JP2022050252A - Information processing device, information processing method and information processing program - Google Patents

Abstract

To propose which brand is good as a new brand, in accordance with a relationship between existing brands and brands to be attracted.SOLUTION: An information processing device comprises an acquisition unit, a calculation unit and a generation unit. The acquisition unit acquires history information related to the action of users with respect to brands. The calculation unit calculates the degree of association of one brand and another on the basis of history information. The generation unit generates a scatter chart in which the degree of association of one brand and another is visualized. For example, the generation unit generates a scatter chart, of which the vertical axis represents the number of duplicate associations with existing brands and the horizontal axis represents the average degree of association with existing brands. Alternatively, the generation unit generates a scatter chart, of which the vertical axis represents the affinity with users having visited a prescribed area where brands exist and the horizontal axis represents the affinity with users of electronic payment. Furthermore, the generation unit may generate a three-dimensional scatter chart in which the degree of association of one brand with another is visualized.SELECTED DRAWING: Figure 1

Description

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

Technology that supports understanding of relationships between stores is disclosed through customer information for each store.

Japanese Unexamined Patent Publication No. 2018-097628

However, the above-mentioned prior art merely shows a store correlation diagram regarding the relationship between existing stores, and does not consider the relationship between a specific brand and the existing brand. Therefore, it cannot be said that it provides useful information when attracting new brands according to the relationship between brands.

The present application has been made in view of the above, and an object of the present application is to propose what kind of brand is good as a new brand according to the relationship between the existing brand and the brand to be attracted.

The information processing apparatus according to the present application has an acquisition unit that acquires history information regarding user behavior with respect to a brand, a calculation unit that calculates the degree of relevance between brands based on the history information, and a relevance degree between the brands. It is characterized by including a generation unit for generating a visualized scatter plot.

According to one aspect of the embodiment, it is possible to propose what kind of brand is good as a new brand according to the relationship between the existing brand and the brand to be attracted.

FIG. 1 is an explanatory diagram showing a first outline of the information processing method according to the embodiment. FIG. 2 is an explanatory diagram showing a second outline of the information processing method according to the embodiment. FIG. 3 is an explanatory diagram showing a third outline of the information processing method according to the embodiment. FIG. 4 is a diagram showing a configuration example of an information processing system according to an embodiment. FIG. 5 is a diagram showing a configuration example of the terminal device according to the embodiment. FIG. 6 is a diagram showing a configuration example of the information processing apparatus according to the embodiment. FIG. 7 is a diagram showing an example of a user information database. FIG. 8 is a diagram showing an example of a history information database. FIG. 9 is a diagram showing an example of a relevance information database. FIG. 10 is a diagram showing an example of a compatibility information database. FIG. 11 is a flowchart showing a processing procedure according to the embodiment. FIG. 12 is a diagram showing an example of a hardware configuration.

Hereinafter, an information processing apparatus, an information processing method, and an embodiment for implementing an information processing program (hereinafter referred to as “embodiment”) according to the present application will be described in detail with reference to the drawings. Note that this embodiment does not limit the information processing apparatus, information processing method, and information processing program according to the present application. Further, in the following embodiments, the same parts are designated by the same reference numerals, and duplicate description is omitted.

[1. Overview of information processing method]
First, with reference to FIGS. 1, 2 and 3, an outline of an information processing method performed by the information processing apparatus according to the embodiment will be described. FIG. 1 is an explanatory diagram showing a first outline of the information processing method according to the embodiment. FIG. 2 is an explanatory diagram showing a second outline of the information processing method according to the embodiment. FIG. 3 is an explanatory diagram showing a third outline of the information processing method according to the embodiment. In this embodiment, a scatter diagram (point graph) is created based on a plurality of different relationships between a new brand (candidate brand) and an existing brand. The dots drawn in the scatter plots shown in FIGS. 1, 2 and 3 indicate each brand. Each point increases according to the number of times each brand appears in the user's history information (number of appearances).

In FIG. 1, a scatter plot relating to the degree of relevance (relationship) with an existing brand will be described as an example. Further, in FIG. 2, a case of creating a scatter plot relating to compatibility with the user will be described as an example. Further, in FIG. 3, a case of creating a three-dimensional scatter plot (3D scatter plot) relating to compatibility with existing brands and users will be described as an example.

As shown in FIGS. 1, 2 and 3, the information processing system 1 includes a terminal device 10, an information providing device 100, and a store device 200. The terminal device 10, the information providing device 100, and the store device 200 are connected to each other via a network N (see FIG. 4) so as to be able to communicate with each other by wire or wirelessly.

The terminal device 10 is a smart device such as a smartphone or tablet used by the user U, and communicates with an arbitrary server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). It is a portable terminal device that can be used. Further, the terminal device 10 is a screen of a liquid crystal display or the like and has a screen having a touch panel function, and the user can use a finger, a stylus, or the like to perform a tap operation, a slide operation, a scroll operation, or the like for display data such as contents. Accepts various operations. The operation performed on the area of the screen on which the content is displayed may be an operation on the content. Further, the terminal device 10 may be not only a smart device but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

The information providing device 100 creates a scatter diagram based on the degree of relevance (relationship) between brands for each brand such as a store or a product, based on various historical information (log data) regarding the behavior of the user U with respect to the brand. It is an information processing device that is realized by a server device, a cloud system, or the like. In the present embodiment, the information providing device 100 creates a scatter plot based on a plurality of different relationships between a new brand (candidate brand) and an existing brand.

That is, the degree of relevance of the existing brand to the new brand is obtained based on the behavior of the user U with respect to each brand such as a store or a product. For example, if a new brand store and an existing brand store to be opened in another location already exist, the user U can open both the new brand store and the existing brand store to be opened in another location. If there is a history of visits, or if the information providing device 100 has a history of purchasing both a new brand product and an existing brand product, or if the user U has a new brand store or product. If there is a history of searching or posting for both stores or products of the existing brand, the relevance of the existing brand to the new brand is calculated based on the frequency of appearance (degree) and the frequency of duplication of those histories. .. The same applies to the degree of relevance between existing brands. However, the above items are only examples.

