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

Abstract

To provide an information processing device capable of supporting the analysis of users of stores and facilities, an information processing method, and an information processing program.SOLUTION: An information processing device comprises an acceptance unit, an acquisition unit, an analysis unit, and a provision unit. The acceptance unit accepts a specification of a store or facility. The acquisition unit acquires information on a plurality of users who have used the store or facility whose specification has been accepted by the acceptance unit, the information indicative of behaviors of the plurality of users before and after the use of the store or facility. The analysis unit summarizes the behaviors of the plurality of users before and after the use of the store or facility on the basis of the information indicative of the behaviors of the plurality of users before and after the use of the store or facility acquired by the acquisition unit.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, techniques for formulating business strategies in stores and the like are known. 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 conventional technology, although it is possible to analyze the business district, there is still room for further improvement in order to support the analysis of users of stores and facilities.

[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 supporting the analysis of users of stores and facilities.

Means for Solving the Problems

[0006] The information processing apparatus according to the present application includes a reception unit, an acquisition unit, an analysis unit, and a provision unit. The reception unit receives a designation of a store or a facility. The acquisition unit acquires information on a plurality of users who have used the store or facility designated by the reception unit, the information indicating the actions of the plurality of users before and after using the store or facility. The analysis unit generalizes the actions of the plurality of users before and after using the store or facility based on the information indicating the actions of the plurality of users before and after using the store or facility acquired by the acquisition unit. The provision unit provides the generalization result by the analysis unit.

Effect of the Invention

[0007] According to one aspect of the embodiment, there is an effect that it is possible to support the analysis of users of stores and facilities.

Brief Description of the Drawings

[0008]

Figure 1

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[0009] Hereinafter, a mode (hereinafter referred to as "embodiment") for implementing the information processing apparatus, information processing method, and information processing program according to the present application 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. Further, in the following embodiments, the same parts are denoted by the same reference numerals, and redundant explanations are omitted.

[0010] **[1. Example of Information Processing]** First, an example of 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 behavior analysis service, and for example, map information in which information about a store or facility designated by the service user O is arranged is transmitted to the terminal device 2 of the service user O. In the following description of steps S1 to S4, the case where the target designated by the service user O is a store will be mainly described.

[0013] As shown in FIG. 1, the information processing apparatus 1 receives a designation of a store by the service user O (step S1). The store is, for example, a retail store (e.g., convenience store, grocery store, clothing store, supermarket, etc.), a food and beverage store (e.g., café, restaurant, fast food restaurant, izakaya, etc.), a service provider store (e.g., beauty salon, dry cleaner, esthetic salon, etc.), etc., but is not limited to such examples.

[0014] In step S1, the information processing apparatus 1 receives a designation of a store by the service user O when, for example, it receives a general information request that includes store information indicating the store designated by the service user O and is transmitted from the terminal device 2, and based on the store information included in the general information request. Hereinafter, the store designated in step S1 may be referred to as the designated store.

[0015] The service user O operates the terminal device 2, for example, to cause the terminal device 2 to transmit a usage request to the information processing apparatus 1. The usage request includes, for example, information indicating the position designated by the service user O or information indicating the area designated by the service user O. Hereinafter, the area including the position designated by the service user O or the area designated by the service user O may be referred to as the designated area.

[0016] When the information processing apparatus 1 receives the usage request transmitted from the terminal device 2, it transmits to the terminal device 2 store designation information including list information indicating a list of stores existing in the designated area and map information of the designated area.

[0017] When the terminal device 2 receives the store designation information transmitted from the information processing apparatus 1, it displays list information indicating a list of stores existing in the designated area and map information of the designated area based on the received store designation information. In the list information, each store existing in the designated area is arranged so as to be individually specifiable, and in the map information of the designated area, store graphics indicating the positions of the respective stores existing in the designated area are arranged individually and specifiably on the map.

[0018] Service user O can specify a store to be analyzed 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 among a plurality of store graphics included in the map information displayed on the terminal device 2. When there is a specification of a store or a store graphic by service user O, the terminal device 2 transmits a general information request including information indicating the store specified by service user O or information indicating the store corresponding to the store graphic specified by service user O as store information to the information processing device 1.

[0019] Subsequently, the information processing device 1 acquires information on a plurality of users who visited the designated store, which is the store designated in step S1, and indicates the actions of the plurality of users before and after visiting the designated store (step S2). Hereinafter, the users of the designated store who visited the designated store may be referred to as store users.

[0020] The information indicating the actions of the store users includes, for example, information indicating the online actions of the store users and information indicating the offline actions of the store users. The online actions of the store users are, for example, the online search actions of the store users (such as web searches, etc.) and the viewing of online content by the store users.

[0021] Online content includes, for example, blog articles, news articles, video content, music content, content posted on SNS (Social Network Service), etc., but is not limited to such examples.

[0022] The information indicating the offline actions of the store users includes, for example, information indicating the facilities and other stores used by the store users and the usage content thereof, information indicating the transportation means used by the store users and the section thereof, and information indicating the movement route traveled by the store users.

[0023] Further, in step S2, the information processing apparatus 1 can also acquire information on a plurality of store users who have visited the designated store, the information indicating the actions of the plurality of store users when they visit the designated store.

[0024] The information indicating the actions of the store users when they visit the designated store is, for example, each payment amount or average payment amount of the store users at the designated store, the content and genre of the purchased goods and services of the store users at the designated store, each stay time or average stay time of the store users at the designated store, etc., but is not limited to such examples. Each payment amount or average payment amount of the store users is, for example, each settlement amount or average settlement amount of the store users, but is not limited to such examples.

[0025] In step S2, the information processing apparatus 1 can acquire, for example, as information indicating the actions of a plurality of store users before and after visiting the designated store, information indicating the actions of a plurality of store users up to a predetermined period before visiting the designated store and information indicating the actions of a plurality of store users up to a predetermined period after visiting the designated store, but is not limited to such examples.

[0026] Further, in step S2, the information processing apparatus 1 can also acquire information on the designated store. The information on the designated store is information indicating the location of the designated store, information indicating the name of the designated store, information indicating the type of the designated store, information on the goods of the designated store, etc. The information indicating the location of the designated store is, for example, information indicating the latitude and longitude of the designated store.

[0027] The information indicating the name of the designated store includes information indicating the chain store name when the designated store is a chain store, and includes information indicating the franchise store name when the designated store is a franchise store. The information indicating the type of the designated store is information indicating the genre of the store, and is, for example, information indicating genres such as convenience stores, grocery stores, clothing stores, supermarkets, cafes, restaurants, fast food stores, izakayas, etc. Note that the genre of the store may be a further subdivided genre. The information on the goods and services of the designated store is information on the goods and services sold at the designated store.

