.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above prior art, although the business district can be analyzed, it is limited to the analysis of one business district specified from the client device, and there is room for further improvement.

[0005] The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program capable of more accurately analyzing a business district.

Means for Solving the Problems

[0006] The information processing apparatus according to the present application includes a reception unit, an analysis unit, and a provision unit. The reception unit receives designations of a plurality of stores. The analysis unit performs an estimation process of estimating the business district of each of the plurality of stores designated by the reception unit, and a comparison process of comparing the business district information between the plurality of stores based on the business district information of each of the plurality of stores estimated by the estimation process. The provision unit provides map information including information indicating the business district of each of the plurality of stores estimated by the estimation process and information indicating the comparison result of the comparison process. [Effect of the Invention]

[0007] According to one aspect of the embodiment, there is an effect that the analysis of the business area can be performed more accurately. [Brief Description of the Drawings]

[0008]

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[0009] Hereinafter, embodiments for implementing the information processing apparatus, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited by this embodiment. Also, each embodiment can be appropriately combined within a range that does not conflict with the processing content. In the following embodiments, the same parts are denoted by the same reference numerals, and redundant descriptions are omitted.

[0010] 〔1. An Example of Information Processing〕 First, an example of the information processing according to the embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram for explaining the information processing according to the embodiment.

[0011] The information processing apparatus 1 shown in FIG. 1 is an information processing apparatus that cooperates with the terminal device 2 of the service user O and provides various services to the service user O online, and is realized by, for example, one or more servers or a cloud system. The terminal device 2 is, for example, a smartphone, a tablet, or a personal computer.

[0012] The service provided to the service user O by the information processing apparatus 1 is, for example, a store business district related analysis service, and for example, transmits map information in which information on the business district of the store designated by the service user O is arranged to the terminal device 2 of the service user O.

[0013] As shown in FIG. 1, the information processing apparatus 1 receives a designation of a plurality of stores by the service user O (step S1). For example, when the information processing apparatus 1 receives a business district comparison information request that includes a plurality of store information indicating a plurality of stores designated by the service user O and is transmitted from the terminal device 2, based on the plurality of store information included in the business district comparison information request, the information processing apparatus 1 receives a designation of a plurality of stores by the service user O. In the following, each of the plurality of stores designated in step S1 may be described as a designated store.

[0014] Service user O, for example, operates the terminal device 2 to send a usage request from the terminal device 2 to the information processing device 1. The usage request includes, for example, information indicating a position specified by the service user O or information indicating a region specified by the service user O. Hereinafter, the region including the position specified by the service user O or the region specified by the service user O may be described as a specified region.

[0015] When the information processing device 1 receives the usage request sent from the terminal device 2, it sends to the terminal device 2 store designation information including list information indicating a list of stores existing in the specified region and map information of the specified region.

[0016] When the terminal device 2 receives the store designation information sent from the information processing device 1, it displays, based on the received store designation information, list information indicating a list of stores existing in the specified region and map information of the specified region. In the list information, each store existing in the specified region is arranged in a list format so as to be individually specifiable, and in the map information of the specified region, store graphics indicating the positions of the respective stores existing in the specified region are arranged on the map so as to be individually specifiable.

[0017] Service user O can specify two or more stores to be analyzed among the plurality of stores included in the list information displayed on the terminal device 2, and can specify the store graphic corresponding to the store to be analyzed among the plurality of store graphics included in the map information displayed on the terminal device 2.

[0018] When there is a specification of two or more stores or two or more store graphics by the service user O, the terminal device 2 sends to the information processing device 1 a trade area comparison information request including, as store information, information indicating the two or more stores specified by the service user O or information indicating the stores corresponding to the two or more store graphics specified by the service user O. Note that the specification by the service user O may be a combination of one or more stores and one or more store graphics.

[0019] Next, the information processing apparatus 1 performs an estimation process of estimating the business areas of each of the plurality of designated stores that received the designation in step S1, and a comparison process of comparing the business area information between the plurality of designated stores based on the business area information of each of the plurality of designated stores estimated by the estimation process (step S2).

[0020] For example, in the estimation process, the information processing apparatus 1 performs, for each designated store, a process of estimating the business area of the designated store based on the information of the users of the designated store. The user of the designated store is a user who has at least one history among visits to the designated store, purchases of goods at the designated store, and use of services at the designated store, but is not limited to such an example. For example, a user whose average stay time at the designated store is longer than a predetermined period may also be used. Hereinafter, the user of the designated store may be referred to as a store user in some cases.

[0021] The information of the store user includes, for example, information indicating the stay location of the store user or information indicating the location history of the store user. The information indicating the stay location of the store user is, for example, information indicating the latitude and longitude of the stay location of the store user, but may also be information indicating the address.

[0022] The stay location of the store user is, for example, a place where the store user habitually stays, such as the residence of the store user or the workplace of the store user. Note that the stay location of the store user may be a place where the store user stays temporarily, such as a lodging facility of the store user or a gaming facility visited by the store user.

[0023] In addition, the information of the store user may further include one or more pieces of information among, for example, information indicating the attributes of the store user, information indicating the usage history of the designated store by the store user, information indicating the facilities used by the store user, information indicating the transportation means used by the store user, and information indicating the location history of the store user.

[0024] Information indicating the attributes of store users includes demographic attributes and psychographic attributes of store users. Demographic attributes are, for example, gender, age, place of residence, place of work, and occupation, etc., and psychographic attributes are interests such as travel, clothing, cars, religion, lifestyle, life stage, purchase intention, thoughts and trends of thoughts, etc.

[0025] The usage history of the designated store by store users is, for example, each payment amount and average payment amount of store users, the content and genre of purchased goods and services by store users, each stay time and average stay time of store users, etc., but is not limited to such examples.

[0026] In the estimation process, for example, the information processing device 1 estimates the business area of the designated store based on the information indicating the stay location of each store user. For example, the information processing device 1 estimates the business area of the designated store using an estimation method such as kernel density estimation based on the stay location of each store user. The information processing device 1 estimates, for example, one or more areas where the density is equal to or greater than a predetermined value as the business area of the designated store.

[0027] Also, in the estimation process, the information processing device 1 determines, for example, whether the number of store users is equal to or greater than a predetermined number for each predetermined unit area, and the information processing device 1 can also estimate the set of unit areas where the number of store users is equal to or greater than the predetermined number as the business area of the designated store.

[0028] The information indicating the stay location of store users is information indicating the place of residence set by the store user or information indicating the place of work set by the store user, etc., but the information processing device 1 can estimate the information indicating various stay locations of store users based on the information indicating the location history of store users.

[0029] For example, based on information indicating the location history of a store user, the information processing apparatus 1 can estimate the place of residence of the store user, the place of work of the store user, the place where the store user stayed temporarily, etc. from the staying patterns at each location of the store user. In the following, the business area of a designated store estimated in the estimation process may be referred to as the designated store business area.

[0030] In addition, the information processing apparatus 1 can also estimate the designated store business area based on information of store users satisfying specific conditions. For example, when the information indicating specific conditions is included in the business area comparison information request received in step S1, the information processing apparatus 1 estimates the designated store business area from the staying places of store users satisfying the specific conditions indicated in the business area comparison information request.

[0031] The specific conditions are, for example, the attributes of the store user, the type of the staying place of the store user, the attributes of the store user, the facilities used by the store user, the means of transportation used by the store user, the purchase of specific goods or the use of specific services by the store user at the designated store, the average staying time of the store user at the designated store, etc., but are not limited to such examples.

[0032] In the comparison process, the information processing apparatus 1 compares the business area information among a plurality of designated stores based on the business area information of each of the plurality of designated stores. The information processing apparatus 1 can, for example, determine the degree of overlap of the business areas between the designated stores or the differences in the business areas between the designated stores in the comparison process. Also, the information processing apparatus 1 can, for example, determine the differences between the business area of a designated store and a general business area in the comparison process.

[0033] The information on the business area of the designated store is information indicating the business area of the designated store, information on the store users of the designated store in the business area of the designated store, etc. The information on the store users in the business area of the designated store includes, for example, information indicating the attributes of the store users, information indicating the usage history of the designated store by the store users, information indicating other stores and facilities used by the store users, information indicating the means of transportation used by the store users, and one or more pieces of information from the information indicating the location history of the store users.

[0034] The usage history of a designated store by a store user is, for example, each payment amount or average payment amount of the store user, the content and genre of the purchased goods and services of the store user, each stay time or average stay time of the store user, etc., but is not limited to such examples.

[0035] In the comparison process, the information processing device 1 determines, for example, the common points and differences of the user layers among a plurality of designated stores. For example, in the comparison process of the information of the business circles among the designated stores, the information processing device 1 can determine one or more common points and differences among the attributes of the store users, the genre of the purchased goods, the average payment amount, the average stay time, hobbies and preferences, used facilities, other used stores, used transportation means, etc. among the plurality of designated stores.

[0036] For example, in the comparison process, the information processing device 1 estimates the main user layer of each designated store and compares the estimated user layers. The main user layer of a designated store is determined by, for example, one or more elements among the attributes of the store user, the genre of the purchased goods, the average payment amount, the average stay time, hobbies and preferences, used facilities, other used stores, used transportation means, etc.