Here, the brand is, for example, a brand of a store (shop) such as a tenant on a floor of a commercial facility or the like, a brand of a product (item) on a product shelf (display shelf) such as a retail store, or the like. Various historical information regarding the behavior of the user U with respect to the brand reflects the brand's name recognition / recognition and ability to attract customers.

In addition, commercial facilities are just one example of facilities where stores can be set up. In reality, large commercial facilities (department stores / shopping centers / outlet malls / underground streets), large leisure facilities (theme parks / amusement parks / amusement parks / zoos / aquariums / pools / bath facilities / parks / gardens / famous places), cultural facilities It may be (hall / theater / movie theater / museum / museum), railway station or airport, port (boarding area), service area (SA), parking area (PA), or the like. A store is just one example of a sales floor. For example, the store is not limited to indoors, but may be outdoors. That is, the store may be an outdoor site of a certain size. Further, the store may be a temporary sales office such as a stall or a tent.

Further, the retail store is, for example, a supermarket, a convenience store, a mass retailer, a drug store, a discount store, a home center, a warehouse type store, or the like. In addition, the product shelf is only an example of store fixtures in which a plurality of products can be arranged. For example, product shelves also include freezing and refrigerating showcases. Further, the product shelf may be, for example, a stand (display stand, sales stand), a wagon, a stall, a cart, or the like, which is arranged at a specific position in the store and on which recommended products, special sale products, etc. are placed. In addition, the product may be hung on a hook or a hanger rack. Further, the product may be placed on the floor, placed on a wall surface or ceiling, or suspended from the ceiling. Further, the product shelf is not limited to the real one, but may be a virtual one. Further, the product shelf may be a screen (screen for ranking the best-selling products, etc.) for displaying a list of a plurality of products on an online mall (electronic shopping street), an EC site (Electronic Commerce site), or the like. Further, the product shelf may be a catalog for catalog sales.

In addition, commodities are just one example of a transaction target. In this embodiment, the goods may be read as services. For example, the product may be an application for various services, various contracts, financial products, materials related to travel products, a booklet (pamphlet), or the like.

The store device 200 is information used by a business operator who manages a new brand scheduled to open a store or a new release, or a business operator who manages and operates a facility having a floor or a store where a product shelf is installed. It is a processing device, which is an information processing device that receives information from the information providing device 100, and is realized by a server device, a cloud system, or the like. Alternatively, it may be a portable terminal device similar to the terminal device 10. For example, the store device 200 is based on a scatter plot that visualizes the relevance of the existing brand to the new brand of the store on the floor from the information providing device 100 via the network N (see FIG. 4), and / or the scatter plot. Receive information (analysis results, survey reports, etc.). Alternatively, the store device 200 visualizes the degree of relevance of the existing brand to the new brand on the product shelf from the information providing device 100 via the network N (see FIG. 4), and / or information based on the scatter diagram. Receive an offer.

[1-1. basic action〕
In the present embodiment, as shown in FIGS. 1, 2 and 3, the information providing device 100 is directly or indirectly (via various servers or the like) from the terminal device 10 of the user U to the store or the like. Acquire various history information (log data) indicating the behavior of the user U regarding the product or the like (step S1). For example, the information providing device 100 acquires a position history, which is a history of the position and date and time of the user U regarding movement in the store, product purchase, etc., from the terminal device 10. Further, the information providing device 100 acquires a search history, which is a history of search queries input by the user U regarding a store, a product, or the like, from a search server (search engine). Further, the information providing device 100 acquires a browsing history, which is a history of contents browsed by the user U regarding a store, a product, or the like, from the content server. Further, the information providing device 100 acquires the purchase history, which is the purchase history of the user U, from the electronic commerce server or the electronic payment server. Further, the information providing device 100 acquires the posting history, which is the posting history of the user U regarding the store, the product, etc., from the posting server or the SNS (Social Networking Service) server that provides the word-of-mouth posting service. The information providing device 100 can acquire various types of information in addition to the above-mentioned information. For example, the information providing device 100 acquires information on the attributes of the user U such as the age, gender, family structure, and economic status of the user U. Then, the information providing device 100 may use the above-mentioned various information as a context of the user U.

Then, the information providing device 100 creates a scatter diagram that visualizes the degree of relevance between the brands for each brand such as a store or a product based on various historical information of the user U (step S2). Here, the information providing device 100 creates a scatter plot based on a plurality of different relationships between a new brand (candidate brand) and an existing brand. For example, the information providing device 100 selects a new brand as a candidate for a store of each brand existing on a floor of a commercial facility or the like, and visualizes the degree of relevance of the existing brand to the new brand of the store on the floor. To create. Alternatively, the information providing device 100 selects a new brand for the products of each brand placed on the product shelf (display shelf), and visualizes the degree of relevance of the existing brand to the new brand of the product on the product shelf. create.

The information providing device 100 is used by a business operator who manages a new brand scheduled to open a store or a new release, or a business operator who manages and operates a facility having a floor or a store where a product shelf is installed. Information on a scatter diagram that visualizes the degree of relevance of the existing brand to the new brand is provided to the store appliance 200 to be used (step S3). For example, the information providing device 100 visualizes the degree of relevance of the existing brand to the new brand of the store on the floor via the network N (see FIG. 4), and / or information based on the scatter plot (analysis result). , Survey report, etc.) is provided to the store appliance 200. Alternatively, the information providing device 100 provides a scatter diagram that visualizes the relevance of the existing brand to the new brand on the product shelf via the network N (see FIG. 4) and / or information based on the scatter diagram to the store device 200. offer.