[0028] In addition, the information processing apparatus 1 can also acquire information indicating the behavior of store users by limiting the information acquired in step S2 to the information of store users who satisfy specific conditions. The specific conditions are, for example, information set by the service user O, and the information indicating the specific conditions is included in, for example, a general information request or the like.

[0029] The specific conditions are, for example, the attributes of the store users, the type of the place where the store users stay, the facilities used by the store users, the transportation means used by the store users, the purchase of specific products or the use of specific services by the store users in the designated store, the average stay time of the store users in the designated store, etc., but are not limited to such examples. Note that the information processing apparatus 1 can also acquire information indicating the behavior of store users by limiting the information acquired in step S2 to the information of a specific time period designated by the service user O.

[0030] In addition, the information processing apparatus 1 can also acquire information indicating the attributes of each of a plurality of store users in step S2. The information indicating the attributes of the store users is the demographic attributes or psychographic attributes of the store users, etc. Demographic attributes are, for example, gender, age, place of residence, place of work, and occupation, etc., and psychographic attributes are the objects of interest such as travel, clothing, cars, religion, etc., lifestyle, thoughts and trends of thoughts, etc.

[0031] Subsequently, the information processing apparatus 1 performs a summarization process (step S3) for summarizing the behaviors of a plurality of store users before and after visiting the designated store, based on the information indicating the behaviors of a plurality of store users before and after visiting the designated store, which is the information acquired in step S2.

[0032] The information processing apparatus 1 can summarize the behaviors of a plurality of store users, for example, by classifying the behaviors of a plurality of store users into two or more groups. The information processing apparatus 1 classifies the behaviors of a plurality of store users into two or more groups, for example, based on the characteristics of the behaviors of the store users before visiting the designated store and the characteristics of the behaviors of the store users after visiting the designated store.

[0033] The characteristics of the behavior of store users before visiting a designated store include, for example, the characteristic that store users may use specific facilities or specific other stores before visiting the designated store, and the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristic that store users may conduct specific searches before visiting the designated store, and the characteristics indicating the tendency of the posted content thereof, etc., but are not limited to such examples.

[0034] The characteristics of the behavior of store users after visiting a designated store include, for example, the characteristic that store users may use specific facilities or specific other stores after visiting the designated store, and the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristic that store users may post about the designated store on SNS after visiting the designated store, and the characteristics indicating the tendency of the posted content thereof, etc., but are not limited to such examples.

[0035] In addition, based on the behavior of store users after visiting a designated store, the information processing device 1 can also determine the satisfaction or dissatisfaction with the designated store as an evaluation of the designated store. For example, the information processing device 1 determines the satisfaction or dissatisfaction with the designated store based on the posted content about the designated store on SNS or the posted content in the communication service. In addition, the information processing device 1 can also determine the satisfaction or dissatisfaction with the designated store based on the word-of-mouth posts about the designated store on the word-of-mouth site.

[0036] In addition, the information processing device 1 can also determine a plurality of location users who perform the same actions as the location users with high satisfaction or low dissatisfaction as the location users with high satisfaction or low dissatisfaction with the designated location, and determine a plurality of location users who perform the same actions as the location users with low satisfaction or high dissatisfaction as the location users with low satisfaction or high dissatisfaction with the designated location.

[0037] For example, the information processing apparatus 1 designates a place user who has answered with high satisfaction or low dissatisfaction in a questionnaire or the like as a place user with high satisfaction or low dissatisfaction with respect to a designated place, and designates a place user who has answered with low satisfaction or high dissatisfaction in a questionnaire or the like as a place user with low satisfaction or high dissatisfaction with respect to the designated place. Based on these place users, the satisfaction or dissatisfaction with respect to the designated place is determined.

[0038] Further, when the information acquired in step S2 includes information indicating the actions of a plurality of store users when visiting a designated store, based on the information indicating the actions of a plurality of store users before and after visiting the designated store and the information indicating the actions of a plurality of store users when visiting the designated store, the actions of a plurality of store users before, during, and after visiting the designated store can be summarized.

[0039] For example, the information processing apparatus 1 classifies the actions of a plurality of store users into two or more groups based on the characteristics of the actions of the store users before visiting the designated store, the characteristics of the actions of the store users when (during) visiting the designated store, and the characteristics of the actions of the store users after visiting the designated store.

[0040] The characteristics of the actions of the store users after visiting the designated store are, for example, characteristics such as the average stay time of the store users in the designated store being short or long, characteristics such as the average moving distance of the store users in the designated store being short or long, characteristics such as the average payment amount of the store users in the designated store being small or large, etc., but are not limited to such examples.

[0041] The information processing apparatus 1 can also classify the actions of a plurality of store users into two or more groups for each of the characteristics of the actions of the store users before visiting the designated store, the characteristics of the actions of the store users when (during) visiting the designated store, and the characteristics of the actions of the store users after visiting the designated store.

[0042] The information processing device 1 performs the above-described generalization 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 an 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. Further, the text generation AI may be a composite system combined with an identification mechanism for preventing unauthorized use, etc.

[0043] Examples of the Transformer-based model include, but are not limited to, GPT (Generative Pre-trained Transformer) (registered trademark), PaLM2 (Pathways Language Model Version 2), or LLaMA (Large Language Model Meta AI). Examples of the RNN-based model include, but are not limited to, RWKV (Receptance Weighted Key Value).

[0044] 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 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.

[0045] 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. The prompt is, for example, information indicating instructions, requests, etc. given to the language model to execute a specific task for the generative AI.

[0046] The information processing apparatus 1 inputs, for example, a prompt including instruction information which is information instructing the generalization of the actions of a plurality of store users before and after visiting a designated store, and part or all of the information acquired in step S1, into the generation AI, and causes the generation AI to output a generalization result of the actions of a plurality of store users before and after visiting the designated store.

[0047] Further, the information processing apparatus 1 inputs, for example, a prompt including instruction information which is information instructing the generalization of the actions of a plurality of store users before, during, and after visiting a designated store, and part or all of the information acquired in step S1, into the generation AI, and causes the generation AI to output a generalization result of the actions of a plurality of store users before, during, and after visiting the designated store. The actions before, during, and after visiting the designated store are the actions before visiting the designated store, the actions at the time of visiting the designated store (during the visit), and the actions after visiting the designated store.

