JP7565740B2 - Purchasing situation analysis support device and purchasing situation analysis support program - Google Patents

Description

The present invention relates to a purchasing situation analysis support device and a purchasing situation analysis support program.

Conventionally, the following technologies have been available to contribute to the analysis of purchasing behavior in commercial areas, tourist destinations, urban areas, and other areas where purchasing behavior for various goods and services occurs.

Patent Document 1 discloses a method for analyzing marketing information. This analysis method includes a step of defining regional units by dividing an area based on lifestyle indicators, a step of generating a living area by grouping regional units with similar lifestyle indicators for a plurality of regional units, and an analysis step of analyzing marketing information based on the living area.

Patent Document 2 also discloses a marketing device equipped with a customer information collection means for collecting sales information from customer POS data and creating customer aggregate data that links the collected sales information of the customer with the customer's personal information. This marketing device is equipped with a segmentation analysis means for clustering the customers into segments based on their lifestyles by non-hierarchical clustering and hierarchical clustering based on the customer aggregate data.

JP 2002-140490 A JP 2014-048780 A

Incidentally, when analyzing purchasing patterns, it is extremely important to understand the emotional tendencies of shoppers, such as whether their feelings about the area in which they are shopping are positive or negative, and the tendencies of their behavioral patterns when purchasing the product.

However, the technologies disclosed in Patent Documents 1 and 2 do not take into account the emotions and behavioral patterns of people who make purchases, and have the problem that they are unable to analyze the characteristics of at least one of the emotions and behavioral patterns of people when making purchases.

The present invention has been made in consideration of the above circumstances, and aims to provide a purchasing situation analysis support device and a purchasing situation analysis support program that can analyze at least one characteristic of a person's emotions and behavioral patterns when engaging in purchasing activities.

The purchasing situation analysis support device of the present invention described in claim 1 comprises an acquisition unit that acquires purchasing information including at least one of purchase items and purchase prices by a plurality of people in a space to be analyzed, acquires at least one of emotion information indicating an emotional state and behavior pattern information indicating a behavior pattern, and acquires attribute information indicating attributes of each of the plurality of people; a classification unit that uses each information acquired by the acquisition unit to classify the purchasing information for each attribute indicated by the attribute information and classifies at least one of the emotion information and the behavior pattern information; and an association unit that uses the classification results by the classification unit to associate the classification results of the purchasing information and the classification results of at least one of the emotion information and the behavior pattern information for each common attribute, and the association unit further associates the probability that a person matching a corresponding attribute matches a tendency represented by the classification results of the purchasing information for each associated attribute and the classification results of at least one of the emotion information and the behavior pattern information, with the corresponding attribute .

According to the purchasing situation analysis support device of the present invention described in claim 1, purchasing information including at least one of the purchase items and the purchase price by multiple people in the space to be analyzed is obtained, and at least one of emotion information indicating the emotional state and behavior pattern information indicating the behavior pattern is obtained, and attribute information indicating the attributes of each of the multiple people is obtained, and using each of the obtained information, the purchasing information is classified for each attribute indicated by the attribute information, and at least one of the emotion information and the behavior pattern information is classified, and the classification results are used to associate the classification results of the purchasing information with the classification results of at least one of the emotion information and the behavior pattern information for each common attribute, thereby analyzing at least one characteristic of a person's emotion and behavior pattern when engaging in purchasing activities.

The purchasing status analysis support device according to the present invention described in claim 2 is the purchasing status analysis support device described in claim 1, further comprising a presentation unit that presents information indicating the result of the association by the association unit.

According to the purchasing situation analysis support device of the present invention described in claim 2, by presenting information showing the results of associating the classification results of purchasing information for each common attribute with the classification results of at least one of emotion information and behavior pattern information, it is possible to more effectively analyze at least one of the characteristics of a person's emotions and behavior patterns when engaging in purchasing activities.

The purchasing status analysis support device according to the present invention described in claim 3 is the purchasing status analysis support device described in claim 2, in which the presentation unit synthesizes information indicating the result of the association with a map image and presents it.

According to the purchasing situation analysis support device of the present invention described in claim 3, by synthesizing and presenting information showing the results of the association with a map image, it is possible to more effectively analyze at least one of the characteristics of a person's emotions and behavioral patterns when engaging in purchasing activities.