As a result, the business operator that manages the new brand that is scheduled to open or launch a new brand will be able to visualize the relevance of the existing brand to the new brand and / or based on the information based on the scatter plot. It is possible to carry out a simulation of opening a store or launching a new store. For example, it is possible to consider and implement changes in the store opening plan of a new brand and determination of the launch time. In addition, the business operator who manages and operates the facility where the floor is located or the store where the product shelves are installed is based on the scatter plot that visualizes the relevance of the existing brand to the new brand and / or the information based on the scatter plot. Therefore, it is possible to study and optimize the layout of new brands and existing brands.

[1-2. Method using existing store data]
Here, with reference to FIG. 1, a case where a proposal for attracting a store and a brand grasp are carried out by a method using existing store data will be described. FIG. 1 shows an example of a scatter plot relating to the degree of relevance to an existing store (the degree of relevance of an existing store to a new store). In this scatter plot, the vertical axis shows multiple relationships with existing stores (compatibility with existing store groups). The horizontal axis shows the average degree of relevance with existing stores (compatibility with specific stores). The dots on the drawing indicate individual brands.

The information providing device 100 generates a scatter plot that visualizes the degree of relevance of, for example, a clothing or cosmetics brand among existing stores. At this time, the information providing device 100 extracts all the brands having a certain degree of relevance or more from all the target stores, and maps them by the number of appearances and the degree of characteristics. In the scatter plot shown in FIG. 1, the higher the vertical axis, the better the compatibility with the existing store group (all stores), and the more right the horizontal axis, the stronger the compatibility with the specific store (some stores).

In the example shown in FIG. 1, the area in the upper center (slightly right) that is compatible with existing stores and has strong compatibility with specific stores is shown as a "recommendation zone" (recommended area), and is particularly compatible among the recommendation zones. Areas narrowed down to those with strong are shown as "high recommendation zones".

For example, by referring to the scatter plot shown in Fig. 1 and selecting the brand / store to be newly added from the upper center (slightly right) when reviewing the existing brand, the affinity is high. Moreover, it is speculated that the sharp atmosphere can be maintained.

[1-3. User location information and payment information]
Next, with reference to FIG. 2, a case where a proposal for attracting a store and a brand grasp are carried out based on the user's location information and payment information will be described. FIG. 2 shows an example of a scatter plot relating to compatibility with the user. In this scatter plot, the vertical axis shows compatibility with users (visiting users) who visit the area around the store (peripheral area). The horizontal axis shows compatibility with store users (electronic payment users). The dots on the drawing indicate individual brands. The users (visiting users) who visit the area around the store may or may not include the users (residents) who live in the area around the store.

The information providing device 100 generates a scatter diagram that visualizes, for example, the degree of relevance to a brand of clothing or cosmetics from the degree of compatibility with the location information and payment information of the user U. Here, the information providing device 100 identifies the user U who visited the area around the store on holidays at least twice a month based on the location information of the user U. Further, the information providing device 100 identifies the user U who has used the electronic payment at the store in the area based on the payment information of the user U.

Further, the information providing device 100 extracts all brands having a certain degree of relevance or more from all the target stores, and maps them by the number of appearances and the degree of characteristics. In the scatter plot shown in FIG. 2, the higher the vertical axis, the better the compatibility with the users (visiting users) who visit the area around the store, and the more right the horizontal axis, the better the store users (electronic payment users). The compatibility is strong.

In the example shown in FIG. 2, the area in the upper center (slightly right) that is compatible with users (visiting users) who visit the area around the store and is strongly compatible with store users (electronic payment users) is ". It is shown as a "recommendation zone", and the area narrowed down to those with particularly strong compatibility among the recommendation zones is shown as a "high recommendation zone".

In this way, not only the data of existing stores, but also various data based on various historical information such as people flow data and attribute information of specific areas, usage data such as electronic payment, users who are interested in brands, etc. are crossed. It is also possible to extract brands that are compatible with each other.

[1-4. Multiplication of various data]
Next, with reference to FIG. 3, a case where a proposal for attracting a store and a brand grasp are carried out by multiplying the various data described above will be described. FIG. 3 shows an example of a three-dimensional scatter plot (3D scatter plot) relating to compatibility with existing stores and users. In the Cartesian coordinate system of the three-dimensional space shown by this three-dimensional scatter diagram, the X-axis shows compatibility with a user who visits the area around the store. The Y-axis indicates compatibility with store users (electronic payment users). The Z axis indicates compatibility with existing stores. The dots on the drawing indicate individual brands. The X-axis, Y-axis, and Z-axis are for convenience only and may be replaced as appropriate. At this time, it is considered that the accuracy increases as the number of dimensions (or variables) increases.

[1-5. Information provision]
The information providing device 100 proposes a store / product layout according to the relationship between existing and / or new brands.

(1) Layout change of existing shop The information providing device 100 selects one or a plurality of existing brands that are open on the floor of a department store or the like, and the floor in the same facility as the selected brand (on the same floor). Not limited to other floors), the compatibility with existing brands is specified, and a scatter plot according to the specified compatibility is provided. The business operator who received the scatter plot can change the layout or the like based on the scatter plot.

(2) Examination of layout optimization of existing shop The information providing device 100 specifies all the relationships between brands arranged on the floor in the same facility for existing brands opened on the floor of a department store or the like. Further, the information providing device 100 specifies an arrangement position (empty arrangement position) in which each brand is arranged on the floor. That is, regardless of the placement of the existing brand, all the store-installable areas (sections) on the floor are specified. Then, the information providing device 100 optimizes the placement position of each brand in the floor based on a predetermined rule. For example, arrange so that the same users are close to each other. Alternatively, the brand that appears in the history information of many users is placed in a larger placement position.

At this time, the information providing device 100 may combine the arrangement position and the person flow data. Optimize the placement position based on the data of how people are flowing. For example, place brands that are highly relevant in women's history information on routes where many women are walking.