[0037] Also, in the comparison process, the information processing device 1 can determine the ratio of store users common among a plurality of designated stores or the ratio of different store users. In such a process, the information processing device 1 can determine the ratio of store users common among a plurality of designated stores for each attribute of the store user (for example, one or more combinations of a plurality of attribute items such as gender, age, place of residence, occupation, etc.).

[0038] Also, the information processing device 1 can determine, for example, the common points and differences between the business circles of a plurality of designated stores, the overlap of store users among a plurality of designated stores, etc. in the comparison process. For example, in the comparison process, the information processing device 1 determines, as the common points and differences between the business circles of a plurality of designated stores, the degree of overlap between the business circles of a plurality of designated stores, the common points and differences in the shapes of the business circles of a plurality of designated stores, etc.

[0039] In addition, in the comparison process, the information processing apparatus 1 can also determine, for example, the common points and differences in the behaviors of store users before and after visiting the store among the designated stores. For example, the information processing apparatus 1 determines the common points and differences in the genres of facilities and other stores that store users often visit before and after visiting the designated stores among the designated stores.

[0040] In addition, in the comparison process, the information processing apparatus 1 can compare the information on the business circles of a plurality of designated stores based on the information of the plurality of designated stores in addition to the information on the business circles of each of the plurality of designated stores.

[0041] The information of a plurality of designated stores is, for example, information indicating the positions of each of the plurality of designated stores, information indicating the products sold at each of the plurality of designated stores, and information indicating the genres of each of the plurality of designated stores.

[0042] In the comparison process, the information processing apparatus 1 can determine, for example, the common points and differences among a plurality of designated stores based on the information of the plurality of designated stores. For example, the information processing apparatus 1 can determine whether a plurality of designated stores are competing stores or collaborative stores based on the information on the business circles of the designated stores.

[0043] In addition, in the comparison process, the information processing apparatus 1 can also use, in addition to the above-described information, geographical information of the designated store business circle, etc. The geographical information is, for example, information indicating the terrain, information indicating the passageway, information indicating the route of public institutions, information indicating traffic regulations and signs, news article information, disaster information, facility and store information, weather information, etc., but is not limited to such examples.

[0044] For example, in the comparison process, the information processing apparatus 1 can determine the common points and differences in the geographical characteristics of the business circles among a plurality of designated stores based on the geographical relationship between the designated store and the designated store business circle. The geographical relationship between the designated store and the designated store business circle is the positional relationship between the designated store and the designated store business circle, the distance and terrain between the designated store and each position of the designated store business circle, etc., but is not limited to such examples.

[0045] The positional relationship between the designated store and the designated store business district is, for example, the shape of the designated store business district as seen from the designated store, the position of the designated store relative to the designated store business district, etc., but is not limited to such examples. The distance between the designated store and each position in the designated store business district is, for example, the moving distance between the designated store and each position in the designated store business district, but may also be the straight-line distance between the designated store and each position in the designated store business district. Also, the terrain between the designated store and each position in the designated store business district is, for example, the magnitude, number, length, and number of curves of the gradient of the moving path to the designated store, etc., but is not limited to such examples.

[0046] The information processing device 1 performs the above-described estimation processing and comparison processing using a generative AI (Artificial Intelligence). The generative AI is, for example, a text generation AI. The text generation AI is, for example, a large language model trained to estimate and output the next token from the input token sequence, and is, for example, a Transformer-based model, an RNN (Recurrent Neural Network)-based model, etc., but may also be a hybrid model thereof. Also, the text generation AI may be a composite system combined with an identification mechanism for preventing unauthorized use.

[0047] The Transformer-based model is, for example, GPT (Generative Pre-trained Transformer) (registered trademark), PaLM2 (Pathways Language Model Version 2), or LLaMA (Large Language Model Meta AI), etc., but is not limited to such examples. The RNN-based model is, for example, RWKV (Receptance Weighted Key Value), etc., but is not limited to such examples.

[0048] Note that it is desirable for the generative AI to be trained so that its generated results do not include personal information or the like. The generative AI is arranged in an external information processing device, and the information processing device 1 uses the generative AI via an API (Application Programming Interface), but the generative AI may also be arranged within the information processing device 1.

[0049] The input information input to the generative AI is called a prompt. In the following, the input information input to the generative AI may be described as a prompt. A prompt is, for example, information indicating instructions, requests, etc. given to the generative AI to perform a specific task.

[0050] The information processing device 1 inputs a prompt including, for example, instruction information for estimating the business areas of each of a plurality of designated stores and comparing the estimated business areas of the plurality of stores, and information necessary for estimating the business areas of the designated stores and comparing the business areas of the designated stores to the generative AI, and causes the generative AI to output the business areas of the designated stores and the comparison results between the business areas of the designated stores.

[0051] The information necessary for estimating the business areas of the designated stores and comparing the business areas of the designated stores includes, for example, the above-described information used in the estimation process and the comparison process, but is not limited to such examples.

[0052] As information necessary for the estimation process of the business areas of the designated stores using the generative AI, the information processing device 1 uses, for example, instruction information for instructing the estimation of the business areas of the designated stores based on the information of the store users (for example, information indicating the staying places of the store users such as the residential areas and workplaces of the store users). Such instruction information is, for example, information indicating an instruction to estimate one or more areas with a density equal to or higher than a predetermined value as the business area of the designated store based on the information of the store users, or information indicating an instruction to estimate one or more areas with a density equal to or higher than a predetermined value estimated using an estimation method such as kernel density estimation as the business area of the designated store based on the information of the store users, etc., but is not limited to such examples.

[0053] In the comparison process using the generative AI, the information processing apparatus 1 uses instruction information for instructing the comparison of the information of the designated store's business district based on the information of the business district of the designated store. For example, the information processing apparatus 1 can cause the generative AI to output information indicating the common points and differences of the user layers among a plurality of designated stores by using instruction information for instructing the comparison of the user layers among the plurality of designated stores.

[0054] The instruction information for instructing the comparison of the user layers among a plurality of designated stores may include information specifying one or more elements used for comparison among, for example, the attributes of store users, the genre of purchased goods, the average payment amount, the average stay time, hobbies and preferences, facilities used, other stores used, and transportation means used.

[0055] Also, in the comparison process using the generative AI, the information processing apparatus 1 uses instruction information for instructing the determination of the ratio of store users common among a plurality of designated stores or the ratio of different store users by comparing store users among a plurality of designated stores, and can cause the generative AI to output information indicating the ratio of store users common among a plurality of designated stores or the ratio of different store users.

[0056] Also, in the comparison process using the generative AI, the information processing apparatus 1 uses instruction information for instructing the determination of the most common attribute among the attributes (for example, one or more combinations of a plurality of attribute items such as gender, age, place of residence, occupation, etc.) of store users common among a plurality of designated stores by comparing store users among a plurality of designated stores, and can cause the generative AI to output information indicating the attributes of store users common among a plurality of designated stores.

[0057] Also, in the comparison process using the generative AI, the information processing apparatus 1 uses instruction information for instructing the determination of the common points and differences between the business districts of a plurality of designated stores by comparing the business districts of a plurality of designated stores, and can cause the generative AI to output information indicating the common points and differences between the business districts of a plurality of designated stores. In this case, the instruction information may include information specifying the overlap between the business districts of a plurality of designated stores and the shape of the business districts of a plurality of designated stores as the objects for determining the common points and differences between the business districts of a plurality of designated stores.

[0058] In the comparison process using the generative AI, the information processing apparatus 1 can also use instruction information for instructing the comparison of the information of the designated store's business district based on the information of a plurality of designated stores in addition to the information of the business district of the designated store.

[0059] For example, in the comparison process using the generative AI, the information processing apparatus 1 can cause the generative AI to output information indicating the common points and differences among a plurality of designated stores by using instruction information for instructing the determination of the common points and differences among a plurality of designated stores through the comparison of the information among the plurality of designated stores.

[0060] For example, in the comparison process using the generative AI, the information processing apparatus 1 can cause the generative AI to output information indicating the common points and differences in the geographical relationship with the designated stores among the business districts of a plurality of designated stores by using instruction information for instructing the determination of the common points and differences in the geographical relationship with the designated stores among the business districts of a plurality of designated stores.

[0061] The instruction information includes, for example, information for instructing the summarization of the comparison results, information for naming a title for the summary of the comparison results, information for instructing the output of the title and the summarized content, and the like. Thereby, in the comparison process, the generative AI can be caused to output information that concisely shows the comparison results between the designated store business districts with a title.

[0062] For example, the information processing apparatus 1 can input the prompt shown in FIG. 1 to the generative AI and cause the generative AI to output the estimation result of the designated store business district and the comparison between the designated store business districts. The instruction information of the prompt shown in FIG. 1 includes information of the output format that defines how to output the comparison results between the estimated business districts, that is, the information of the character string "name a title for the summary and output the title and the summarized content".

[0063] Although not shown, the instruction information of the prompt shown in FIG. 1 includes information indicating an instruction to output an estimated business area. For example, the instruction information of the prompt shown in FIG. 1 may include information such as the information of the character string "Output the density value of users in the estimated business area in a list format for each location.", but is not limited to such an example.

[0064] In addition, the information processing apparatus 1 can also perform the estimation process and the comparison process separately by inputting the prompt of the estimation process and the prompt of the comparison process into the generation AI separately. In this case, the prompt of the comparison process includes information indicating the position of the designated store business area estimated by the estimation process.