The purchasing status analysis support device according to the present invention described in claim 4 is the purchasing status analysis support device described in claim 3, in which the map image is a social heat map image.

According to the purchasing situation analysis support device of the present invention described in claim 4, by making the map image a social heat map image, it is possible to more effectively analyze at least one of the characteristics of people's emotions and behavioral patterns when engaging in purchasing activities.

The purchasing status analysis support device according to the present invention described in claim 5 is a purchasing status analysis support device described in any one of claims 1 to 4, in which the attributes include at least one of gender, age, and place of residence.

According to the purchasing situation analysis support device of the present invention described in claim 5, by including at least one of the attributes of gender, age, and place of residence as attributes, it is possible to analyze at least one characteristic of emotions and behavioral patterns when a person is engaged in purchasing activities for each included attribute.

The purchasing status analysis support device according to the present invention described in claim 6 is a purchasing status analysis support device described in any one of claims 1 to 5, in which the person corresponding to the purchasing information and the person corresponding to at least one of the emotion information and the behavior pattern information are different people.

According to the purchasing status analysis support device of the present invention described in claim 6, a general-purpose analysis can be performed by defining the plurality of people as different people corresponding to the purchasing information and the person corresponding to at least one of the emotional information and the behavioral pattern information.
The purchasing situation analysis support device of the present invention as described in claim 7 is the purchasing situation analysis support device as described in claim 1, wherein the emotional information is at least one of three types of information: positive, which indicates an optimistic emotion, negative, which indicates a pessimistic emotion, and information indicating neither emotion.
The purchasing status analysis support device of the present invention as described in claim 8 is the purchasing status analysis support device as described in claim 1, wherein the acquisition unit collects information posted on SNS that can be used to infer the emotions felt by people who visited the corresponding space to be analyzed, and derives the emotional information by analyzing the collected information.
The purchasing status analysis support device of the present invention described in claim 9 is a purchasing status analysis support device described in claim 1, wherein the space to be analyzed is an area including a location where a user terminal, which is a terminal possessed by a target person to use the device, is located.

A purchasing status analysis support program according to the present invention as described in claim 10 is a process for acquiring purchasing information including at least one of purchase items and purchase prices by a plurality of people in a space to be analyzed, acquiring at least one of emotion information indicating an emotional state and behavior pattern information indicating a behavior pattern, and acquiring attribute information indicating attributes of each of the plurality of people, using each acquired information to classify the purchasing information for each attribute indicated by the attribute information, and classifying at least one of the emotion information and the behavior pattern information, and using the classification results to associate the classification results of the purchasing information with the classification results of at least one of the emotion information and the behavior pattern information for each common attribute, and causes a computer to execute a process for further associating, with the corresponding attribute, a probability that a person matching the corresponding attribute matches a tendency represented by the classification results of the purchasing information for each associated attribute and the classification results of at least one of the emotion information and the behavior pattern information.

According to the purchasing status analysis support program of the present invention as described in claim 10 , purchasing information including at least one of the purchase items and purchase price by a plurality of people in the space to be analyzed is obtained, and at least one of emotion information indicating an emotional state and behavior pattern information indicating a behavior pattern is obtained, and attribute information indicating the attributes of each of the plurality of people is obtained, and using each of the obtained information, the purchasing information is classified for each attribute indicated by the attribute information, and at least one of the emotion information and the behavior pattern information is classified, and the classification results are used to associate the classification results of the purchasing information with the classification results of at least one of the emotion information and the behavior pattern information for each common attribute, thereby making it possible to analyze at least one of the characteristics of a person's emotions and behavior patterns when engaging in purchasing activities.

As described above, the present invention makes it possible to analyze at least one characteristic of a person's emotions and behavioral patterns when engaging in purchasing activities.