Further, the information providing device 100 may optimize the placement position based on the relationship between the brands and the attribute of the user who is the target as a complex facility. Further, the information providing device 100 may determine the optimum layout based on how a person with a certain attribute is moving. Further, the information providing device 100 may use the information of the electronic payment method, or may see the relevance in the payment history or the like.

At this time, in the information providing device 100, the facility may be set for each floor, and the user attribute may be set for each facility. That is, optimization is performed for each floor based on the attributes of users for each department store. Further, the information providing device 100 may optimize the layout of the products arranged on the product shelves by regarding the facility as a product shelf and the store as a product. Further, the information providing device 100 may consider the visibility of the product on the product shelf.

Further, the information providing device 100 may realize these by letting the model learn the past history information. For example, the information providing device 100 learns a model so as to output information indicating sales when a layout (distance) and a relationship based on a search query are input. This makes it possible to judge that it is not good to place certain brands close to each other.

(3) Store opening simulation of a newly added shop When the brand is a new brand to be opened, the information providing device 100 can perform a store opening simulation by the above processing. For example, the information providing device 100 identifies all the relationships between the new brand scheduled to open on the floor of a department store or the like and the existing brand existing on the floor in the same facility. In addition, the information providing device 100 specifies an arrangement position (candidate position for opening a store) in which each brand is arranged on the floor. This makes it possible to identify the compatibility between the new brand and neighboring brands. Then, the information providing device 100 provides a scatter plot according to the specified compatibility. The business operator who received the scatter plot can change the layout or the like based on the scatter plot.

[2. Information processing system configuration example]
Next, the configuration of the information processing system 1 including the information providing device 100 according to the embodiment will be described with reference to FIG. FIG. 4 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 4, the information processing system 1 according to the embodiment includes a terminal device 10 and an information providing device 100. These various devices are connected so as to be communicable by wire or wirelessly via the network N. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Further, the number of each device included in the information processing system 1 shown in FIG. 4 is not limited to that shown in the figure. For example, in FIG. 4, for simplification of the illustration, only one terminal device 10 is shown, but this is merely an example and is not limited, and may be two or more.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 is a smart device such as a smartphone or tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a car navigation system, a wearable device such as a smart watch or a head-mounted display (Wearable Device). , Smart glasses, etc.

Further, the terminal device 10 includes a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: 5th generation mobile communication system), Bluetooth (registered trademark), and wireless LAN (Local). It can be connected to the network N via short-range wireless communication such as Area Network) and communicate with the information providing device 100.

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, or the like. The information providing device 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be described with reference to FIG. FIG. 5 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. 5, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40. Be prepared.

(Communication unit 11)
The communication unit 11 is connected to the network N (see FIG. 4) by wire or wirelessly, and transmits / receives information to / from the information providing device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, or the like.

(Display unit 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic EL display (Organic Electro-Luminescent Display). Further, the display unit 12 is a touch panel type display, but the display unit 12 is not limited thereto.

(Input unit 13)
The input unit 13 is an input device that receives various operations from the user U. Further, the input unit 13 has, for example, a button for inputting characters, numbers, and the like. When the display unit 12 is a touch panel type display, a part of the display unit 12 functions as an input unit 13. The input unit 13 may be a microphone or the like that receives voice input from the user U. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives a signal (radio wave) transmitted from a GPS (Global Positioning System) satellite, and based on the received signal, position information (for example, latitude) indicating the current position of the terminal device 10 which is its own device. And longitude). That is, the positioning unit 14 positions the terminal device 10. GPS is only an example of GNSS (Global Navigation Satellite System).

In addition, the positioning unit 14 can position the position by various methods other than GPS. For example, the positioning unit 14 may position the position by using various communication functions of the terminal device 10 as an auxiliary positioning means for position correction or the like as described below.

(Wi-Fi positioning)
For example, the positioning unit 14 positions the position of the terminal device 10 by using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 determines the position of the terminal device 10 by performing Wi-Fi communication or the like and measuring the distance to a nearby base station or access point.

(Beacon positioning)
Further, the positioning unit 14 may position the position by using the Bluetooth (registered trademark) function of the terminal device 10. For example, the positioning unit 14 positions the terminal device 10 by connecting to a beacon transmitter connected by the Bluetooth (registered trademark) function.

(Geomagnetic positioning)
Further, the positioning unit 14 positions the position of the terminal device 10 based on the geomagnetic pattern of the structure measured in advance and the geomagnetic sensor included in the terminal device 10.

(RFID positioning)
Further, for example, when the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used in a station ticket gate, a store, or the like, or has a function of reading an RFID tag. In this case, the used position is recorded together with the information that the payment or the like was made by the terminal device 10. The positioning unit 14 may position the position of the terminal device 10 by acquiring such information. Further, the position may be determined by an optical sensor included in the terminal device 10, an infrared sensor, or the like.

The positioning unit 14 may position the position of the terminal device 10 by using one or a combination of the above-mentioned positioning means, if necessary.

(Sensor unit 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. The connection may be a wired connection or a wireless connection. For example, the sensors may be a detection device other than the terminal device 10, such as a wearable device or a wireless device. In the example shown in FIG. 5, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, a pressure sensor 23, a temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( It is equipped with a camera) 28.

It should be noted that the above-mentioned sensors 21 to 28 are merely examples and are not limited thereto. That is, the sensor unit 20 may be configured to include a part of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or in place of the sensors 21 to 28. ..

The acceleration sensor 21 is, for example, a 3-axis acceleration sensor, and detects the physical movement of the terminal device 10 such as the moving direction, the speed, and the acceleration of the terminal device 10. The gyro sensor 22 detects the physical movement of the terminal device 10 such as the inclination in the triaxial direction based on the angular velocity of the terminal device 10 and the like. The barometric pressure sensor 23 detects, for example, the barometric pressure around the terminal device 10.