[0065] In addition, instead of using the generation AI, the information processing apparatus 1 can also estimate the designated store business area by statistical processing. For example, the information processing apparatus 1 aggregates the number of store users for each predetermined unit area based on the information indicating the stay locations of a plurality of store users, and estimates the designated store business area based on such aggregation results.

[0066] The information processing apparatus 1 can, for example, estimate one or more areas with a density equal to or higher than a predetermined value as the business area of the designated store, or estimate one or more areas with a density equal to or higher than a predetermined value estimated using an estimation method such as kernel density estimation as the business area of the designated store.

[0067] In addition, instead of using the generation AI, the information processing apparatus 1 can also compare the information between the designated store business areas by statistical processing. For example, the information processing apparatus 1 can determine the main user layer of each designated store business area based on one or more pieces of information such as the attributes of store users, the genre of purchased goods, the average payment amount, the average stay time, hobbies, and preferences.

[0068] In addition, the information processing apparatus 1 can determine the ratio of store users common to a plurality of designated stores or the ratio of different store users by statistical processing using the information of store users of a plurality of designated stores. The comparison of the information between the designated store business areas by statistical processing is not limited to the above-described examples.

[0069] Further, for example, the information processing apparatus 1 can input a prompt including processing definition information, instruction information, and information necessary for estimation for extracting a processing type and processing target information to the generative AI, and acquire, from the generative AI, processing information including information indicating the processing type and the processing target information as output information.

[0070] The information processing apparatus 1 can perform a process corresponding to the processing type indicated by the information indicating the processing type using the processing target information, for example, by specific arithmetic processing or statistical processing. The processing type is, for example, business area estimation, business area comparison, etc., but is not limited to such examples. Business area estimation is a process of estimating a designated store business area, and business area comparison is a process of comparing characteristics and features between designated store business areas.

[0071] The generative AI extracts and outputs, as the processing target information, the information necessary for the process indicated by the processing type among the various types of information included in the prompt. For example, when the processing type is business area estimation, the generative AI extracts and outputs, as the processing target information, the information necessary for estimating the designated store business area among the various types of information included in the prompt. The information necessary for estimating the designated store business area is, for example, the information described above.

[0072] Further, when the processing type is business area comparison, the generative AI extracts and outputs, as the processing target information, the information necessary for comparing the information between the designated store business areas among the various types of information included in the prompt. The information necessary for comparing the information between the designated store business areas is, for example, the information described above.

[0073] For example, when the generative AI is GPT of OpenAI, the information processing apparatus 1 can cause the generative AI to output the processing information as the output information using the function of function calling for the output information of the generative AI.

[0074] The generative AI may be a multimodal generative AI or the like. The multimodal generative AI is, for example, a generative AI that generates at least one of text, images, and audio from at least one of text, images, and audio. The multimodal generative AI is, for example, GPT-4 Turbo with vision, gemini, CM3Leon (Chameleon Multimodal Model), etc., but is not limited to such examples.

[0075] In this case, the information processing apparatus 1 further inputs, as input information, instruction information indicating an instruction to draw the estimated designated store business district on the map and map information indicating the map of the area including the designated store to the generative AI, so that map information showing the designated store business district on the map can be output from the generative AI.

[0076] Also, the information processing apparatus 1 can receive the designation of a strategic target store and a plurality of comparison target stores by the service user O. The strategic target store is a store for which the service user O desires to formulate a strategic proposal with respect to the information processing apparatus 1, and the comparison target stores are stores that the service user O wants to consider when formulating a strategic proposal.

[0077] For example, when the information processing apparatus 1 receives a strategic proposal information request transmitted from the terminal device 2 and including a plurality of store information indicating the strategic target store and the plurality of comparison target stores designated by the service user O, the information processing apparatus 1 accepts the designation of the strategic target store and the plurality of comparison target stores by the service user O based on the plurality of store information included in the strategic proposal request.

[0078] When the information processing apparatus 1 accepts the designation of a strategic target store and a plurality of comparison target stores by the service user O, it can also determine a strategic proposal based on the differences in the user layers among the plurality of designated stores. The strategic proposal is, for example, an aggressive strategy (raising price or quality to capture share from competitors), a niche strategy (finding a niche in the customer segment to expand share), a collaboration strategy (aiming to acquire customers and increase sales through collaboration with other stores), etc., but is not limited to such examples.

[0079] When the information processing apparatus 1 receives, for example, the designation of a strategic target store and a plurality of comparison target stores by the service user O, it performs the above-described estimation process of estimating the business areas of each of the strategic target store and the plurality of comparison target stores, and based on the information on the business areas of each of the strategic target store and the plurality of comparison target stores estimated by the estimation process, performs a strategy formulation process of formulating a strategy for the strategic target store.

[0080] In the strategy proposal process, the information processing apparatus 1 makes a strategy proposal for the strategic target store based on the information on the business areas of each of the strategic target store and the plurality of comparison target stores. For example, in the strategy proposal process, the information processing apparatus 1 can perform a comparison process similar to the above-described comparison process. For example, in the strategy proposal process, the information processing apparatus 1 makes a strategy proposal for the strategic target store based on the above-described comparison process.

[0081] The information processing apparatus 1 inputs a prompt for performing the estimation process and the strategy formulation process to the generative AI, and causes the generative AI to output the results of the estimation process and the strategy formulation process. Further, the information processing apparatus 1 can also perform the estimation process and the strategy formulation process individually by inputting the prompt for the estimation process and the prompt for the strategy formulation process to the generative AI individually. In this case, the prompt for the strategy formulation process includes information indicating the position of the designated store business area estimated by the estimation process.

[0082] Further, the information processing apparatus 1 can perform a process corresponding to the process type indicated by the information indicating the process type using the process target information, for example, by specific arithmetic processing or statistical processing. The process type is, for example, business area estimation, business area comparison, strategy formulation process, etc., but is not limited to such examples. Note that the information processing apparatus 1 can also estimate the designated store business area by statistical processing instead of using the generative AI.

[0083] Subsequently, the information processing apparatus 1 provides map information including information indicating a plurality of designated store business areas estimated in step S2 and information indicating a comparison result between the information of the plurality of designated store business areas (step S3). For example, the information processing apparatus 1 provides the service user O with map information including information indicating a plurality of designated store business areas and information indicating a comparison result between the information of the plurality of designated store business areas by transmitting the map information including the information indicating a plurality of designated store business areas and the information indicating a comparison result between the information of the plurality of designated store business areas to the terminal device 2.

[0084] Also, when the estimation process and the strategy formulation process are performed in step S2, the information processing apparatus 1 provides map information including information indicating the business areas of each of the strategic target stores and the plurality of comparison target stores estimated in step S2 and information indicating the result of the strategy formulation for the strategic target stores. The result of the strategy formulation for the strategic target stores includes information indicating a strategic proposal for the strategic target stores, and may further include the result of the comparison process.

[0085] For example, the information processing apparatus 1 provides the service user O with map information including information indicating the business areas of a plurality of stores including the strategic target store and the plurality of comparison target stores and information indicating a strategic proposal for the strategic target store by transmitting the map information including the information indicating the business areas of a plurality of stores including the strategic target store and the plurality of comparison target stores and the information indicating a strategic proposal for the strategic target store to the terminal device 2.

[0086] The information processing apparatus 1 provides, as map information, information in a state where the business areas of each designated store estimated in step S2 are highlighted in different manners (for example, the color of the area of the business area, the color of the frame surrounding the area of the business area, etc.) on the map.

[0087] In this way, the information processing apparatus 1 receives the designation of a plurality of stores, performs estimation processing for estimating the business area of each of the plurality of stores that have received the designation, and based on the information on the business area of each of the plurality of stores estimated by the estimation processing, performs comparison processing for comparing the information on the business areas between the plurality of stores, and provides map information including information indicating the business area of each of the plurality of stores estimated by the estimation processing and information indicating the comparison result of the comparison processing. As a result, the information processing apparatus 1 can perform more accurate analysis of business areas. Therefore, the service user O can grasp the comparison result of the business areas between the designated stores, and according to the comparison result of the business areas between the designated stores, for example, the difference in the user layers between the designated stores, the overlap and differences in the business areas between the designated stores, the grasp of cannibalization and tips between the designated stores (for example, between chain stores), the grasp of competition and cooperation between the designated stores, etc., and can grasp appropriate analysis results of the business areas.

[0088] Hereinafter, the configuration of the information processing system including the information processing apparatus 1 and the terminal apparatus 2 that perform such processing will be described in detail.

[0089] 〔2. Configuration of Information Processing System〕 FIG. 2 is a diagram showing an example of the configuration of the information processing system according to the embodiment. As shown in FIG. 2, the information processing system 100 according to the embodiment includes an information processing apparatus 1 and a plurality of terminal apparatuses 2.

[0090] The plurality of terminal apparatuses 2 are used by different service users O. The terminal apparatus 2 is, for example, a notebook PC (Personal Computer), a desktop PC, a smartphone, a tablet PC, or a wearable device. The wearable device is, for example, smart glasses or a smartwatch, but is not limited to such examples.