[0048] The information processing apparatus 1 can cause the generation AI to output a generalization result of the actions of a plurality of store users before, during, and after visiting a designated store, for example, by including in the prompt instruction information instructing the generalization of the actions of a plurality of store users before, during, and after visiting the designated store by classifying the actions of a plurality of store users before, during, and after visiting the designated store into a plurality of groups.

[0049] Further, the information processing apparatus 1 can cause the generation AI to output a generalization result of the actions of a plurality of store users before, during, and after visiting a designated store, for example, by including in the prompt instruction information including information showing examples of the characteristics of the actions of a plurality of store users before, during, and after visiting the designated store.

[0050] Further, the information processing apparatus 1 can cause the generation AI to output a generalization result of the actions of a plurality of store users before, during, and after visiting a designated store, for example, by including in the prompt instruction information including information specifying the characteristics to be generalized as the characteristics of the actions of a plurality of store users before, during, and after visiting the designated store.

[0051] The characteristics of the behavior of store users before visiting a designated store include, for example, the characteristic that store users may use specific facilities or specific other stores before visiting the designated store, and the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristic that store users may conduct specific searches before visiting the designated store, and the characteristics indicating the tendency of the posted content, etc., but are not limited to such examples.

[0052] The characteristics of the behavior of store users after visiting a designated store include, for example, the characteristic that store users may use specific facilities or specific other stores after visiting the designated store, and the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristic that store users may post about the designated store on SNS after visiting the designated store, and the characteristics indicating the tendency of the posted content, etc., but are not limited to such examples.

[0053] The information indicating the behavior of store users when visiting a designated store includes, for example, the amount of each payment and the average payment amount of store users in the designated store, the content and genre of the purchased goods and purchased services of store users in the designated store, the length of each stay and the average stay time of store users in the designated store, etc., but are not limited to such examples.

[0054] The information processing device 1, for example, inputs the prompt shown in FIG. 1 to the generative AI and causes the generative AI to output a summary result of the behavior of a plurality of store users before, during, and after visiting the designated store. The prompt shown in FIG. 1 includes instruction information and information necessary for the summarization process. The instruction information also includes information on the output format that defines how to output the characteristics of the behavior of a plurality of store users before, during, and after visiting the store. In the example shown in FIG. 1, the information necessary for the summarization process includes the information of the designated store and the information on the behavior of store users before and after visiting the store.

[0055] Alternatively, instead of using the generative AI, the information processing apparatus 1 can classify the behaviors of a plurality of store users into two or more groups using a classification model. The classification model is, for example, GBDT (Gradient Boosting Decision Tree), a neural network, etc., but is not limited to such examples.

[0056] Also, the generative AI may be a multimodal generative AI, etc. The multimodal generative AI is, for example, a generative AI that generates at least one of text, image, and voice from at least one of text, image, and voice. 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.

[0057] Subsequently, the information processing apparatus 1 provides the service user O with the provided information including the information indicating the result of the generalization process in step S3 (step S4). For example, the information processing apparatus 1 provides the service user O with the provided information by transmitting the provided information including the information indicating the result of the generalization process in step S3 to the terminal device 2. The information processing apparatus 1 provides, for example, the information indicating the characteristics of two or more groups classified in step S3.

[0058] The information processing apparatus 1 provides the service user O with map information showing the result of the generalization process in step S3 on the map as the provided information. The result of the generalization process shown on the map includes, for example, the information indicating the characteristics of each classified group. For example, if the information indicating the characteristics of each group includes the information indicating the locations that are easy for store users to visit, in the map information provided as the provided information, in addition to the information indicating the characteristics of the group, the information emphasizing the locations that are easy for store users to visit is shown on the map.

[0059] In the example shown in FIG. 1, as a result of the generalization process in step S3, information regarding "Café A", which is a place that a store user is likely to visit before coming to the designated store, is shown, and information regarding "Movie Theater D", which is a place that a store user is likely to visit after coming to the designated store, is shown.

[0060] In the above-described example, the information processing apparatus 1 receives a designation of a store in step S1, but can also receive a designation of a facility instead of the store. The facility is, for example, a commercial facility (including a complex commercial facility), a movie theater, a sports gym, a hospital, a library, a school, a public facility, etc., but is not limited to such examples.

[0061] In this case, in step S2, the information processing apparatus 1 acquires information of a plurality of facility users who are users who have used the designated facility, which is the facility designated in step S1, and which indicates the actions of the plurality of facility users before and after (or before, during, and after) the use of the designated facility. Before, during, and after the use of the designated facility means before the use of the designated facility, during the use of the designated facility, and after the use of the designated facility. The information indicating the actions of the users who use the facility is the same information as the information indicating the actions of the above-described store users.

[0062] Also, in step S3, the information processing apparatus 1 performs a generalization process of generalizing the actions of the plurality of facility users before and after (or before, during, and after) the use of the designated facility based on the information indicating the actions of the plurality of facility users before and after (or before, during, and after) the use of the designated facility, which is the information acquired in step S2. The method of generalizing the actions of the plurality of facility users is the same as the method of generalizing the actions of the plurality of store users.

[0063] Note that the information processing apparatus 1 can also classify users according to their intentions or purposes of using the store or facility, instead of or in addition to the characteristics of the users before and after (or before, during, and after) the use of the store or facility, based on the information indicating the actions of the plurality of users before and after (or before, during, and after) the use of the store or facility.

[0064] In this way, the information processing apparatus 1 receives a designation of a store or a facility, acquires information of a plurality of users who have used the store or facility that has been designated, the information indicating the actions of the plurality of users before and after using the store or facility, generalizes the actions of the plurality of users before and after using the store or facility based on the acquired information indicating the actions of the plurality of users before and after using the store or facility, and provides the generalized result.

[0065] Thereby, the information processing apparatus 1 can support the operation strategy in a store or a facility. For example, the service user O can formulate an operation strategy for the designated store or designated facility from the actions of the store users before and after using the designated store or designated facility based on the result of generalizing the actions of the plurality of store users before and after using the designated store or designated facility.

[0066] For example, the service user O can efficiently distribute an advertisement for the designated store or designated facility by providing advertisement content to other stores or facilities that store users or facility users often visit before and after using the designated store or designated facility.

[0067] Also, the service user O can grasp that there is a high possibility that store users or facility users may have dissatisfaction when going to other stores or facilities of the same genre as the designated store or designated facility after using the designated store or designated facility. Also, in the reverse case, the service user O can grasp that there is a high possibility that other stores or facilities may have dissatisfaction.