1 is a block diagram showing an example of a hardware configuration of a purchasing status analysis support system according to an embodiment. 1 is a block diagram showing an example of a functional configuration of a purchasing status analysis support system according to an embodiment. FIG. 2 is a schematic diagram showing an example of a configuration of a target area information database according to the embodiment. FIG. 2 is a schematic diagram illustrating an example of a configuration of a purchase information database according to the embodiment. FIG. 2 is a schematic diagram showing an example of a configuration of an emotion information database according to the embodiment. FIG. 2 is a schematic diagram showing an example of a configuration of a behavior pattern information database according to the embodiment. FIG. 2 is a schematic diagram illustrating an example of a configuration of an associated information database according to the embodiment. 11 is a flowchart illustrating an example of a purchasing status analysis support process according to the embodiment. 11 is a flowchart illustrating an example of associated information presentation processing according to the embodiment. 11 is a flowchart illustrating an example of an associated information display process according to the embodiment. FIG. 4 is a front view showing an example of a configuration of an initial screen according to the embodiment. FIG. 13 is a front view showing an example of a configuration of an association result screen according to the embodiment.

Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. In this embodiment, the present invention will be described as being applied to a purchasing status analysis support system that includes a purchasing status analysis support device configured with a server computer or the like, and multiple target user terminals that are terminals used individually by each target user.

First, the configuration of the purchasing status analysis support system 90 according to this embodiment will be described with reference to Figures 1 and 2. Figure 1 is a block diagram showing an example of the hardware configuration of the purchasing status analysis support system 90 according to this embodiment. Also, Figure 2 is a block diagram showing an example of the functional configuration of the purchasing status analysis support system 90 according to this embodiment.

As shown in FIG. 1, the purchasing status analysis support system 90 according to this embodiment includes a purchasing status analysis support device 10 and multiple target user terminals 30, each of which is capable of accessing a network 80. Examples of the purchasing status analysis support device 10 include information processing devices such as personal computers and server computers. Examples of the target user terminals 30 include portable terminals such as smartphones, tablet terminals, and PDAs (Personal Digital Assistants, mobile information terminals).

The subject terminal 30 according to this embodiment is a terminal owned by each of a plurality of subjects who are to use the purchasing status analysis support system 90. The subject terminal 30 includes a CPU (Central Processing Unit) 31, a memory 32 as a temporary storage area, a non-volatile storage unit 33, an input unit 34 such as a touch panel, a display unit 35 such as a liquid crystal display, and a media read/write device (R/W) 36. The subject terminal 30 also includes a camera 38, a microphone 39, a GPS (Global Positioning Systems) 40, and a wireless communication unit 42. The CPU 31, the memory 32, the storage unit 33, the input unit 34, the display unit 35, the media read/write device 36, the camera 38, the microphone 39, the GPS 40, and the wireless communication unit 42 are connected to each other via a bus B1. The media read/write device 36 reads information written in the recording medium 37 and writes information to the recording medium 37.

The storage unit 33 is realized by a hard disk drive (HDD), a solid state drive (SSD), a flash memory, etc. The storage unit 33, which serves as a storage medium, stores the associated information display program 33A. The associated information display program 33A is stored in the storage unit 33 when a recording medium 37 to which the associated information display program 33A has been written is set in the medium reading and writing device 36, and the medium reading and writing device 36 reads the associated information display program 33A from the recording medium 37. The CPU 31 reads the associated information display program 33A from the storage unit 33, expands it in the memory 32, and sequentially executes the processes of the associated information display program 33A.

Meanwhile, the purchasing status analysis support device 10 is a device that collectively stores and manages various information handled by the purchasing status analysis support system 90. The purchasing status analysis support device 10 comprises a CPU 11, a memory 12 as a temporary storage area, a non-volatile storage unit 13, an input unit 14 such as a keyboard and mouse, a display unit 15 such as a liquid crystal display, a media reading and writing device 16, and a communication interface (I/F) unit 18. The CPU 11, memory 12, storage unit 13, input unit 14, display unit 15, media reading and writing device 16, and communication interface (I/F) unit 18 are connected to each other via bus B2. The media reading and writing device 16 reads information written to the recording medium 17 and writes information to the recording medium 17.