[0091] Each of the information processing apparatus 1 and the terminal apparatus 2 is connected to be communicable with each other by wire or wirelessly via the network N. Note that the information processing system 100 shown in FIG. 2 may include a plurality of information processing apparatuses 1 and the like.

[0092] The network N includes, for example, a WAN (Wide Area Network) such as the Internet and a mobile communication network such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation: the 5th generation mobile communication system), but is not limited to such examples.

[0093] The terminal device 2 can be connected to the network N via a mobile communication network, short-range wireless communication such as Bluetooth (registered trademark), or a wireless LAN (Local Area Network), and communicate with the information processing device 1 and the like.

[0094] [3. Configuration of the information processing device 1] FIG. 3 is a diagram showing an example of the configuration of the information processing device 1 according to the embodiment. As shown in FIG. 3, the information processing device 1 includes a communication unit 10, a storage unit 11, and a processing unit 12.

[0095] [3.1. Communication unit 10] The communication unit 10 is realized by, for example, a communication module or a NIC (Network Interface Card). The communication unit 10 is connected to the network N by wire or wirelessly, and transmits and receives information to and from various other devices. For example, the communication unit 10 transmits and receives information to and from the terminal device 2 via the network N.

[0096] [3.2. Storage unit 11] The storage unit 11 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 11 includes a user information storage unit 20, a store information storage unit 21, a geographical information storage unit 22, and a content storage unit 23.

[0097] [3.2.1. User information storage unit 20] The user information storage unit 20 stores user information including information about the user. FIG. 4 is a diagram showing an example of a user information table stored in the user information storage unit 20 of the information processing apparatus 1 according to the embodiment. As shown in FIG. 4, the user information table stored in the user information storage unit 20 includes items such as "user ID", "attribute information", and "behavior history".

[0098] The "user ID" is identification information for identifying the user. The "attribute information" is attribute information of the user corresponding to the "user ID", and includes, for example, information on psychographic attributes and information on demographic attributes. Demographic attributes are, for example, gender, age, place of residence, place of work, and occupation, and psychographic attributes are objects of interest such as travel, clothing, cars, religion, lifestyle, life stage, purchase intention, thoughts and trends of thoughts, and the like.

[0099] The "behavior history" is information indicating the behavior history of the user corresponding to the "user ID", and includes, for example, information indicating the user's location history, information indicating the user's store usage history, information indicating the user's facility usage history, information indicating the user's transportation usage history, and the like, but is not limited to such examples.

[0100] The information indicating the user's store usage history includes, for example, each payment amount and average payment amount of the user in the store, information indicating the user's settlement history outside the store, the content and genre of the purchased goods and services of the user in the store, each stay time and average stay time of the user in the store, and the like, but is not limited to such examples.

[0101] [3.2.2. Store Information Storage Unit 21] The store information storage unit 21 stores information on various stores. FIG. 5 is a diagram showing an example of a store information table stored in the store information storage unit 21 of the information processing apparatus 1 according to the embodiment. As shown in FIG. 5, the store information table stored in the store information storage unit 21 includes items such as "store ID", "store location", "store name", "store type", and "product information".

[0102] The "store ID" is identification information for identifying a store. The "store location" is information indicating the location of the store corresponding to the "store ID", for example, information indicating the latitude and longitude of the store. The "store name" is information indicating the name of the store corresponding to the "store ID". When the store is a chain store, it includes information indicating the chain store name. When the store is a franchise store, it includes information indicating the franchise store name.

[0103] The "store type" is information indicating the type of the store corresponding to the "store ID", for example, information indicating the genre of the store. The "product information" is information about the products of the store corresponding to the "store ID".

[0104] Although not shown in the figure, the store information storage unit 21 may include information indicating the sales of the store, information indicating the sales floor area of the store, information indicating the number of employees of the store, and the like.

[0105] 〔3.2.3. Geographic Information Storage Unit 22〕 The geographic information storage unit 22 stores geographic information. The geographic information is, for example, information indicating terrain, information indicating passageways, information indicating routes of public institutions, information indicating traffic regulations and signs, information of news articles, information of disasters, information of facilities and stores, weather information, etc., but is not limited to such examples.

[0106] 〔3.2.4. Content Storage Unit 23〕 The content storage unit 23 stores various contents. The contents stored in the content storage unit 23 are, for example, information indicating news articles, posting information to SNS (Social Network Service) regarding the store, posting information to communication services regarding the store, traffic information of each region, advertisement information of the store, etc., but is not limited to such examples.

[0107] 〔3.3. Processing Unit 12〕 The processing unit 12 is a controller, which is realized, for example, by a processor such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), when various programs (corresponding to an example of an information processing program) stored in a storage device inside the information processing apparatus 1 are executed with a RAM or the like as a work area.

[0108] Also, the processing unit 12 is a controller, and part or all of it may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a GPGPU (General Purpose Graphic Processing Unit).

[0109] As shown in FIG. 3, the processing unit 12 includes an acquisition unit 30, a reception unit 31, an analysis unit 32, and a provision unit 33, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the processing unit 12 is not limited to the configuration shown in FIG. 3, and any other configuration may be used as long as it can perform the information processing described later.

[0110] [3.3.1. Acquisition Unit 30] The acquisition unit 30 acquires various information from an external information processing apparatus, a terminal device 2, etc. via the network N and the communication unit 10.

[0111] For example, the acquisition unit 30 acquires user information from an external information processing apparatus and stores the acquired user information in the user information storage unit 20. Also, the acquisition unit 30 acquires store information from an external information processing apparatus and stores the acquired store information in the store information storage unit 21.

[0112] In addition, the acquisition unit 30 acquires geographical information from an external information processing device and stores the acquired geographical information in the geographical information storage unit 22. Further, the acquisition unit 30 acquires various contents from an external information processing device and stores the acquired various contents in the content storage unit 23.

[0113] In addition, the acquisition unit 30 acquires various information from the storage unit 11. For example, the acquisition unit 30 acquires user information from the user information storage unit 20, acquires store information from the store information storage unit 21, acquires geographical information from the geographical information storage unit 22, and acquires contents from the content storage unit 23.

[0114] 〔3.3.2. Reception Unit 31〕 The reception unit 31 receives various information. For example, the reception unit 31 receives a usage request transmitted from the terminal device 2. The usage request includes, for example, information indicating a position specified by the service user O or information indicating a specified area that is an area specified by the service user O.

[0115] In addition, the reception unit 31 receives the designation of a plurality of stores. For example, the reception unit 31 receives the designation of stores by the service user O by receiving a business area comparison information request that includes information indicating the designation of a plurality of stores by the service user O and is transmitted from the terminal device 2.

[0116] In addition, the reception unit 31 receives the designation of a strategic target store and a plurality of comparison target stores by the service user O. The strategic target store is a store for which the service user O desires to formulate a strategic proposal for the information processing device 1, and the comparison target store is a store that the service user O desires to consider when formulating a strategic proposal.

[0117] When the reception unit 31 receives a strategic proposal information request that includes multiple store information indicating, for example, the strategic target store designated by the service user O and multiple comparison target stores and is transmitted from the terminal device 2, it accepts the designation of the strategic target store and the multiple comparison target stores by the service user O based on the multiple store information included in the strategic proposal request.

[0118] [3.3.3. Analysis Unit 32] The analysis unit 32 performs various analyses. The analyses include estimation and comparison. For example, the analysis unit 32 performs an estimation process of estimating the business area of each of the multiple designated stores, which are the multiple stores designated by the reception unit 31, and a comparison process of comparing the business area information between the multiple designated stores based on the business area information of each of the multiple designated stores estimated by the estimation process.

[0119] For example, in the estimation process, the analysis unit 32 performs, for each designated store, a process of estimating the business area of the designated store based on the information of the users of the designated store. The users of the designated store are users who have at least one history among visiting the designated store, purchasing goods at the designated store, and using services at the designated store, but are not limited to such examples. For example, users whose average stay time at the designated store is longer than a predetermined period may also be included. Hereinafter, the users of the designated store may be described as store users.

[0120] The information of the store users includes, for example, information indicating the stay location of the store users or information indicating the location history of the store users. The information indicating the stay location of the store users is, for example, information indicating the latitude and longitude of the stay location of the store users, but may also be information indicating the address.

[0121] The stay location of the store users is, for example, a place where the store users habitually stay, such as the residence of the store users or the workplace of the store users. Note that the stay location of the store users may also be a place where the store users stay temporarily, such as the accommodation facility of the store users or the gaming facility visited by the store users.

[0122] In addition, the information of the store user may further include one or more pieces of information among, for example, information indicating the attributes of the store user, information indicating the usage history of the designated store by the store user, information indicating the facilities used by the store user, information indicating the transportation means used by the store user, and information indicating the location history of the store user.

[0123] The information indicating the attributes of the store user is, for example, demographic attributes or psychographic attributes of the store user. Demographic attributes are, for example, gender, age, place of residence, place of work, and occupation, etc., and psychographic attributes are objects of interest such as travel, clothing, cars, religion, lifestyle, life stage, purchase intention, thoughts and trends of thoughts, etc.

[0124] The usage history of the designated store by the store user is, for example, each payment amount or average payment amount of the store user, the content and genre of the purchased goods and services of the store user, each stay time or average stay time of the store user, etc., but is not limited to such examples.