Since the terminal device 10 includes the above-mentioned acceleration sensor 21, gyro sensor 22, pressure sensor 23, etc., technologies such as pedestrian autonomous navigation (PDR) using each of these sensors 21 to 23, etc. It becomes possible to determine the position of the terminal device 10 by using. This makes it possible to acquire indoor position information, which is difficult to acquire with a positioning system such as GPS.

For example, a pedometer using an acceleration sensor 21 can calculate the number of steps, the walking speed, and the walking distance. Further, the gyro sensor 22 can be used to know the traveling direction of the user U, the direction of the line of sight, and the inclination of the body. Further, from the atmospheric pressure detected by the atmospheric pressure sensor 23, it is possible to know the altitude at which the terminal device 10 of the user U exists and the number of floors of the floor.

The air temperature sensor 24 detects, for example, the air temperature around the terminal device 10. The sound sensor 25 detects, for example, the sound around the terminal device 10. The optical sensor 26 detects the illuminance around the terminal device 10. The magnetic sensor 27 detects, for example, the geomagnetism around the terminal device 10. The image sensor 28 captures an image of the surroundings of the terminal device 10.

The barometric pressure sensor 23, the temperature sensor 24, the sound sensor 25, the optical sensor 26, and the image sensor 28, respectively, detect the barometric pressure, the temperature, the sound, and the illuminance, and capture an image of the surroundings, so that the terminal device 10 It is possible to detect the surrounding environment and situation of. Further, it is possible to improve the accuracy of the position information of the terminal device 10 from the surrounding environment and the situation of the terminal device 10.

(Control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input / output port, and various circuits. Further, the control unit 30 may be configured by hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 30 includes a transmission unit 31, a reception unit 32, and a processing unit 33.

(Transmitting unit 31)
The transmission unit 31 is positioned by, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and the positioning unit 14. The position information and the like of the terminal device 10 can be transmitted to the information providing device 100 via the communication unit 11.

(Receiver 32)
The receiving unit 32 can receive various information provided by the information providing device 100 and a request for sensor information from the information providing device 100 via the communication unit 11.

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10 including the display unit 12 and the like. For example, the processing unit 33 can output various information transmitted by the transmitting unit 31 and various information received by the receiving unit 32 from the information providing device 100 to the display unit 12 for display.

(Memory unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk. To. Various programs, various data, and the like are stored in the storage unit 40.

[4. Configuration example of information processing device]
Next, the configuration of the information providing device 100 according to the embodiment will be described with reference to FIG. FIG. 6 is a diagram showing a configuration example of the information providing device 100 according to the embodiment. As shown in FIG. 6, the information providing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Further, the communication unit 110 is connected to the network N (see FIG. 4) by wire or wirelessly.

(Memory unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As shown in FIG. 6, the storage unit 120 has a user information database 121, a history information database 122, a relevance information database 123, and a compatibility information database 124.

(User information database 121)
The user information database 121 stores various information about the user U. For example, the user information database 121 stores various information such as the attributes of the user U. FIG. 7 is a diagram showing an example of the user information database 121. In the example shown in FIG. 7, the user information database 121 has items such as "user ID (Identifier)", "age", "gender", "home", "work location", and "interest".

The "user ID" indicates identification information for identifying the user U. Further, "age" indicates the age of the user U identified by the user ID. The "age" may be a specific age of the user U identified by the user ID, for example, 35 years old. Further, "gender" indicates the gender of the user U identified by the user ID.

Further, "home" indicates the location information of the home of the user U identified by the user ID. In the example shown in FIG. 7, "home" is illustrated with an abstract reference numeral such as "LC11", but may be latitude / longitude information or the like. Further, for example, "home" may be a region name or an address.

Further, the "work location" indicates the location information of the work location (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 7, the “work location” is illustrated with an abstract code such as “LC12”, but may be latitude / longitude information or the like. Further, for example, the "work location" may be a region name or an address.

Further, "interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object of which the user U identified by the user ID is highly interested. For example, "interest" may be a search query (keyword) or the like that the user U inputs into a search engine and searches. In the example shown in FIG. 7, "interest" is shown one for each user U, but may be plural.

For example, in the example shown in FIG. 7, the age of the user U identified by the user ID "U1" is "20's", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that the home is "LC11". Further, for example, the user U identified by the user ID "U1" indicates that the work location is "LC12". Further, for example, the user U identified by the user ID "U1" indicates that he / she is interested in "sports".

Here, in the example shown in FIG. 7, abstract values such as “U1”, “LC11”, and “LC12” are used for illustration, but “U1”, “LC11”, and “LC12” are specific. Information such as character strings and numerical values shall be stored. Hereinafter, abstract values may be illustrated also in figures relating to other information.

The user information database 121 is not limited to the above, and various information may be stored depending on the purpose. For example, the user information database 121 may store various information about the terminal device 10 of the user U. In addition, the user information database 121 includes demographics (demographic attributes), psychographics (psychological attributes), geographics (geographical attributes), behavioral attributes (behavioral attributes), etc. of the user U. Information about the attribute may be stored. For example, the user information database 121 includes name, family structure, place of origin (local), occupation, position, income, qualification, living style (detached house, apartment, etc.), presence / absence of a car, commuting time, commuting to school / commuting. Memorize information such as routes, commuter pass sections (stations, routes, etc.), frequently used stations (other than the nearest station to your home / work location), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. You may.

(History information database 122)
The history information database 122 stores various information related to log data indicating the behavior of the user U. FIG. 8 is a diagram showing an example of the history information database 122. In the example shown in FIG. 8, the history information database 122 has items such as "user ID", "location history", "search history", "browsing history", "purchasing history", and "posting history".

The "user ID" indicates identification information for identifying the user U. Further, the "position history" indicates a position history which is a history of the position of the user U. Further, the "search history" indicates a search history that is a history of search queries entered by the user U. Further, the "browsing history" indicates the browsing history, which is the history of the content browsed by the user U. Further, the "purchase history" indicates a purchase history which is a purchase history by the user U. Further, the "posting history" indicates a posting history which is a posting history by the user U.