The storage unit 13 is realized by a HDD, SSD, flash memory, etc. The storage unit 13 as a storage medium stores a purchasing status analysis support program 13A and an associated information presentation program 13B. The purchasing status analysis support program 13A is stored in the storage unit 13 by setting the recording medium 17 on which the purchasing status analysis support program 13A is written in the medium reading and writing device 16, and the medium reading and writing device 16 reading the purchasing status analysis support program 13A from the recording medium 17. The associated information presentation program 13B is stored in the storage unit 13 by setting the recording medium 17 on which the associated information presentation program 13B is written in the medium reading and writing device 16, and the medium reading and writing device 16 reading the associated information presentation program 13B from the recording medium 17. The CPU 11 reads the purchasing status analysis support program 13A and the associated information presentation program 13B from the storage unit 13, loads them into the memory 12, and sequentially executes the processes that the purchasing status analysis support program 13A and the associated information presentation program 13B each have.

The storage unit 13 also stores a target area information database 13C, a purchase information database 13D, an emotion information database 13E, a behavior pattern information database 13F, and an associated information database 13G. The target area information database 13C, the purchase information database 13D, the emotion information database 13E, the behavior pattern information database 13F, and the associated information database 13G will be described in detail below.

Next, referring to FIG. 2, the functional configuration of the purchasing status analysis support device 10 and the target user terminal 30 according to this embodiment will be described.

As shown in FIG. 2, the purchasing situation analysis support device 10 includes an acquisition unit 11A, a classification unit 11B, an association unit 11C, and a presentation unit 11D. The CPU 11 of the purchasing situation analysis support device 10 executes the purchasing situation analysis support program 13A and the associated information presentation program 13B, thereby functioning as the acquisition unit 11A, the classification unit 11B, the association unit 11C, and the presentation unit 11D.

The acquisition unit 11A according to the present embodiment acquires purchase information including at least one of the purchase object and the purchase price by a plurality of people in the space to be analyzed (hereinafter referred to as the "analysis target space"). The acquisition unit 11A also acquires at least one of emotion information indicating the emotional state and behavior pattern information indicating the behavior pattern by a plurality of people in the analysis target space, and acquires attribute information indicating the attributes of each of the plurality of people. In the present embodiment, the purchase information includes both the purchase object and the purchase price, but this is not limited thereto. The purchase information may include only one of the purchase object and the purchase price. In addition, the purchase information may include other purchase-related information such as information indicating the store where the purchase was made, information indicating the genre of the purchase object, and information indicating whether the purchase was made by electronic payment or cash. In the present embodiment, the acquisition unit 11A acquires both emotion information and behavior pattern information, but this is not limited thereto. The acquisition unit 11A may acquire only one of the emotion information and the behavior pattern information.

In this embodiment, the attributes include all of gender, age, and place of residence, but are not limited to this. The attributes may include only one or a combination of two of gender, age, and place of residence. The attributes may also include information about other relevant persons, such as occupation, position, and hobbies. In this embodiment, the plurality of people are different from the person corresponding to the purchase information and the person corresponding to both the emotion information and the behavior pattern information, but are not limited to this. The plurality of people may be different from the person corresponding to the purchase information and the person corresponding to either the emotion information or the behavior pattern information. Conversely, the person corresponding to the purchase information and the person corresponding to at least one of the emotion information and the behavior pattern information may be the same person.

The classification unit 11B according to this embodiment uses each piece of information acquired by the acquisition unit 11A to classify the purchasing information for each attribute indicated by the attribute information, and also classifies at least one of the emotion information and the behavioral pattern information (in this embodiment, both).

The associating unit 11C according to this embodiment uses the classification results by the classifying unit 11B to associate the classification results of the purchasing information with at least one of the classification results of the emotion information and the behavior pattern information for each common attribute. In this embodiment, the classifying unit 11B associates the classification results of the purchasing information with the classification results of both the emotion information and the behavior pattern information, but this is not limited to this. The classifying unit 11B may also associate the classification results of the purchasing information with the classification results of either the emotion information or the behavior pattern information.

The presentation unit 11D according to this embodiment then presents information indicating the result of the association by the association unit 11C (hereinafter also referred to as "associated information"). The presentation unit 11D according to this embodiment presents the associated information by transmitting information about the associated information to the requested target user terminal 30 and displaying it on the display unit 35 of the target user terminal 30, but this is not limited to the present embodiment. For example, the associated information may be presented by displaying it on the display unit 15 of the purchasing status analysis support device 10. Furthermore, the presentation of the associated information by the presentation unit 11D is not limited to displaying it on the display unit, and may be presented by voice or by printing it on an image forming device (a so-called printer).