[0125] In the estimation process, for example, based on the information indicating the stay location of each store user, the analysis unit 32 estimates the business area of the designated store. For example, based on the stay location of each store user, the analysis unit 32 estimates the business area of the designated store using an estimation method such as kernel density estimation. The analysis unit 32 estimates, for example, one or more areas where the density is equal to or greater than a predetermined value as the business area of the designated store.

[0126] In addition, in the estimation process, the analysis unit 32 determines, for example, whether the number of store users in each predetermined unit area is equal to or greater than a predetermined number, and the analysis unit 32 can also estimate the set of unit areas where the number of store users is equal to or greater than the predetermined number as the business area of the designated store.

[0127] The information indicating the stay location of the store user is information indicating the place of residence set by the store user or information indicating the place of work set by the store user, etc., but the analysis unit 32 can estimate the information indicating various stay locations of the store user based on the information indicating the location history of the store user.

[0128] For example, based on the information indicating the location history of the store user, the analysis unit 32 can estimate the place of residence of the store user, the place of work of the store user, the place where the store user stayed temporarily, etc. from the staying patterns at each location of the store user. In the following, the business area of a designated store estimated in the estimation process may be referred to as the designated store business area.

[0129] In addition, the analysis unit 32 can also estimate the designated store business area based on the information of store users who meet specific conditions. For example, when the information indicating specific conditions is included in the business area comparison information request received by the reception unit 31, the analysis unit 32 estimates the designated store business area from the staying places of store users who meet the specific conditions indicated in the business area comparison information request.

[0130] The specific conditions are, for example, the attributes of the store user, the type of the staying place of the store user, the attributes of the store user, the facilities used by the store user, the transportation means used by the store user, the purchase of specific goods or the use of specific services by the store user at the designated store, the average staying time of the store user at the designated store, etc., but are not limited to such examples.

[0131] In the comparison process, the analysis unit 32 compares the business area information between a plurality of designated stores based on the business area information of each of the plurality of designated stores. For example, in the comparison process, the analysis unit 32 can determine the degree of overlap of the business areas between the designated stores or the differences in the business areas between the designated stores. In addition, for example, in the comparison process, the analysis unit 32 can also determine the difference between the business area of a designated store and a general business area.

[0132] The business area information of the designated store is information indicating the business area of the designated store, information of the store users of the designated store in the business area of the designated store, etc. In the comparison process, the analysis unit 32 can use at least one of the business area information of each of the plurality of designated stores and the information of the store users of each of the plurality of designated stores as the business area information of each of the plurality of designated stores to compare the business area information between the plurality of designated stores.

[0133] The information of store users in the business district of a designated store includes, for example, one or more pieces of information among information indicating the attributes of store users, information indicating the usage history of the designated store by store users, information indicating other stores and facilities used by store users, information indicating the transportation means used by store users, and information indicating the location history of store users.

[0134] The usage history of the designated store by store users is, for example, each payment amount and average payment amount of store users, the content and genre of purchased goods and purchased services by store users, each stay time and average stay time of store users, etc., but is not limited to such examples.

[0135] In the comparison process, the analysis unit 32 determines, for example, the common points and differences of the user groups among a plurality of designated stores. For example, in the comparison process of the information of the business districts between designated stores, the analysis unit 32 can determine one or more common points and differences among the attributes of store users, the genre of purchased goods, the average payment amount, the average stay time, hobbies and preferences, used facilities, other used stores, used transportation means, etc. between a plurality of designated stores.

[0136] For example, in the comparison process, the analysis unit 32 estimates the main user group of each designated store and compares the estimated user groups. The main user group of a designated store is determined by, for example, one or more elements among the attributes of store users, the genre of purchased goods, the average payment amount, the average stay time, hobbies and preferences, used facilities, other used stores, used transportation means, etc.

[0137] In addition, in the comparison process, the analysis unit 32 can determine the ratio of store users in common or the ratio of different store users among a plurality of designated stores. In such a process, the analysis unit 32 can determine the ratio of store users in common among a plurality of designated stores for each attribute of store users (for example, one or more combinations of a plurality of attribute items such as gender, age, place of residence, occupation, etc.).

[0138] In addition, in, for example, the comparison process, the analysis unit 32 can determine commonalities and differences between the business areas of a plurality of designated stores, overlaps among the store users of a plurality of designated stores, and the like. For example, in the comparison process, as the commonalities and differences between the business areas of a plurality of designated stores, the analysis unit 32 can determine the degree of overlap between the business areas of a plurality of designated stores, commonalities and differences in the shapes of the business areas of a plurality of designated stores, and the like.

[0139] In addition, in, for example, the comparison process, the analysis unit 32 can also determine commonalities and differences in the behavior of store users before and after visiting a store among the designated stores. For example, the analysis unit 32 determines commonalities and differences in the facilities that store users often visit and the genres of other stores before and after visiting a designated store among the designated stores.

[0140] In addition, in the comparison process, the analysis unit 32 can compare the information on the business areas between a plurality of designated stores based on the information on the plurality of designated stores in addition to the information on the business areas of each of the plurality of designated stores.

[0141] The information on a plurality of designated stores is, for example, information indicating the positions of each of the plurality of designated stores, information indicating the products sold at each of the plurality of designated stores, information indicating the genre of each of the plurality of designated stores, and the like, but is not limited to such examples. For example, in the comparison process, the analysis unit 32 can use the information indicating the positions of each of the plurality of designated stores, the information indicating the products sold at each of the plurality of designated stores, and the information indicating the genre of each of the plurality of designated stores as the information on each of the plurality of designated stores to compare the information on the business areas between the plurality of stores.

[0142] In the comparison process, the analysis unit 32 can, for example, determine commonalities and differences between a plurality of designated stores based on the information on the plurality of designated stores. For example, based on the information on the business areas of the designated stores, the analysis unit 32 can determine whether a plurality of designated stores are competing stores or collaborative stores.

[0143] In addition, in the comparison process, the analysis unit 32 can further use, in addition to the above-described information, geographical information of the designated store's business district, etc. The geographical information includes, for example, information indicating terrain, information indicating traffic routes, information indicating routes of public institutions, information indicating traffic regulations and signs, information of news articles, information of disasters, information of facilities and stores, weather information, etc., but is not limited to such examples.

[0144] For example, in the comparison process, the analysis unit 32 can determine the common points and differences in the geographical characteristics of the business districts among a plurality of designated stores based on the geographical relationship between the designated store and the designated store's business district. The geographical relationship between the designated store and the designated store's business district includes the positional relationship between the designated store and the designated store's business district, the distance and terrain between the designated store and each position of the designated store's business district, etc., but is not limited to such examples.

[0145] The positional relationship between the designated store and the designated store's business district includes, for example, the shape of the designated store's business district as seen from the designated store, the position of the designated store relative to the designated store's business district, etc., but is not limited to such examples. The distance between the designated store and each position of the designated store's business district is, for example, the moving distance between the designated store and each position of the designated store's business district, but may also be the straight-line distance between the designated store and each position of the designated store's business district. Also, the terrain between the designated store and each position of the designated store's business district includes, for example, the magnitude and number of gradients of the moving route to the designated store, the length and number of curves, etc., but is not limited to such examples.

[0146] The analysis unit 32 performs the above-described estimation process and comparison process using a generation AI. The generation AI is, for example, a text generation AI. The text generation AI is, for example, a large language model trained to estimate and output the next token from the input token sequence, and is, for example, a transformer-based model or an RNN-based model, etc., but may also be a hybrid model thereof. Also, the text generation AI may be a composite system combined with an identification mechanism for preventing unauthorized use.

[0147] Transformer-based models include, but are not limited to, examples such as GPT, PaLM2, or LLaMA. RNN-based models include, but are not limited to, examples such as RWKV.

[0148] Note that it is desirable for the generative AI to be trained so as not to include personal information etc. in its generation results. The generative AI is arranged in an external information processing device, and the analysis unit 32 uses the generative AI via an API, but the generative AI may be arranged within the analysis unit 32.

[0149] The analysis unit 32 inputs a prompt including, for example, instruction information that is information for instructing the estimation of the business areas of each of a plurality of designated stores and the comparison between the estimated multiple business areas, and information necessary for the estimation of the designated store business area and the comparison between the designated store business areas, into the generative AI, and causes the generative AI to output the designated store business area and the comparison result between the designated store business areas.

[0150] The information necessary for the estimation of the designated store business area and the comparison between the designated store business areas includes, but is not limited to, for example, the above-described information used in the estimation process and the comparison process.

[0151] As information necessary for the estimation process of the designated store business area using the generative AI, the analysis unit 32 uses, for example, instruction information for instructing the estimation of the designated store business area based on information of store users (for example, information indicating the stay locations of store users such as the residence and workplace of store users). Such instruction information is, for example, information indicating an instruction to estimate one or more areas with a density equal to or higher than a predetermined value as the business area of the designated store based on information of store users, or information indicating an instruction to estimate one or more areas with a density estimated using an estimation method such as kernel density estimation and equal to or higher than a predetermined value as the business area of the designated store based on information of store users, but is not limited to such examples.

[0152] In the comparison process using the generative AI, the analysis unit 32 uses instruction information for instructing the comparison of the information of the designated store's business district based on the information of the business district of the designated store. For example, the analysis unit 32 can cause the generative AI to output information indicating the common points and differences of the user layers among a plurality of designated stores by using instruction information for instructing the comparison of the user layers among the plurality of designated stores.