[0068] Hereinafter, the configuration of the information processing system including the information processing apparatus 1 and the terminal device 2 that perform such processing will be described in detail.

[0069] 〔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 devices 2.

[0070] The plurality of terminal devices 2 are used by different service users O. The terminal device 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.

[0071] Each of the information processing device 1 and the terminal device 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 devices 1 and the like.

[0072] 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.

[0073] 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.

[0074] 〔3. Configuration of 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.

[0075] 〔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 other various devices. For example, the communication unit 10 transmits and receives information to and from the terminal device 2 via the network N.

[0076] [3.2. Memory Unit 11] The memory 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 memory unit 11 includes a user information storage unit 20, a location information storage unit 21, a geographical information storage unit 22, and a content storage unit 23.

[0077] [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".

[0078] 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 or 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, thoughts, and trends of thoughts.

[0079] 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 usage history of stores and facilities, information indicating the user's usage history of transportation means, etc., but is not limited to such examples.

[0080] The information indicating the user's usage history of stores and facilities is, for example, each payment amount or average payment amount of the user in the store or facility, the content and genre of the purchased goods and services of the user in the store or facility, each stay time or average stay time of the user in the store or facility, etc., but is not limited to such examples.

[0081] [3.2.2. Location Information Storage Unit 21] The location information storage unit 21 stores information on various locations (such as stores and facilities). FIG. 5 is a diagram showing an example of a location information table stored in the location information storage unit 21 of the information processing apparatus 1 according to the embodiment. As shown in FIG. 5, the location information table stored in the location information storage unit 21 includes items such as "Location ID", "Location Position", "Location Name", "Location Type", and "Location Information".

[0082] The "Location ID" is identification information for identifying a location such as a store or a facility. The "Location Position" is information indicating the position of the location corresponding to the "Location ID", for example, information indicating the latitude and longitude of the location. The "Location Name" is information indicating the name of the location corresponding to the "Location ID". When the location is a store and 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.

[0083] The "Location Type" is information indicating the type of the location corresponding to the "Location ID", for example, information indicating the genre of the location. The "Location Information" is information on the location corresponding to the "Location ID". For example, when the location is a store, it is information on products and services. When the location is a facility, it is information indicating objects and services provided by the facility.

[0084] Although not shown, the location information storage unit 21 may include information indicating the sales of the location, information indicating the area of the location, information indicating the number of employees at the location, and the like.

[0085] [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, news article information, disaster information, information on facilities and stores, weather information, etc., but is not limited to such examples.

[0086] [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 related to stores, posting information to communication services related to stores, word-of-mouth posts about stores on word-of-mouth sites, advertising information of stores, weather information, etc., but are not limited to such examples.

[0087] [3.3. Processing unit 12] The processing unit 12 is a controller and is realized, for example, by a processor such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the information processing apparatus 1 using a RAM or the like as a work area.

[0088] Also, the processing unit 12 is a controller and may be partially or entirely 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).

[0089] As shown in FIG. 3, the processing unit 12 includes a reception unit 30, an acquisition unit 31, an analysis unit 32, and a provision unit 33, and realizes or executes the functions and operations of information processing described below. Note that the internal configuration of the processing unit 12 is not limited to the configuration shown in FIG. 3, and may be any other configuration as long as it performs the information processing described later.

[0090] [3.3.1. Reception unit 30] The reception unit 30 receives various types of information. For example, the reception unit 30 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.

[0091] In addition, the reception unit 30 receives a designation of a store or facility. For example, the reception unit 30 receives a designation of a store or facility by the service user O by receiving a general information request that includes information indicating the designation of the store or facility by the service user O and is transmitted from the terminal device 2.

[0092] 〔3.3.2. Acquisition Unit 31〕 The acquisition unit 31 acquires various types of information from an external information processing device, the terminal device 2, etc. via the network N and the communication unit 10.

[0093] For example, the acquisition unit 31 acquires user information from an external information processing device and stores the acquired user information in the user information storage unit 20. Also, the acquisition unit 31 acquires store or facility information from an external information processing device and stores the acquired store or facility information in the location information storage unit 21.

[0094] In addition, the acquisition unit 31 acquires geographical information from an external information processing device and stores the acquired geographical information in the geographical information storage unit 22. Also, the acquisition unit 31 acquires various types of content from an external information processing device and stores the acquired various types of content in the content storage unit 23.

[0095] In addition, the acquisition unit 31 acquires various types of information from the storage unit 11. For example, the acquisition unit 31 acquires user information from the user information storage unit 20, acquires store or facility information from the location information storage unit 21, acquires geographical information from the geographical information storage unit 22, and acquires content from the content storage unit 23.

[0096] For example, when the acquisition unit 31 receives a designation of a store or facility by the reception unit 30, it acquires information on the designated facility, which is the store or facility designated by the reception unit 30, or information on a plurality of users who have used the designated facility, and information indicating the actions of the plurality of users before and after using the designated facility or designated facility.

[0097] In addition, when the acquisition unit 31 receives a designation of a store or facility by the reception unit 30, it can further acquire information on a plurality of users who have used the designated facility or designated facility, and information indicating the actions of the plurality of users when using the designated facility or designated facility.

[0098] The information indicating the actions of the location users includes, for example, information indicating the online actions of the location users and information indicating the offline actions of the location users. The online actions of the location users are, for example, the online search actions of the location users (such as web searches), the browsing of online content by the location users, etc.

[0099] Online content includes, for example, blog articles, news articles, video content, music content, posted content on SNS, posted content on review sites, etc., but is not limited to such examples.

[0100] The information indicating the offline actions of the location users includes, for example, information indicating other locations (other stores and other facilities) used by the location users and information indicating the usage content thereof, information indicating the transportation means used by the location users and the section thereof, information indicating the movement route traveled by the location users, etc.

[0101] In addition, the acquisition unit 31 can also acquire information on a plurality of location users who have used the designated location, and information indicating the actions of the plurality of location users when using the designated location. When the designated location is a store, the use of the designated location is, for example, coming to the store, purchasing goods or services at the store, etc. When the designated location is a facility, the use of the designated location is, for example, visiting the facility, using equipment or services within the facility, etc., but is not limited to such examples.

[0102] Information indicating the behavior of location users when using a designated location includes, for example, each payment amount or average payment amount of location users at the designated location, the content and genre of purchased goods and services of location users at the designated location, each stay time or average stay time of location users at the designated location, etc., but is not limited to such examples. Each payment amount or average payment amount of location users is, for example, each settlement amount or average settlement amount of location users, but is not limited to such examples.