For example, in the example shown in FIG. 8, the user U identified by the user ID "U1" moves according to "location history # 1", searches according to "search history # 1", and "views". It indicates that the content is browsed according to "History # 1", a predetermined product or the like is purchased at a predetermined store or the like according to "Purchase history # 1", and the content is posted according to "Posting history".

Here, in the example shown in FIG. 8, abstractions such as "U1", "position history # 1", "search history # 1", "browsing history # 1", "purchasing history # 1", and "posting history # 1" are used. Although it is illustrated using a specific value, "U1", "position history # 1", "search history # 1", "browsing history # 1", "purchasing history # 1", and "posting history # 1" , Specific information such as character strings and numerical values shall be stored.

The history information database 122 is not limited to the above, and various information may be stored depending on the purpose. For example, the history information database 122 may store information related to a visit history and an entrance / exit history, which is a history of a user U visiting (visiting / visiting) a store, facility, or the like.

(Relevance information database 123)
The relevance information database 123 stores various information regarding the relevance of each brand to the existing brand. FIG. 9 is a diagram showing an example of the relevance information database 123. In the example shown in FIG. 9, the relevance information database 123 has items such as “target brand ID”, “existing brand ID”, and “relevance”.

The "target brand ID" indicates identification information for identifying a brand (target brand) to be analyzed or investigated. The target brand may be a new brand or an existing brand. In addition, the "existing brand ID" exists in the same place as the target brand (facilities and stores in the same area, floors in the same facility, product shelves in the same store, etc.), and the degree of relevance to the target brand is calculated. Shows identification information for identifying existing brands. The “relevance” indicates the relevance of the existing brand to the target brand.

For example, in the example shown in FIG. 9, the degree of relevance between the target brand identified by the target brand ID “target brand # 1” and the existing brand identified by the existing brand ID “existing brand # 11” is “relevance degree #”. 11 ”.

The relevance information database 123 is not limited to the above, and various information may be stored depending on the purpose. For example, the relevance information database 123 may store information regarding facility IDs and store IDs. In addition, the relevance information database 123 may store information on the brand name recognition / recognition and the ability to attract customers. Further, the relevance information database 123 may store information about an area or place where a facility, a store, or the like is located. That is, information on regional characteristics may be stored regarding the relationship between brands. Further, the relevance information database 123 may store information on the time and season when the relevance between brands is obtained. That is, information on fashion may be stored regarding the relationship between brands.

(Compatibility information database 124)
The compatibility information database 124 stores various information regarding compatibility between the brand and the user. FIG. 10 is a diagram showing an example of the compatibility information database 124. In the example shown in FIG. 10, the compatibility information database 124 has items such as "target brand ID", "compatibility with local visitors", and "compatibility with store users".

The "target brand ID" indicates identification information for identifying a brand (target brand) to be analyzed or investigated. The target brand may be a new brand or an existing brand. In addition, "compatibility with local visitors" indicates compatibility with users (visiting users) who visit the area around the store (surrounding area). In addition, "compatibility with store users" indicates compatibility with store users (electronic payment users).

For example, in the example shown in FIG. 10, the target brand identified by the target brand ID “target brand # 1” has “compatibility # A1” compatibility with local visitors and “compatibility” with store users. It indicates that it is "# B1".

The compatibility information database 124 is not limited to the above, and various information may be stored depending on the purpose. For example, the compatibility information database 124 may store information indicating compatibility with users having further different attributes and characteristics. In addition, the compatibility information database 124 may store detailed information about the area.

(Control unit 130)
Returning to FIG. 6, the explanation will be continued. The control unit 130 is a controller, and is an information providing device 100 by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like. It is realized by executing various programs (corresponding to an example of an information processing program) stored in the internal storage device of the ASIC with a storage area such as a RAM as a work area. In the example shown in FIG. 6, the control unit 130 includes an acquisition unit 131, a calculation unit 132, a generation unit 133, and a provision unit 134.

(Acquisition unit 131)
The acquisition unit 131 acquires various historical information regarding the user U's behavior with respect to the brand directly or indirectly (via various servers and the like) from the terminal device 10 of the user U via the communication unit 110. do. Various historical information regarding the behavior of the user U with respect to the brand reflects the brand's name recognition / recognition and ability to attract customers. The acquisition unit 131 stores various acquired history information in the history information database 122 of the storage unit 120.

Further, the acquisition unit 131 acquires the registration information (user information) input by the user U from the terminal device 10 of the user U via the communication unit 110. The acquisition unit 131 stores the acquired user information in the user information database 121 of the storage unit 120.

(Calculation unit 132)
The calculation unit 132 calculates the degree of relevance between brands based on various history information acquired by the acquisition unit 131 and stored in the storage unit 120. That is, the calculation unit 132 reads various history information stored in the history information database 122 of the storage unit 120, and calculates the degree of relevance between the brands based on the read history information.

Further, the calculation unit 132 calculates the compatibility between the brand and the user based on the history information. For example, the calculation unit 132 calculates the compatibility with a user who visits a predetermined area where the brand exists. In addition, the calculation unit 132 calculates the compatibility with the user of the electronic payment. However, the above compatibility is only an example.

Further, the calculation unit 132 acquires user information acquired by the acquisition unit 131 and stored in the user information database 121 of the storage unit 120 when calculating the degree of relevance between brands or the compatibility between brands and users. May be read and used. Then, the calculation unit 132 stores the calculated information based on the relevance between the brands in the relevance information database 123 of the storage unit 120. Further, the calculation unit 132 stores the calculated information based on the compatibility between the brand and the user in the compatibility information database 124 of the storage unit 120.

For example, the calculation unit 132 calculates the degree of relevance between existing brands. In addition, the calculation unit 132 calculates the degree of relevance of the existing brand to the new brand. At this time, the calculation unit 132 calculates the degree of relevance of the existing brand to the selected target brand among the plurality of brands existing in the same place.