[0153] The instruction information for instructing the comparison of the user layers among a plurality of designated stores may include information specifying one or more elements used for comparison among, for example, the attributes of store users, the genres of purchased products, the average payment amount, the average stay time, hobbies and preferences, used facilities, other used stores, used transportation means, etc.

[0154] In addition, in the comparison process using the generative AI, the analysis unit 32 uses instruction information for instructing the determination of the ratio of store users common among a plurality of designated stores or the ratio of different store users by comparing the store users among the plurality of designated stores, and can cause the generative AI to output information indicating the ratio of store users common among the plurality of designated stores or the ratio of different store users.

[0155] In addition, in the comparison process using the generative AI, the analysis unit 32 uses instruction information for instructing the determination of the most common attribute among the attributes of store users common among a plurality of designated stores (for example, one or more combinations of a plurality of attribute items such as gender, age, place of residence, occupation, etc.) by comparing the store users among the plurality of designated stores, and can cause the generative AI to output information indicating the attributes of store users common among the plurality of designated stores.

[0156] In addition, in the comparison process using the generative AI, the analysis unit 32 uses instruction information for instructing the determination of the common points and differences between the business districts of a plurality of designated stores by comparing the business districts of the plurality of designated stores, and can cause the generative AI to output information indicating the common points and differences between the business districts of the plurality of designated stores. In this case, the instruction information may include information specifying the overlap between the business districts of the plurality of designated stores and the shape of the business districts of the plurality of designated stores as the objects for determining the common points and differences between the business districts of the plurality of designated stores.

[0157] In the comparison process using the generative AI, the analysis unit 32 can also use instruction information for instructing the comparison of the information on the business area of the designated store based on the information on a plurality of designated stores in addition to the information on the business area of the designated store.

[0158] For example, in the comparison process using the generative AI, the analysis unit 32 can cause the generative AI to output information indicating common points and differences among a plurality of designated stores by using instruction information for instructing the determination of common points and differences among a plurality of designated stores through the comparison of information among the plurality of designated stores.

[0159] For example, in the comparison process using the generative AI, the analysis unit 32 can cause the generative AI to output information indicating common points and differences in the geographical relationship between the designated stores among the business areas of the plurality of designated stores by using instruction information for instructing the determination of common points and differences in the geographical relationship between the designated stores among the business areas of the plurality of designated stores.

[0160] The instruction information includes, for example, information for instructing the summarization of the comparison results, information for naming a title for the summary of the comparison results, information for instructing the output of the title and the summarized content, and the like. Thereby, in the comparison process, the generative AI can be caused to output information that concisely shows the comparison results between the business areas of the designated stores with a title.

[0161] FIG. 6 is a diagram showing an example of a prompt used by the analysis unit 32 of the processing unit 12 in the information processing apparatus 1 according to the embodiment. The analysis unit 32 can input the prompt shown in FIG. 6 to the generative AI and cause the generative AI to output the estimation result of the business area of the designated store and the comparison between the business areas of the designated stores. The instruction information of the prompt shown in FIG. 6 includes information on the output format that defines how to output the comparison results between the estimated business areas of the designated stores, and information of the character string "name a title for the summary and output the title and the summary content".

[0162] Although not shown, the prompt instruction information shown in FIG. 6 includes information indicating an instruction to output the estimated business area. For example, the prompt instruction information shown in FIG. 6 may include information such as the information of the character string "Output the density value of the users in the estimated business area in a list format for each location.", but is not limited to such an example. Note that in the prompt shown in FIG. 6, a part of the information other than the instruction information is omitted. Also, the prompt instruction information shown in FIG. 6 may not include information indicating an instruction to output the estimated designated store business area.

[0163] In addition, the analysis unit 32 can also perform the estimation process and the comparison process separately by inputting the prompt of the estimation process and the prompt of the comparison process into the generation AI individually. In this case, the prompt of the comparison process includes information indicating the position of the designated store business area estimated in the estimation process.

[0164] In addition, instead of using the generation AI, the analysis unit 32 can also estimate the designated store business area by statistical processing. For example, the analysis unit 32 aggregates the number of store users for each predetermined unit area based on the information indicating the stay locations of a plurality of store users, and estimates the designated store business area based on such aggregation results.

[0165] The analysis unit 32 can, for example, estimate one or more areas with a density equal to or higher than a predetermined value as the business area of the designated store, or estimate one or more areas with a density equal to or higher than a predetermined value using an estimation method such as kernel density estimation as the business area of the designated store.

[0166] In addition, instead of using the generation AI, the analysis unit 32 can also compare the information between the designated store business areas by statistical processing. For example, the analysis unit 32 can determine the main user layer of each designated store business area based on one or more pieces of information such as the attributes of store users, the genre of purchased goods, the average payment amount, the average stay time, hobbies, and preferences.

[0167] In addition, the analysis unit 32 can determine the ratio of store users common to a plurality of designated stores or the ratio of different store users by performing statistical processing using information on store users of the plurality of designated stores. The comparison of information between the business areas of the designated stores by statistical processing is not limited to the example described above.

[0168] Also, for example, the analysis unit 32 inputs a prompt including processing definition information, instruction information, and information necessary for estimation for extracting a processing type and processing target information into the generation AI, and acquires, from the generation AI, processing information including information indicating the processing type and processing target information as output information.

[0169] The analysis unit 32 can perform a process corresponding to the process type indicated by the information indicating the process type using the processing target information, for example, by specific arithmetic processing or statistical processing. The process type is, for example, business area estimation, business area comparison, etc., but is not limited to such examples. Business area estimation is a process of estimating the business area of a designated store, and business area comparison is a process of comparing the characteristics and features between the business areas of designated stores.

[0170] The generation AI extracts and outputs, as processing target information, information necessary for the process indicated by the process type among various information included in the prompt. For example, when the process type is business area estimation, the generation AI extracts and outputs, as processing target information, information necessary for estimating the business area of the designated store among various information included in the prompt. The information necessary for estimating the business area of the designated store is, for example, the information described above.

[0171] Also, when the process type is business area comparison, the generation AI extracts and outputs, as processing target information, information necessary for comparing the information between the business areas of the designated stores among various information included in the prompt. The information necessary for comparing the information between the business areas of the designated stores is, for example, the information described above.

[0172] For example, when the generation AI is GPT of OpenAI, the analysis unit 32 can cause the generation AI to output the processing information as output information using the function of function calling for the output information of the generation AI.

[0173] The generative AI may be a multimodal generative AI or the like. The multimodal generative AI is, for example, a generative AI that generates at least one of text, images, and audio from at least one of text, images, and audio. Examples of the multimodal generative AI include, but are not limited to, GPT-4 Turbo with vision, gemini, CM3Leon (Chameleon Multimodal Model), etc.

[0174] In this case, the analysis unit 32 further inputs, as input information, information indicating an instruction for causing the generative AI to draw the estimated business area of the designated store on the map and map information indicating the map of the area including the designated store, so that the generative AI can output map information showing the business area of the designated store on the map.

[0175] When the reception unit 31 receives the designation of the strategic target store and a plurality of comparison target stores by the service user O, the analysis unit 32 can also determine a strategic proposal based on the differences in the user layers among the plurality of designated stores. The strategic proposal is, for example, an aggressive strategy (raising price or quality to capture share from competitors), a niche strategy (finding a niche in the customer segment to expand share), a collaborative strategy (aiming to acquire customers and increase sales through collaboration with other stores), etc., but is not limited to such examples.

[0176] For example, when the analysis unit 32 receives the designation of the strategic target store and a plurality of comparison target stores by the service user O, the analysis unit 32 performs the above-described estimation process of estimating the business area of each of the strategic target store and the plurality of comparison target stores, and a strategy formulation process of formulating a strategy for the strategic target store based on the information on the business areas of each of the strategic target store and the plurality of comparison target stores estimated by the estimation process.

[0177] In the strategic proposal process, the analysis unit 32 makes a strategic proposal for the target store based on the information of the business areas of the target store and each of the multiple comparison target stores. For example, in the strategic proposal process, the analysis unit 32 can perform a comparison process similar to the above-described comparison process. For example, in the strategic proposal process, the analysis unit 32 makes a strategic proposal for the target store based on the above-described comparison process.

[0178] The analysis unit 32 inputs a prompt for performing the estimation process and the strategic planning process into the generative AI, and causes the generative AI to output the results of the estimation process and the strategic planning process. Also, the analysis unit 32 can separately perform the estimation process and the strategic planning process by separately inputting the prompt for the estimation process and the prompt for the strategic planning process into the generative AI. In this case, the prompt for the strategic planning process includes information indicating the position of the designated store business area estimated by the estimation process.

[0179] FIG. 7 is a diagram showing another example of a prompt used by the analysis unit 32 of the processing unit 12 in the information processing apparatus 1 according to the embodiment. The analysis unit 32 inputs the prompt shown in FIG. 7 into the generative AI, and causes the generative AI to output the estimation result of the designated store business area and the result of strategic planning.

[0180] The instruction information of the prompt shown in FIG. 7 includes information of an output format that defines how to output a strategic proposal, which is the result of strategic planning, in the form of the string "Propose the following content for various strategies\nTitle of the strategy, Summary of the strategy, Predicted effects and risks by implementation, Information used for planning".