[0103] The acquisition unit 31 acquires, for example, as information indicating the behavior of a plurality of location users before and after using a designated location, information indicating the behavior of a plurality of location users up to a predetermined period before using the designated location and information indicating the behavior of a plurality of location users up to a predetermined period after using the designated location, but is not limited to such examples.

[0104] In addition, the acquisition unit 31 can also acquire information about the designated location. The information about the designated location includes information indicating the location of the designated location, information indicating the name of the designated location, information indicating the type of the designated location, information about the products of the designated location, etc. The information indicating the location of the designated location is, for example, information indicating the latitude and longitude of the designated location.

[0105] The information indicating the name of the designated location includes, when the designated location is a store, information indicating the chain name when the designated store is a chain store, and information indicating the franchise name when the designated store is a franchise store. The information indicating the type of the designated location is information indicating the genre of the location, for example, information indicating genres such as convenience store, grocery store, clothing store, supermarket, café, restaurant, fast food restaurant, izakaya, etc. Note that the genre of the store may be a further subdivided genre. The information about the products and services of the designated location is information about the products and services sold at the designated location.

[0106] In addition, the acquisition unit 31 can also acquire information indicating the behavior of store users by limiting it to the information of store users who meet specific conditions. The specific conditions are, for example, information set by the service user O, and the information indicating the specific conditions is included in, for example, a general information request or the like.

[0107] The specific conditions are, for example, the attributes of the location users, the type of the location where the location users stay, other locations (other stores or other facilities) used by the location users, the means of transportation used by the location users, the purchase of specific products or the use of specific services by the location users at the designated location, the average stay time of the location users at the designated location, etc., but are not limited to such examples. Note that the acquisition unit 31 can also acquire information indicating the behavior of store users by limiting it to the information of a specific time period designated by the service user O.

[0108] In addition, the acquisition unit 31 can also acquire information indicating the attributes of each of the multiple location users. The information indicating the attributes of the location users is demographic attributes or psychographic attributes of the location users, etc. 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, thoughts and trends of thoughts, etc.

[0109] [3.3.3. Analysis Unit 32] Based on the information indicating the behavior of multiple users before and after the use of the designated store or designated facility acquired by the acquisition unit 31, the analysis unit 32 generalizes the behavior of multiple users before and after the use of the designated store or designated facility. Hereinafter, there are cases where the designated store or designated facility is described as the designated location, and the users of the designated store or designated facility are described as location users.

[0110] The analysis unit 32 can generalize the behavior of multiple location users, for example, by classifying the behavior of multiple location users into two or more groups. The analysis unit 32 classifies the behavior of multiple location users into two or more groups, for example, based on the characteristics of the behavior of the location users before the use of the designated location and the characteristics of the behavior of the location users after the use of the designated location.

[0111] The characteristics of the actions of the location users before using the designated store are, for example, the characteristics that the location users may use specific facilities or specific other stores before using the designated location, the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristics that the location users may conduct specific searches before using the designated location, the characteristics indicating the tendency of the posted content thereof, etc., but are not limited to such examples.

[0112] The characteristics of the actions of the location users after using the designated location are, for example, the characteristics that the location users may use specific facilities or specific other stores after using the designated location, the characteristics indicating the tendency of the usage content in such facilities or stores, the characteristics that the location users may post about the designated location on the SNS after using the designated location, the characteristics indicating the tendency of the posted content thereof, etc., but are not limited to such examples.

[0113] In addition, based on the actions of the location users after using the designated location, the analysis unit 32 can also determine the satisfaction or dissatisfaction with the designated location as an evaluation of the designated store. For example, the analysis unit 32 determines the satisfaction or dissatisfaction with the designated location based on the posted content about the designated store on the SNS, the posted content in the communication service, etc. In addition, the analysis unit 32 can also determine the satisfaction or dissatisfaction with the designated store based on the word-of-mouth posts about the designated store on the word-of-mouth site.

[0114] In addition, the analysis unit 32 can also determine a plurality of location users who perform actions common to the location users with high satisfaction or low dissatisfaction as the location users with high satisfaction or low dissatisfaction with the designated location, and determine a plurality of location users who perform actions common to the location users with low satisfaction or high dissatisfaction as the location users with low satisfaction or high dissatisfaction with the designated location.

[0115] For example, the analysis unit 32 designates a place user who has answered in a questionnaire or the like that the satisfaction level is high or the dissatisfaction level is low as a place user with a high satisfaction level or a low dissatisfaction level with respect to the designated place, and designates a place user who has answered in a questionnaire or the like that the satisfaction level is low or the dissatisfaction level is high as a place user with a low satisfaction level or a high dissatisfaction level with respect to the designated place. Based on these place users, the analysis unit 32 determines the degree of satisfaction with respect to the designated place.

[0116] Further, when the information acquired by the acquisition unit 31 includes information indicating the actions of a plurality of place users when using the designated place, the analysis unit 32 can summarize the actions of a plurality of place users before, during, and after using the designated store based on the information indicating the actions of a plurality of place users before and after using the designated place and the information indicating the actions of a plurality of place users when using the designated place.

[0117] For example, the analysis unit 32 classifies the actions of a plurality of place users into two or more groups based on the characteristics of the actions of the place users before using the designated place, the characteristics of the actions of the place users when using (during use) the designated place, and the characteristics of the actions of the place users after using the designated place.

[0118] The characteristics of the actions of the place users after using the designated place are, for example, characteristics such as the average stay time of the place users at the designated place being short or long, the average moving distance of the place users at the designated place being short or long, the average payment amount of the place users at the designated place being small or large, etc., but are not limited to such examples.

[0119] The analysis unit 32 can also classify the actions of a plurality of store users into two or more groups for each of the characteristics of the actions of the store users before visiting the designated store, the characteristics of the actions of the store users when visiting (during the visit) the designated store, and the characteristics of the actions of the store users after visiting the designated store.

[0120] The analysis unit 32 performs the above-described summarization process using a generative AI. 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-based model, etc., but may also be a hybrid model thereof. Further, the text generation AI may be a composite system combined with an identification mechanism for preventing unauthorized use, etc.

[0121] The Transformer-based model is, for example, GPT, PaLM2, or LLaMA, etc., but is not limited to such examples. The RNN-based model is, for example, RWKV, etc., but is not limited to such examples.

[0122] Note that it is desirable that the generative AI 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 also be arranged within the information processing device 1.