When a plurality of brands are stores, the place where the plurality of brands exist is a floor in the same facility (not limited to the same floor but may be another floor). When a plurality of brands are products, the place where the plurality of brands exist is a product shelf in the same store (not only the same product shelf but also other product shelves).

In addition, even if it does not actually exist in the same place, a new brand that is planned to be placed in the same place (source, exhibition) and may exist in the same place in the future is also a brand that exists in the same place. deal. This is because when calculating the degree of relevance between brands, it is assumed that the new brand exists in the same place.

(Generation unit 133)
The generation unit 133 generates a scatter plot that visualizes the degree of relevance between brands. For example, the generation unit 133 generates a scatter plot in which the vertical axis is a plurality of relations with the existing brand and the horizontal axis is the average degree of relations with the existing brand. Alternatively, the generation unit 133 generates a scatter plot in which the vertical axis is compatibility with a user who has visited a predetermined area where the brand exists, and the horizontal axis is compatibility with a user of electronic payment. In addition, the generation unit 133 may generate a three-dimensional scatter plot that visualizes the degree of relevance between brands.

(Providing section 134)
The providing unit 134 provides information based on the degree of relevance between brands to the business operator related to the brand. For example, the provision unit 134 provides information on a new layout of a brand based on the degree of relevance between the brands to a business operator who manages the placement of the brand in the place where the brand exists.

The business operator that manages the arrangement of brands is, for example, a business operator that manages the layout of a store installed on the floor of a facility, a business operator that manages the layout of products arranged on the product shelves of a store, and the like. In addition to the above-mentioned businesses, the provision unit 134 may provide information to businesses (shops, manufacturers, etc.) that manage the brand as businesses related to the brand.

[5. Processing procedure]
Next, the processing procedure by the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 11 is a flowchart showing a processing procedure according to the embodiment. The processing procedure shown below is repeatedly executed by the control unit 130 of the information providing device 100.

For example, as shown in FIG. 11, the acquisition unit 131 of the information providing device 100 directly or indirectly (via various servers or the like) from the terminal device 10 of the user U via the communication unit 110. Acquire various historical information regarding the behavior of the user U with respect to the brand (step S101). At this time, the acquisition unit 131 stores various acquired history information in the history information database 122 of the storage unit 120.

Subsequently, the calculation unit 132 of the information providing device 100 reads various history information acquired by the acquisition unit 131 and stored in the storage unit 120, and based on the read history information, determines the degree of relevance between the brands. Calculate (step S102).

Subsequently, the generation unit 133 of the information providing device 100 generates a scatter diagram that visualizes the degree of relevance between the brands (step S103). For example, the generation unit 133 generates a scatter plot in which the vertical axis is a plurality of relations with the existing brand and the horizontal axis is the average degree of relations with the existing brand. Alternatively, the generation unit 133 generates a scatter plot in which the vertical axis is compatibility with a user who has visited a predetermined area where the brand exists, and the horizontal axis is compatibility with a user of electronic payment. In addition, the generation unit 133 may generate a three-dimensional scatter plot that visualizes the degree of relevance between brands.

Subsequently, the providing unit 134 of the information providing device 100 provides information based on the degree of relevance between the brands to the business operator related to the brand (step S104). For example, the provision unit 134 provides information on a new layout of a brand based on the degree of relevance between the brands to a business operator who manages the placement of the brand in the place where the brand exists.

[6. Modification example]
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above-described embodiment. Therefore, a modified example of the embodiment will be described below.

In the above embodiment, the information providing device 100 generates a scatter diagram that visualizes the relevance of the existing brand to the new brand of the product in the same product shelf, but is not limited to the same product shelf in reality. You may generate a scatter diagram that visualizes the relevance of an existing brand to a new brand of goods on different shelves. That is, the information providing device 100 may generate a scatter diagram that visualizes the degree of relevance of the product placed on another product shelf different from the product shelf on which the new brand is placed with the existing brand.

Further, in the above embodiment, the information providing device 100 generates a scatter plot that visualizes the degree of relevance of the existing brand to the new brand of the store on the floor in the same facility, but in reality, the floor in the same facility. Not limited to this, a scatter plot that visualizes the degree of relevance of an existing brand to a new brand of a store between different facilities in the same area (area) may be generated. That is, the information providing device 100 may generate a scatter diagram that visualizes the degree of relevance of the new brand to the existing brand existing in another facility different from the new store opening or existing facility.

Further, in the above embodiment, the information providing device 100 may compare the degree of relevance of the existing brand to the new brand of the product on the product shelf in which the same product is arranged among a plurality of stores. For example, the information providing device 100 relates the existing brand to the new brand of the specific product on the product shelf in the first store and the relationship of the existing brand to the new brand of the specific product on the product shelf in the second store. Compare with degree. In reality, the degree of relevance may be compared between three or more stores. This makes it possible to investigate and analyze differences in the degree of relevance and changes between brands due to differences in the arrangement of the same products and brands on the product shelves of each store.

[7. effect〕
As described above, the information providing device 100 according to the present application includes an acquisition unit 131, a calculation unit 132, and a generation unit 133. The acquisition unit 131 acquires history information regarding the behavior of the user U with respect to the brand. The calculation unit 132 calculates the degree of relevance between brands based on the history information. The generation unit 133 generates a scatter plot that visualizes the degree of relevance between brands. For example, the generation unit 133 generates a scatter plot in which the vertical axis is a plurality of relations with the existing brand and the horizontal axis is the average degree of relations with the existing brand. Alternatively, the generation unit 133 generates a scatter plot in which the vertical axis is compatibility with a user who has visited a predetermined area where the brand exists, and the horizontal axis is compatibility with a user of electronic payment. In addition, the generation unit 133 may generate a three-dimensional scatter plot that visualizes the degree of relevance between brands.