[0181] Although not shown, the instruction information of the prompt shown in FIG. 7 includes information indicating an instruction to output the estimated business area. For example, the instruction information of the prompt shown in FIG. 7 may include information such as the information of the character string "Output the density value of users in the estimated business area in a list format for each location.", but is not limited to such an example. Note that in the prompt shown in FIG. 7, a part of the information other than the instruction information is omitted. Also, the instruction information of the prompt shown in FIG. 7 may not include information indicating an instruction to output the estimated business area.

[0182] In addition, the analysis unit 32 can perform a process corresponding to the process type indicated by the information indicating the process type using the process target information, for example, by specific arithmetic processing or statistical processing. The process type is, for example, business area estimation, business area comparison, strategy formulation process, etc., but is not limited to such examples. Note that the analysis unit 32 can also estimate the designated store business area by statistical processing instead of using the generation AI.

[0183] [3.3.4. Providing Unit 33] The providing unit 33 provides various information to the service user O. For example, the providing unit 33 provides various information to the service user O by transmitting various information to the terminal device 2 via the communication unit 10 and the network N.

[0184] For example, when a usage request is received by the reception unit 31, the providing unit 33 transmits store designation information including list information indicating a list of stores existing in the designated area and map information of the designated area to the terminal device 2.

[0185] When the terminal device 2 receives the store designation information transmitted from the providing unit 33, based on the received store designation information, it displays list information indicating a list of stores existing in the designated area and map information of the designated area. In the list information, each store existing in the designated area is arranged in a list format so that it can be individually designated, and in the map information of the designated area, store graphics indicating the positions of each store existing in the designated area are arranged on the map so that they can be individually designated.

[0186] Service user O can specify two or more stores to be analyzed from among a plurality of stores included in the list information displayed on the terminal device 2, and can specify a store graphic corresponding to the store to be analyzed from among a plurality of store graphics included in the map information displayed on the terminal device 2.

[0187] When there is a specification of two or more stores or two or more store graphics by service user O, the terminal device 2 transmits a business district comparison information request including information indicating the two or more stores specified by service user O or information indicating the stores corresponding to the two or more store graphics specified by service user O as store information to the information processing device 1. Note that the specification by service user O may be a combination of one or more stores and one or more store graphics.

[0188] In addition, when a business district comparison information request is received by the reception unit 31, the providing unit 33 provides map information including information indicating a plurality of designated store business districts estimated by the analysis unit 32 and information indicating a comparison result between information of a plurality of designated store business districts.

[0189] For example, the providing unit 33 provides service user O with map information including information indicating a plurality of designated store business districts and information indicating a comparison result between information of a plurality of designated store business districts by transmitting the map information including information indicating a plurality of designated store business districts and information indicating a comparison result between information of a plurality of designated store business districts to the terminal device 2.

[0190] FIG. 8 is a diagram showing an example of map information provided by the providing unit 33 of the processing unit 12 in the information processing device 1 according to the embodiment and displayed on the terminal device 2. In the example shown in FIG. 8, as information indicating a comparison result between information of a plurality of designated store business districts, information of the character string "The Higashi Fukuoka store and the Onojo store have a business district area overlap of about 40 to 60% with each other, and 5 to 6% of the users use both stores. By promoting marketing to residents near the Higashi Fukuoka store, the distance hurdle can be lowered and it may become a more accessible store. \n*It is also necessary to consider the type of products, the workplace and transportation conditions of the users." is included.

[0191] In addition, when the estimation process and the strategy formulation process are performed by the analysis unit 32, the providing unit 33 provides map information including information indicating the business areas of each of the strategic target store and the plurality of comparison target stores estimated by the analysis unit 32 and information indicating the result of the strategy formulation for the strategic target store. The result of the strategy formulation for the strategic target store includes information indicating a strategy proposal for the strategic target store, and may further include the result of the comparison process.

[0192] For example, the providing unit 33 provides the service user O with map information including information indicating the business areas of a plurality of stores including the strategic target store and the plurality of comparison target stores and information indicating a strategy proposal for the strategic target store by transmitting the map information including information indicating the business areas of a plurality of stores including the strategic target store and the plurality of comparison target stores and information indicating a strategy proposal for the strategic target store to the terminal device 2.

[0193] For example, the providing unit 33 provides, as map information, information in a state where the business areas of the designated stores estimated by the analysis unit 32 are highlighted in different manners (for example, the color of the business area region, the color of the frame surrounding the business area region, etc.) on the map.

[0194] [4. Processing Procedure] Next, the information processing procedure by the processing unit 12 of the information processing apparatus 1 according to the embodiment will be described. FIG. 9 is a flowchart showing an example of information processing by the processing unit 12 of the information processing apparatus 1 according to the embodiment.

[0195] As shown in FIG. 9, the processing unit 12 of the information processing apparatus 1 determines whether or not a usage request has been received from the service user O (step S10). When the processing unit 12 determines that a usage request has been received from the service user O (step S10: Yes), the processing unit 12 provides the service user O with store designation information (step S11).

[0196] When the processing of step S11 is completed, or when it is determined that a usage request from the service user O has not been received (step S10: No), the processing unit 12 determines whether a request for commercial area comparison information has been received from the service user O (step S12).

[0197] If the processing unit 12 determines that it has received a trade area information request from the service user O (step S12: Yes), it estimates the designated store trade area and compares it with the designated store trade areas (step S13).Then, the processing unit 12 provides the service user O with map information including information indicating the designated store trade area and information indicating the comparison result between the designated store trade areas (step S14).

[0198] When the processing of step S14 is completed, or when it is determined that a request for trade area comparison information has not been received from the service user O (step S12: No), the processing unit 12 determines whether a request for strategy proposal information has been received from the service user O (step S15).

[0199] When the processing unit 12 determines that it has received a strategy proposal information request from the service user O (step S15: Yes), it performs a process of estimating the trade areas of the strategic target store and the plurality of comparison target stores and a process of formulating a strategy for the strategic target store (step S16).Then, the processing unit 12 provides the service user O with map information including information indicating the trade areas of the strategic target store and the plurality of comparison target stores and information indicating a strategy proposal for the strategic target store (step S17).

[0200] When the processing of step S17 is completed or when it is determined that a strategy proposal information request has not been received from the service user O (step S15: No), the processing unit 12 determines whether or not it is time to end the operation (step S18). The processing unit 12 determines that it is time to end the operation when, for example, the power of the information processing device 1 is turned off.

[0201] When the processing unit 12 determines that it is not the operation end timing (step S18: No), the process proceeds to step S10. When it determines that it is the operation end timing (step S18: Yes), the process shown in FIG. 9 is terminated.

[0202] 〔5. Modification Example〕 For example, in the comparison process, the analysis unit 32 can estimate the moving speed of the store users at each position in the business district of the designated store based on the information indicating the position history of the store users, and compare the estimation results.

[0203] Also, in the estimation process, the analysis unit 32 can estimate the business district of the designated store for each predetermined period based on the information of the store users for each predetermined period and the like. In this case, the providing unit 33 can also provide map information showing on the map while automatically switching the business district of the designated store for each predetermined period estimated in the estimation process in time series.

[0204] Also, in the comparison process, the analysis unit 32 can compare the information between the business districts of the designated stores for each predetermined period based on the information of the store users for each predetermined period and the like. In this case, the providing unit 33 can also provide map information showing on the map while automatically switching the comparison results of the information between the business districts of the designated stores for each predetermined period estimated in the second estimation process in time series.

[0205] Also, in the comparison process, the analysis unit 32 can estimate the characteristics of the business district of the designated store using the posting information to the SNS related to the designated store or the posting information to the communication service related to the designated store as the information of the designated store, and compare the estimated characteristics. For example, the analysis unit 32 can estimate the high posting frequency of the store users in the business district of the designated store related to the designated store to the SNS, the high posting frequency of the store users in the business district of the designated store related to the designated store to the communication service, etc. as the characteristics of the business district of the designated store, and compare the estimation results.

[0206] In this case, the analysis unit 32 inputs a prompt including information for instructing the generation AI to estimate and compare, for example, the high posting frequency of store users in the designated store's business district regarding the designated store on SNS, and the high posting frequency of store users in the designated store's business district regarding the designated store on communication services, as instruction information.

[0207] Also, the analysis unit 32 can, for example, perform the comparison process by dividing it into a plurality of processes. For example, the analysis unit 32 can perform a plurality of processes including a first process for determining the characteristics of each designated store's business district, a second process for comparing the characteristics between the designated store's business districts to determine common points and differences, and a third process for summarizing the results of the second process as the comparison process.

[0208] In this case, in the first process, the analysis unit 32 inputs a prompt including instruction information for instructing the determination of the characteristics of each designated store's business district and information necessary for the determination of the characteristics of each designated store's business district to the generation AI, and causes the generation AI to output information indicating the characteristics of each designated store's business district. Note that the first process may be performed for each designated store's business district.

[0209] Also, in the second process, the analysis unit 32 inputs a prompt including instruction information for instructing the comparison of the characteristics between the designated store's business districts to determine common points and differences and information indicating the characteristics of each designated store's business district determined in the first process to the generation AI, and causes the generation AI to output information indicating common points and differences in the characteristics between the designated store's business districts.