[0123] 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. The prompt is, for example, information indicating instructions, requests, etc. given to the generative AI to perform a specific task.

[0124] The analysis unit 32 inputs a prompt including, for example, instruction information that is information instructing the summarization of the actions of a plurality of location users before and after the use of a specified location, and a part or all of the information acquired by the acquisition unit 31, to the generative AI, and causes the generative AI to output a summarization result of the actions of a plurality of location users before and after the use of the specified location.

[0125] Further, for example, the analysis unit 32 inputs a prompt including instruction information containing information instructing a summary of the actions of a plurality of location users before, during, and after the use of a designated location, and part or all of the information acquired in step S1, into the generation AI, and causes the generation AI to output a summary result of the actions of a plurality of location users before, during, and after the use of the designated location. The actions before, during, and after the use of the designated location are the actions before the use of the designated location, the actions during the use (while using) of the designated location, and the actions after the use of the designated location.

[0126] The instruction information includes, for example, information instructing an analysis of the actions of a location user before the use of the designated location, information instructing an analysis of the actions of a location user during the use (while using) of the designated location, information instructing an analysis of the actions of a location user after the use of the designated location, information instructing a summary of the results of each action analysis, and the like.

[0127] For example, the analysis unit 32 can cause the generation AI to output a summary result of the actions of a plurality of location users before, during, and after the use of the designated location by including, in the prompt, instruction information instructing a summary of the actions of a plurality of location users by classifying the actions of a plurality of location users before, during, and after the use of the designated location into a plurality of groups.

[0128] Further, for example, the analysis unit 32 can cause the generation AI to output a summary result of the actions of a plurality of location users before, during, and after the use of the designated location by including, in the prompt, instruction information including information showing examples of the characteristics of the actions of a plurality of location users before, during, and after the use of the designated location.

[0129] Further, for example, the analysis unit 32 can cause the generation AI to output a summary result of the actions of a plurality of location users before, during, and after the use of the designated location by including, in the prompt, instruction information including information specifying the characteristics to be summarized as the characteristics of the actions of a plurality of location users before, during, and after the use of the designated location.

[0130] The characteristics of the behavior of a location user before using a specified location include, for example, the characteristic that the location user may use a specific facility or a specific other store before using the specified location, the characteristic indicating the tendency of the usage content in that facility or store, the characteristic that the location user may conduct a specific search before using the specified location, the characteristic indicating the tendency of the content of that post, etc., but are not limited to such examples.

[0131] The characteristics of the behavior of a location user after using a specified location include, for example, the characteristic that the location user may use a specific facility or a specific other store after using the specified location, the characteristic indicating the tendency of the usage content in that facility or store, the characteristic that the location user may post about the specified location on SNS after using the specified location, the characteristic indicating the tendency of the content of that post, etc., but are not limited to such examples.

[0132] The information indicating the behavior of a location user when using a specified location includes, for example, each payment amount and average payment amount of the location user at the specified location, the content and genre of the purchased goods and purchased services of the location user at the specified location, each stay time and average stay time of the location user at the specified location, etc., but are not limited to such examples.

[0133] In addition, the analysis unit 32 can also analyze the intention to use a specified location by using generative AI or statistical processing. For example, the analysis unit 32 can analyze the intention to use a specified location by using generative AI by inputting a prompt including instruction information containing information instructing the analysis of the intention to use a specified location into the generative AI.

[0134] 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 inputs, for example, the prompt shown in FIG. 6 into the generative AI and causes the generative AI to output a summary result of the behavior of a plurality of store users before, during, and after visiting a specified store.

[0135] The prompt shown in FIG. 6 includes instruction information and information necessary for summarization processing. The instruction information includes, for example, information instructing the behavior analysis before coming to the store, information instructing the behavior analysis during the store visit (at the time of coming to the store), information instructing the behavior analysis after coming to the store, information instructing the summary of the results of each behavior analysis, and the like. In the example shown in FIG. 6, as the information necessary for summarization processing, information on the designated store and information on the behavior of the store user before and after coming to the store are included.

[0136] The information instructing each behavior analysis also includes information indicating the type of information used in the analysis, information instructing the classification of the characteristics of the behavior of the store user, and information indicating points to note during classification. In addition, the instruction information of the prompt shown in FIG. 6 includes, for example, information indicating the upper limit value of the number of classifications of the store user, information indicating points to note during consideration, information indicating how to summarize the title and description, information indicating the expression method, and the like.

[0137] Also, the instruction information of the prompt shown in FIG. 6, as information instructing the summary of the results of each behavior analysis, is the information of the character string "Summarize and output\n-Summarize information for each user classification\n-Contents: Title of the user group, description of the user group, position information where characteristic behaviors were performed before, during, and after coming to the store, several behaviors each, average satisfaction, dissatisfaction points".

[0138] For example, as information on the output format that defines how to output the characteristics of the behaviors of a plurality of store users before, during, and after coming to the designated store, the information of the character string "Connect the three elements with "\t" separation\n-Bullet points are separated by line breaks, and the beginning of each is "."" is included, but it 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.

[0139] 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, for example, the prompt shown in FIG. 7 to the generation AI, and causes the generation AI to output the summary result of the behaviors of a plurality of facility users before, during, and after coming to the designated facility based on the analysis of the usage intention of the facility.

[0140] The instruction information of the prompt shown in FIG. 7 includes, for example, information for instructing the extraction of the usage intention of the facility user (facility resident), information for instructing the behavior analysis before facility use (before visiting the facility), information for instructing the behavior analysis during facility use (during visiting the facility), information for instructing the behavior analysis after facility use (after visiting the facility), and the like.

[0141] The information for instructing the extraction of the usage intention of the facility user includes, for example, information indicating the type of information used for extraction, information indicating the granularity of the classification of the usage intention, information indicating points to note during the classification of the usage intention, and the like. Thereby, the analysis unit 32 can analyze the usage intention of the designated facility using the generation AI. The same applies to the designated location.

[0142] The information for instructing each behavior analysis includes, for example, information indicating the type of information used for the analysis, information indicating the classification of the characteristics of the behavior of the store user and points to note during the classification, information indicating the upper limit value of the number of classifications of the store user, and the like.

[0143] The instruction information of the prompt shown in FIG. 7 includes, as information on the output format for defining how to output the characteristics of the behavior of multiple relocated users before, during, and after the use of the facility, the character string "The three elements are connected by '\t'\n· The bullet points are separated by line breaks, and the beginning of each is '.' 5. Summarize and output\n- For each user classification, obtain information\n- The content is the title of the user group, the description of the user group, the characteristic behavior before visiting, the characteristic behavior during visiting, the characteristic behavior after visiting, and the points of satisfaction / dissatisfaction with the facility", but is not limited to such examples. Note that in the prompt shown in FIG. 7, a part of the information other than the instruction information is omitted.