On the other hand, the presentation unit 11D according to this embodiment presents the associated information by synthesizing it with a map image. In particular, in this embodiment, a social heat map image is applied as the map image. The social heat map image is an image showing a map in which areas with different densities or colors are displayed on the map image that is normally displayed in the corresponding area, emphasizing locations where there is a lot of information that matches the target's category. That is, in this embodiment, each target is asked to answer a number of questions in advance, and the answer results are analyzed and classified to determine the category of each target in advance. Then, the social heat map image according to this embodiment is displayed on the map image so that the density increases in locations where there is a lot of information (in this embodiment, information posted on SNS (Social Networking Service)) that matches the target's category to be used. However, this is not limited to a form of changing the density, and the color may be changed in order from high density to low density, such as red → yellow → green.

In this embodiment, the purchasing status analysis support device 10 is connected via a network 80 or the like to a server that provides the latest social heat map images for each of the areas (hereinafter referred to as "target areas") that are the subject of the purchasing status analysis support system 90. The purchasing status analysis support device 10 then obtains the latest social heat map images from this server and sequentially updates the social heat map images stored in the target area information database 13C (see also FIG. 3) described below. However, this is not the only possible form, and the purchasing status analysis support device 10 itself may sequentially update the social heat map images corresponding to each target person.

On the other hand, the subject terminal 30 according to this embodiment includes a receiving unit 31A and a display control unit 31B. The CPU 31 of the subject terminal 30 executes the associated information display program 33A, thereby functioning as the receiving unit 31A and the display control unit 31B.

The receiving unit 31A in this embodiment receives association information indicating the results of association by the associating unit 11C of the purchasing status analysis support device 10 from the purchasing status analysis support device 10. In addition, the display control unit 31B controls the display of information related to the association information received by the receiving unit 31A on the display unit 35.

Next, the target area information database 13C according to this embodiment will be described with reference to FIG. 3. FIG. 3 is a schematic diagram showing an example of the configuration of the target area information database 13C according to this embodiment.

The target area information database 13C according to this embodiment is a database in which information about the target area described above is registered. As shown in FIG. 3, the target area information database 13C according to this embodiment stores information on the target area name, social heat map image, target district name, and target district position.

The target area name is information indicating the name of each of the target areas, and the social heat map image is information indicating the above-mentioned social heat map image for each subject in the target area indicated by the corresponding target area name. The target district name is information indicating the name of a district that exists within the corresponding target area, and the target district position is information indicating the position where the corresponding target district exists.

In this embodiment, the target area is an area divided by chome in each town in the corresponding target area, and the area in the target area excluding chome corresponds to the above-mentioned analysis target space. In addition, in this embodiment, the target area position is defined as the coordinate position in a two-dimensional coordinate system of a pair of diagonal corners of the circumscribing rectangular frame of the corresponding target area. However, this is not limited to these forms, and for example, the target area may be an area divided by house number in each town in the corresponding target area, the target area position may be the coordinate position in the two-dimensional coordinate system of the center point of the circumscribing rectangular frame, or latitude and longitude may be applied instead of the coordinate position in the two-dimensional coordinate system.

Next, the purchasing information database 13D according to this embodiment will be described with reference to FIG. 4. FIG. 4 is a schematic diagram showing an example of the configuration of the purchasing information database 13D according to this embodiment.

The purchasing information database 13D according to this embodiment is a database in which the purchasing information described above is registered. As shown in FIG. 4, the purchasing information database 13D according to this embodiment stores information on the purchasing area, attributes, date and time, product name, and price.

The purchasing district is information indicating the district where the corresponding purchase object was purchased, and in this embodiment, the above-mentioned analysis target space is applied. The attribute is information indicating the above-mentioned attribute information, and the date and time is information indicating the date and time when the corresponding purchase object was purchased. The item name is information indicating the name of the purchase object, and the amount is information indicating the purchase price of the corresponding purchase object.

In this embodiment, the purchasing information is information obtained from an electronic payment system when the payment method for the purchase price when each purchaser purchases the purchase item is an electronic payment system with the consent of each purchaser, but this is not limited to this. For example, the purchasing information may be information obtained from a POS (Point Of Sale) system used in various stores in each target area.