[0210] Also, in the third process, the analysis unit 32 inputs a prompt including instruction information for instructing the summarization of the results of the second process and information indicating common points and differences in the characteristics between the designated store's business districts determined in the second process to the generation AI, and causes the generation AI to output information indicating the comparison results of the characteristics between the designated store's business districts.

[0211] 〔6. Hardware Configuration〕 The information processing apparatus 1 according to the above-described embodiment is realized by a computer 80 configured as shown in FIG. 10, for example. FIG. 10 is a hardware configuration diagram showing an example of a computer 80 that realizes the functions of the information processing apparatus 1 according to the embodiment. The computer 80 includes a CPU 81, a RAM 82, a ROM (Read Only Memory) 83, an HDD (Hard Disk Drive) 84, a communication interface (I / F) 85, an input / output interface (I / F) 86, and a media interface (I / F) 87.

[0212] The CPU 81 operates based on a program stored in the ROM 83 or the HDD 84 and controls each part. The ROM 83 stores a boot program executed by the CPU 81 when the computer 80 is started up, a program dependent on the hardware of the computer 80, and the like.

[0213] The HDD 84 stores a program executed by the CPU 81, data used by such a program, and the like. The communication interface 85 receives data from other devices via the network N (see FIG. 2) and sends it to the CPU 81, and sends data generated by the CPU 81 to other devices via the network N.

[0214] The CPU 81 controls output devices such as a display and a printer, and input devices such as a keyboard or a mouse via the input / output interface 86. The CPU 81 acquires data from the input devices via the input / output interface 86. Further, the CPU 81 outputs data generated via the input / output interface 86 to the output devices.

[0215] The media interface 87 reads a program or data stored in the recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads such a program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory, etc.

[0216] For example, when the computer 80 functions as the information processing apparatus 1 according to the embodiment, the CPU 81 of the computer 80 realizes the functions of the processing unit 12 by executing the program loaded onto the RAM 82. Further, the data in the storage unit 11 is stored in the HDD 84. The CPU 81 of the computer 80 reads and executes these programs from the recording medium 88. As another example, these programs may be acquired from another device via the network N.

[0217] 〔7. Others〕 Also, among the respective processes described in the above embodiment, all or part of the processes described as being automatically performed can be manually performed, or all or part of the processes described as being manually performed can be automatically performed by a known method. In addition, regarding the processing procedures, specific names, and information including various data and parameters shown in the above documents and drawings, they can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

[0218] Also, each component of each device shown in the drawings is a functional concept, and it is not necessarily physically configured as shown in the drawings. That is, the specific form of the distribution and integration of each device is not limited to that shown, and all or part of it can be functionally or physically distributed and integrated in any unit according to various loads and usage situations, etc.

[0219] For example, the above-described information processing apparatus 1 may be implemented by a terminal device and a server computer, or may be implemented by a plurality of server computers. Further, depending on the function, the configuration can be flexibly changed, such as by calling an external platform or the like using an API or network computing.

[0220] Also, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not conflict.

[0221] 〔8. Effects〕 As described above, the information processing apparatus 1 according to the embodiment includes a reception unit 31, an analysis unit 32, and a provision unit 33. The reception unit 31 receives designations of a plurality of stores. The analysis unit 32 performs an estimation process of estimating the business area of each of the plurality of stores designated by the reception unit 31, and a comparison process of comparing the business area information between the plurality of stores based on the business area information of each of the plurality of stores estimated by the estimation process. The provision unit 33 provides map information including information indicating the business area of each of the plurality of stores estimated by the estimation process and information indicating the comparison result of the comparison process. Thereby, the information processing apparatus 1 can perform business area analysis with higher accuracy.

[0222] Also, in the comparison process, the analysis unit 32 compares the business area information between the plurality of stores based on the business area information of each of the plurality of stores estimated by the estimation process and the information of the plurality of stores designated by the reception unit 31. Thereby, the information processing apparatus 1 can perform business area analysis with higher accuracy.

[0223] Also, in the comparison process, the analysis unit 32 uses, as the information of each of the plurality of stores, information indicating the position of each of the plurality of stores, information indicating the products sold at each of the plurality of stores, and information indicating the genre of each of the plurality of stores, and compares the business area information between the plurality of stores. Thereby, the information processing apparatus 1 can perform business area analysis with higher accuracy.

[0224] In addition, in the comparison process, the analysis unit 32 uses the information of each user of a plurality of stores as the information of the business area of each of the plurality of stores to compare the information of the business areas between the plurality of stores. Thereby, the information processing apparatus 1 can provide the information of the business area with an appropriate range as the business area of the store. Thereby, the information processing apparatus 1 can perform the analysis of the business area more accurately.

[0225] In addition, in the comparison process, the analysis unit 32 uses the information indicating the attributes of the user, the information indicating the usage history of the store by the user, and the information indicating the facilities used by the user as the information of the users of the store to compare the information of the business areas between the plurality of stores. Thereby, the information processing apparatus 1 can perform the analysis of the business area more accurately.

[0226] In addition, in the comparison process, the analysis unit 32 uses the generation AI to compare the information of the business areas between the plurality of stores. Thereby, the information processing apparatus 1 can perform the analysis of the business area more accurately.

[0227] In addition, in the estimation process, the analysis unit 32 estimates the business area of each of the plurality of stores using the generation AI based on the place of residence of each user of the plurality of stores. Thereby, the information processing apparatus 1 can perform the analysis of the business area more accurately.

[0228] In addition, the analysis unit 32 determines a strategic proposal based on the difference in customer layers between the plurality of stores. Thereby, the information processing apparatus 1 can perform the analysis of the business area more accurately.

[0229] As described above, the embodiments of the present application have been described in detail with reference to the drawings. However, this is an example, and the present invention can be implemented in other forms in which various modifications and improvements are made based on the knowledge of those skilled in the art, including the aspects described in the column of the disclosure of the invention.

[0230] In addition, the above-mentioned "section (section, module, unit)" can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

Description of Reference Numerals

[0231] 1 Information processing device 2 Terminal device 10 Communication unit 11 Memory unit 12 Processing unit 20 User information memory unit 21 Store information memory unit 22 Geographic information memory unit 23 Content memory unit 30 Acquisition unit 31 Reception unit 32 Analysis unit 33 Provision unit 100 Information processing system N Network

Claims

1. A reception unit that receives designations of a plurality of stores, An analysis unit that performs an estimation process of estimating the business area of each of the plurality of stores designated by the reception unit, and a comparison process of comparing the business area information between the plurality of stores based on the business area information of each of the plurality of stores estimated by the estimation process, A providing unit that provides map information including information indicating the business area of each of the plurality of stores estimated by the estimation process and information indicating the comparison result of the comparison process, An information processing apparatus characterized by the above.

2. The analysis unit, In the comparison process, based on the business area information of each of the plurality of stores estimated by the estimation process and the information of the plurality of stores received by the reception unit, the business area information between the plurality of stores is compared. The information processing apparatus according to claim 1, characterized by the above.

3. The analysis unit, In the comparison process, using information indicating the location of each of the plurality of stores, information indicating the products sold at each of the plurality of stores, and information indicating the genre of each of the plurality of stores as the information of each of the plurality of stores, the business area information between the plurality of stores is compared. The information processing apparatus according to claim 2, characterized by the above.

4. The analysis unit, In the comparison process, using the information of the users of each of the plurality of stores as the business area information of each of the plurality of stores, the business area information between the plurality of stores is compared. The information processing apparatus according to any one of claims 1 to 3, characterized by the above.

5. The analysis unit, In the comparison process, using information indicating the attributes of the users, information indicating the usage history of the stores by the users, and information indicating the facilities used by the users as the information of the users of the stores, the business area information between the plurality of stores is compared. The information processing apparatus according to claim 4, characterized by the above.

6. The analysis unit, In the comparison process, using a generative AI to compare the business area information between the plurality of stores. The information processing apparatus according to any one of claims 1 to 3, characterized by the above.

7. The analysis unit, In the estimation process, based on the place of residence of the users of each of the plurality of stores, using a generative AI to estimate the business area of each of the plurality of stores. The information processing apparatus according to any one of claims 1 to 3, characterized by the above.

8. The analysis unit, Determine strategic proposals based on the differences in customer segments among the plurality of stores The information processing apparatus according to any one of claims 1 to 3, characterized in that

9. An information processing method executed by a computer, comprising A reception step of receiving designations of a plurality of stores, An estimation process of estimating the business area of each of the plurality of stores designated in the reception step, and a comparison process of comparing the business area information among the plurality of stores based on the information on the business area of each of the plurality of stores estimated in the estimation process, in an analysis step A provision step of providing map information including information indicating the business area of each of the plurality of stores estimated in the estimation process and information indicating the comparison result of the comparison process An information processing method characterized by the above

10. A reception procedure for receiving designations of a plurality of stores, An estimation process of estimating the business area of each of the plurality of stores designated in the reception procedure, and a comparison process of comparing the business area information among the plurality of stores based on the information on the business area of each of the plurality of stores estimated in the estimation process, in an analysis procedure Causing a computer to execute a provision procedure for providing map information including information indicating the business area of each of the plurality of stores estimated in the estimation process and information indicating the comparison result of the comparison process An information processing program characterized by the above

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