This makes it possible to propose what kind of brand is good as a new brand according to the relationship between the existing brand and the brand to be attracted. For example, it is possible to propose a layout change for an existing shop. You can also consider optimizing the layout of existing shops and propose the results of that study. In addition, it is possible to propose a store opening simulation for a new store.

[8. Hardware configuration]
Further, the terminal device 10 and the information providing device 100 according to the above-described embodiment are realized by, for example, a computer 1000 having a configuration as shown in FIG. Hereinafter, the information providing device 100 will be described as an example. FIG. 12 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to the output device 1010 and the input device 1020, and the arithmetic unit 1030, the primary storage device 1040, the secondary storage device 1050, the output I / F (Interface) 1060, the input I / F 1070, and the network I / F 1080 are bused. It has a form connected by 1090.

The arithmetic unit 1030 operates based on a program stored in the primary storage device 1040 or the secondary storage device 1050, a program read from the input device 1020, or the like, and executes various processes. The arithmetic unit 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the arithmetic unit 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and is a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid). State Drive), flash memory, etc. The secondary storage device 1050 may be an internal storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), NAS (Network Attached Storage), a file server, or the like.

The output I / F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various information such as a display, a projector, and a printer. For example, USB (Universal Serial Bus) or DVI. (Digital Visual Interface), HDMI (Registered Trademark) (High Definition Multimedia Interface), etc. Further, the input I / F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, a keyboard, a keypad, a button, a scanner, and the like, and is realized by, for example, USB.

Further, the output I / F 1060 and the input I / F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

Further, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated as input / output I / F.

The input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

The network I / F 1080 receives data from another device via the network N and sends it to the arithmetic unit 1030, and also transmits the data generated by the arithmetic unit 1030 to the other device via the network N.

The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output I / F 1060 and the input I / F 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the information providing device 100, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 130 by executing the program loaded on the primary storage device 1040. Further, the arithmetic unit 1030 of the computer 1000 may load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. Further, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I / F 1080 to call the functions and data of the program from other programs of the other devices and use them.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Further, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, that is, those in a so-called equal range. Furthermore, the components described above can be combined as appropriate. Further, various omissions, replacements or changes of the components can be made without departing from the gist of the above-described embodiment.

Further, among the processes described in the above-described embodiment, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or part of it can be done automatically by a known method. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown in the figure.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, the above-mentioned information providing device 100 may be realized by a plurality of server computers, or may be realized by calling an external platform or the like by API (Application Programming Interface), network computing, or the like depending on the function. Can be changed flexibly.

Further, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not contradict each other.

Further, the above-mentioned "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.

1 Information processing system 10 Terminal device 100 Information provider 110 Communication unit 120 Storage unit 121 User information database 122 History information database 123 Relevance information database 124 Compatibility information database 130 Control unit 131 Acquisition unit 132 Calculation unit 133 Generation unit 134 Providing unit 200 store equipment

Claims (14)

An acquisition department that acquires historical information about user behavior with respect to the brand,
A calculation unit that calculates the degree of relevance between brands based on the history information,
A generation unit that generates a scatter plot that visualizes the degree of relevance between brands,
An information processing device characterized by being equipped with. The information processing apparatus according to claim 1, wherein the generation unit generates a scatter plot in which the vertical axis is a plurality of relations with an existing brand and the horizontal axis is an average degree of relations with an existing brand. The calculation unit calculates the compatibility between the brand and the user based on the history information.
The claim is characterized in that the generation unit generates a scatter plot in which the vertical axis is compatibility with a user who visits a predetermined area where a brand exists, and the horizontal axis is compatibility with a user of electronic payment. The information processing apparatus according to 1 or 2. The information processing apparatus according to any one of claims 1 to 3, wherein the generation unit generates a three-dimensional scatter plot that visualizes the degree of relevance between the brands. The calculation unit calculates the degree of relevance between existing brands and
The information processing apparatus according to any one of claims 1 to 4, wherein the generation unit generates a scatter diagram that visualizes the degree of relevance between the existing brands. The calculation unit calculates the degree of relevance of the existing brand to the new brand.
The information processing apparatus according to any one of claims 1 to 5, wherein the generation unit generates a scatter diagram that visualizes the degree of relevance of the existing brand to the new brand. The calculation unit calculates the degree of relevance of an existing brand to the target brand among a plurality of brands.
The information processing apparatus according to any one of claims 1 to 6, wherein the generation unit generates a scatter diagram that visualizes the degree of relevance of an existing brand to the target brand. The calculation unit calculates the degree of relevance of an existing brand to a target brand among a plurality of brands existing in the same place.
The information processing apparatus according to any one of claims 1 to 7, wherein the generation unit generates a scatter diagram that visualizes the degree of relevance of an existing brand to the target brand. The plurality of brands are stores and
The information processing apparatus according to claim 8, wherein the place where the plurality of brands exist is a floor in the same facility. The plurality of brands are products and
The information processing device according to claim 8, wherein the place where the plurality of brands exist is a product shelf in the same store. A provider that provides information based on the degree of relevance between brands to businesses related to the brand, and
The information processing apparatus according to any one of claims 1 to 10, further comprising. 11. The provision unit is characterized in that it provides information on a new layout of the brand based on the degree of relevance between the brands to a business operator who manages the arrangement of the brand in the place where the brand exists. The information processing device described in. It is an information processing method executed by an information processing device.
The acquisition process to acquire history information about user behavior with respect to the brand,
A calculation process that calculates the degree of relevance between brands based on the history information,
A generation process that generates a scatter plot that visualizes the degree of relevance between brands,
An information processing method characterized by including. Acquisition procedure to acquire history information about user behavior with respect to the brand,
A calculation procedure for calculating the degree of relevance between brands based on the history information, and
A generation procedure for generating a scatter plot that visualizes the degree of relevance between brands, and
Information processing program to make a computer execute.

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