[0144] In addition, instead of using the generation AI, the analysis unit 32 can classify the behaviors of multiple location users into two or more groups using a classification model. The classification model is, for example, GBDT, a neural network, etc., but is not limited to such examples.

[0145] Also, the generative AI may be, for example, a multimodal generative AI. The multimodal generative AI is 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, etc.

[0146] [3.3.4. Provision Unit 33] The provision unit 33 provides various information to the service user O. For example, the provision 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.

[0147] For example, when a usage request is received by the reception unit 30, the provision unit 33 provides the store designation information to the service user O by transmitting the store designation information including the list information indicating the list of stores existing in the designated area and the map information of the designated area to the terminal device 2.

[0148] When the terminal device 2 receives the store designation information transmitted from the information processing device 1, it displays the list information indicating the list of stores existing in the designated area and the map information of the designated area based on the received store designation information. 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 the stores existing in the designated area are arranged individually and can be designated on the map.

[0149] Service user O can specify a store 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. When there is a specification of a store or a store graphic by service user O, the terminal device 2 transmits a general information request including information indicating the store specified by service user O or information indicating the store corresponding to the store graphic specified by service user O as store information to the information processing device 1.

[0150] Also, when the reception unit 30 receives a general information request, the providing unit 33 provides the service user O with the provided information by transmitting the provided information including the information indicating the result of the generalization process by the analysis unit 32 to the terminal device 2. The providing unit 33 provides, for example, information indicating the characteristics of two or more groups classified by the analysis unit 32.

[0151] The providing unit 33 provides the service user O with map information showing the result of the generalization process on the map as the provided information. The result of the generalization process shown on the map includes, for example, information indicating the characteristics of each classified group. For example, when the information indicating the characteristics of each group includes information indicating a location that is easy for the store user to visit, in the map information provided as the provided information, in addition to the information indicating the characteristics of the group, information emphasizing the location that is easy for the store user to visit is shown on the map.

[0152] 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 a result of the generalization process by the analysis unit 32, information regarding "Cafe A" as a location that is easy for the store user to visit before coming to the designated store and information regarding "Movie Theater D" as a location that is easy for the store user to visit after coming to the designated store are shown.

[0153] Specifically, as information about "Café A", the information string "· Easy for User Group A and User Group C to visit before coming to the store\n· Both user groups have a high satisfaction level with the target store\n· Relax and review the experience at the store with friends" is included in the provided information. Also, as information about "Movie Theater D", the information string "· Easy for User Group B to visit after coming to the store\n· Low satisfaction level with the target store\n· Go to watch mainstream movies to enhance the satisfaction of the day\n· The dissatisfaction point is that the cycle of new releases is slow" is included in the provided information.

[0154] [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.

[0155] As shown in FIG. 9, the processing unit 12 of the information processing apparatus 1 determines whether it has received a usage request from the service user O (step S10). When the processing unit 12 determines that it has received a usage request from the service user O (step S10: Yes), it provides store designation information to the service user O (step S11).

[0156] When the processing of step S11 is completed, or when the processing unit 12 determines that it has not received a usage request from the service user O (step S10: No), it determines whether it has received a general information request from the service user O (step S12).

[0157] When the processing unit 12 determines that it has received a general information request from the service user O (step S12: Yes), it acquires information indicating the actions of multiple users before, during, and after the use of the designated location from the storage unit 11 etc. (step S13). Then, based on the information acquired in step S13, the processing unit 12 summarizes the actions of multiple location users before, during, and after the use of the designated location (step S14), and provides provided information including information indicating the summarization result of step S14 (step S15).

[0158] When the process in step S15 is completed, or when it is determined that a general information request from the service user O has not been received (step S12: No), the processing unit 12 determines whether the operation end timing has arrived (step S16). For example, the processing unit 12 determines that the operation end timing has arrived when the power of the information processing apparatus 1 is turned off.

[0159] When the processing unit 12 determines that the operation end timing has not arrived (step S16: No), the process proceeds to step S10. When the processing unit 12 determines that the operation end timing has arrived (step S16: Yes), the process shown in FIG. 9 is terminated.

[0160] 〔5. Modification Example〕 For example, in the generalization process, the analysis unit 32 estimates the moving speed of the store user before and after using the designated location based on the information indicating the location history of the store user, and can generalize the moving speed of the store user before and after using the designated location as part or all of the actions of the store user before and after using the designated location.

[0161] In addition, in the generalization process, the analysis unit 32 can also generalize the actions of the location user before, during, and after using the designated location for each predetermined period based on information such as the actions of the location user before, during, and after using the designated location for each predetermined period. In this case, the providing unit 33 can also provide map information that shows on the map while automatically switching the generalization results for each predetermined period estimated in the estimation process in time series.

[0162] In addition, for example, the analysis unit 32 can also perform the overall control process by dividing it into a plurality of processes. For example, the analysis unit 32 includes a first process for determining the characteristics of the actions of the location user before using the designated location, a second process for determining the characteristics of the actions of the location user while using the designated location, a third process for determining the characteristics of the actions of the location user after using the designated location, and a fourth process for summarizing the results of the first process, the results of the second process, and the results of the third process. A plurality of processes can be performed as the generalization process.

[0163] In this case, in the first process, the analysis unit 32 inputs, to the generation AI, instruction information for instructing determination of characteristics of the actions of the location user before using the designated location and a prompt including information necessary for determining the actions of the location user before using the designated location, and causes the generation AI to output information indicating the characteristics of the actions of the location user before using the designated location.

[0164] Also, in the second process, the analysis unit 32 inputs, to the generation AI, instruction information for instructing determination of characteristics of the actions of the location user while using the designated location and a prompt including information necessary for determining the actions of the location user while using the designated location, and causes the generation AI to output information indicating the characteristics of the actions of the location user while using the designated location.

[0165] Also, in the third process, the analysis unit 32 inputs, to the generation AI, instruction information for instructing determination of characteristics of the actions of the location user after using the designated location and a prompt including information necessary for determining the actions of the location user after using the designated location, and causes the generation AI to output information indicating the characteristics of the actions of the location user after using the designated location.

[0166] Also, in the fourth process, the analysis unit 32 inputs, to the generation AI, instruction information for instructing summarization of the results of the first process, the results of the second process, and the results of the third process and a prompt including information indicating the results of the first process, the results of the second process, and the results of the third process, and causes the generation AI to output information indicating a comparison result summarizing the actions of the location user before, during, and after use of the designated location.

[0167] Also, in the above-described example, the reception unit 30 receives designation of one location, but may also receive designations of a plurality of locations as a designation of one group. In this case, the acquisition unit 31 acquires information on actions before, during, and after use of the plurality of locations. The analysis unit 32 can summarize the actions of a plurality of users before and after use of one group based on the information on actions before, during, and after use of the plurality of locations. One group is, for example, a group of a plurality of stores in a commercial facility.

[0168] 〔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.

[0169] The CPU 81 operates based on programs 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 starts up, programs dependent on the hardware of the computer 80, and the like.

[0170] The HDD 84 stores programs executed by the CPU 81, data used by such programs, 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.

[0171] 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.

[0172] 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.

[0173] 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, but as another example, these programs may be acquired from other devices via the network N.

[0174] 〔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 document 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.

[0175] 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.

[0176] For example, the information processing apparatus 1 described above may be implemented by a terminal device and a server computer, or may be implemented by a plurality of server computers. Also, depending on the functions, the configuration can be flexibly changed, such as by calling an external platform or the like using an API or network computing.

[0177] In addition, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not conflict.

[0178] 〔8. Effect〕 As described above, the information processing apparatus according to the embodiment includes a reception unit 30, an acquisition unit 31, an analysis unit 32, and a provision unit 33. The reception unit 30 receives a designation of a store or a facility. The acquisition unit 31 acquires information of a plurality of users who have used the store or facility designated by the reception unit 30, and information indicating the actions of the plurality of users before and after using the store or facility. The analysis unit 32 generalizes the actions of the plurality of users before and after using the store or facility based on the information indicating the actions of the plurality of users before and after using the store or facility acquired by the acquisition unit 31. The provision unit 33 provides the generalization result by the analysis unit 32. Thereby, the information processing apparatus 1 can support the analysis of users of stores and facilities.

[0179] In addition, the acquisition unit 31 further acquires information of a plurality of users who have used the store or facility, and information indicating the actions of the plurality of users when using the store or facility. The analysis unit 32 generalizes the actions of the plurality of users before, during, and after using the store or facility based on the information indicating the actions of the plurality of users before and after using the store or facility and the information indicating the actions of the plurality of users when using the store or facility acquired by the acquisition unit 31. Thereby, the information processing apparatus 1 can more effectively support the analysis of users of stores and facilities.

[0180] In addition, the analysis unit 32 generalizes the actions of a plurality of users by classifying the actions of the plurality of users into two or more groups. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0181] In addition, the providing unit 33 provides information indicating the characteristics of two or more groups classified by the analysis unit 32. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0182] In addition, the analysis unit 32 analyzes the intention of using the store or facility. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0183] In addition, the analysis unit 32 generalizes the actions of a plurality of users by using a generative AI. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0184] In addition, the information indicating actions includes information indicating online actions and information indicating offline actions. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0185] In addition, the analysis unit 32 determines the evaluation of a plurality of users with respect to the store or facility. Thereby, the information processing apparatus 1 can more effectively support the analysis of the users of the store or facility.

[0186] 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.

[0187] In addition, the above-described "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.

Explanation of Reference Numerals

[0188] 1 Information processing device 2 Terminal device 10 Communication unit 11 Memory unit 12 Processing unit 20 User information memory unit 21 Location information memory unit 22 Geographic information memory unit 23 Content memory unit 30 Reception unit 31 Acquisition unit 32 Analysis unit 33 Provision unit 100 Information processing system N Network

Claims

1. a reception unit that receives a designation of a store or a facility; an acquisition unit that acquires information on a plurality of users who have used the store or the facility designated by the reception unit, the information indicating the actions of the plurality of users before and after using the store or the facility; an analysis unit that generalizes the actions of the plurality of users before and after using the store or the facility based on the information indicating the actions of the plurality of users before and after using the store or the facility acquired by the acquisition unit; a provision unit that provides the generalization result by the analysis unit, and comprising an information processing apparatus characterized by the above.

2. The acquisition unit further acquires information on a plurality of users who have used the store or the facility, the information indicating the actions of the plurality of users at the time of using the store or the facility, The analysis unit generalizes the actions of the plurality of users before, during, and after using the store or the facility based on the information indicating the actions of the plurality of users before and after using the store or the facility and the information indicating the actions of the plurality of users at the time of using the store or the facility acquired by the acquisition unit The information processing apparatus according to claim 1, characterized by the above.

3. The analysis unit generalizes the actions of the plurality of users by classifying the actions of the plurality of users into two or more groups The information processing apparatus according to claim 2, characterized by the above.

4. The provision unit provides information indicating the characteristics of two or more groups classified by the analysis unit The information processing apparatus according to claim 3, characterized by the above.

5. The analysis unit analyzes the intention of using the store or the facility The information processing apparatus according to claim 4, characterized by the above.

6. The analysis unit generalizes the actions of the plurality of users using a generative AI The information processing apparatus according to any one of claims 1 to 5, characterized by the above.

7. The information indicating the actions includes information indicating online actions and information indicating offline actions The information processing apparatus according to any one of claims 1 to 5, characterized by the above.

8. The analysis unit determines the evaluation of the plurality of users with respect to the store or the facility The information processing apparatus according to any one of claims 1 to 5, characterized by the above.

9. An information processing method executed by a computer, comprising a reception step of receiving a designation of a store or a facility; An acquisition step of acquiring information of a plurality of users who used the store or the facility whose designation was received in the reception step, the information indicating the actions of the plurality of users before and after using the store or the facility; An analysis step of generalizing the actions of the plurality of users before and after using the store or the facility based on the information indicating the actions of the plurality of users before and after using the store or the facility acquired in the acquisition step; A provision step of providing a generalization result by the analysis step, and An information processing method characterized by the above.

10. A reception procedure for receiving a designation of a store or a facility; An acquisition procedure for acquiring information of a plurality of users who used the store or the facility whose designation was received in the reception procedure, the information indicating the actions of the plurality of users before and after using the store or the facility; An analysis procedure for generalizing the actions of the plurality of users before and after using the store or the facility based on the information indicating the actions of the plurality of users before and after using the store or the facility acquired in the acquisition procedure; Causing a computer to execute a provision procedure for providing a generalization result by the analysis procedure, and An information processing program characterized by the above.

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