The example shown in Figure 4 shows that an 18-year-old male living in Shinagawa Ward in Otemachi purchased a pair of shoes for 5,500 yen at 10:12 on October 10, 2020.

Next, the emotion information database 13E according to this embodiment will be described with reference to FIG. 5. FIG. 5 is a schematic diagram showing an example of the configuration of the emotion information database 13E according to this embodiment.

The emotion information database 13E according to this embodiment is a database in which the emotion information described above is registered. As shown in FIG. 5, the emotion information database 13E according to this embodiment stores information on the area to be analyzed, attributes, date and time, and emotions.

The above-mentioned analysis target area is information indicating the area to be analyzed for purchasing status, and in this embodiment, the above-mentioned analysis target space is applied. The above-mentioned attributes are the same information as the attributes in the purchasing information database 13D, and the above-mentioned date and time are information indicating the date and time when information from which the corresponding emotion can be inferred (hereinafter referred to as "emotion basic information") was posted. The above-mentioned emotion is information indicating an emotion inferred from the corresponding emotion basic information.

In this embodiment, as the basic emotion information, the purchasing status analysis support device 10 collects and applies information posted on SNS via the network 80 or the like that can be used to infer the emotions felt by people who visited the corresponding analysis target area. Then, in this embodiment, the collected basic emotion information is analyzed to derive information indicating the above-mentioned emotions.

In this manner, in this embodiment, basic emotion information is collected from SNS, but this is not limited to this. For example, information that allows for inferring emotions toward a particular analysis target area from subjects who have visited that area may be collected as basic emotion information.

In addition, in this embodiment, two types of information are applied as the information indicating the above emotion: positive, which indicates an optimistic emotion, and negative, which indicates a pessimistic emotion; however, this is not limited to this. For example, in addition to the two types of information, positive and negative, three types of information, which indicates a neutral emotion, may be applied as the information indicating the above emotion, and a combination of one or two types of information may be applied as the information indicating the above emotion. In addition, in this embodiment, a method using artificial intelligence is applied as a method for deriving information indicating emotion from basic emotion information; however, this is not limited to this, and for example, a conventionally known statistical method such as cluster analysis may be applied.

The example shown in Figure 5 shows that a 45-year-old man living in Shinagawa Ward in Otemachi was experiencing positive emotions at 9:18 on October 10, 2020.

Next, the behavior pattern information database 13F according to this embodiment will be described with reference to FIG. 6. FIG. 6 is a schematic diagram showing an example of the configuration of the behavior pattern information database 13F according to this embodiment.

The behavior pattern information database 13F according to this embodiment is a database in which the above-mentioned behavior pattern information is registered. As shown in FIG. 6, the behavior pattern information database 13F according to this embodiment stores information on the subject ID (Identification), attributes, date and time, and behavior patterns.

The subject ID is information that is assigned in advance to each subject and is different in order to individually identify the corresponding subject, and the attributes are the same information as the attributes in the purchase information database 13D. The date and time is information that indicates the start and end times of an action when the corresponding subject is performing an action of a corresponding action pattern, which will be described later, and the action pattern is information that indicates the action performed by the corresponding subject during the corresponding date and time.

In this embodiment, information indicating the movement route of the corresponding target person's location is used as information indicating the above-mentioned behavioral pattern, but this is not limited to this. For example, in addition to information indicating the movement route, information indicating the means of transportation, such as train, car, bicycle, walking, etc., may be applied as information indicating the above-mentioned behavioral pattern.

In addition, in this embodiment, the behavior pattern information is acquired by having the subject's terminal 30 carried by the subject identify its own location using the GPS 40, and then sequentially transmitting location information indicating the identified location, as well as the subject ID and information indicating attributes corresponding to the subject. However, this is not limited to the above, and for example, the behavior pattern information may be extracted from information posted on SNS and applied.

In the example shown in Figure 6, for example, the subject with the subject ID "U10001" is a 24-year-old man living in Shinagawa Ward, and it is shown that he traveled from Shinagawa to Otemachi and then from Otemachi to Shinagawa between 11:25 and 16:45 on October 10, 2020.

Next, the associated information database 13G according to this embodiment will be described with reference to FIG. 7. FIG. 7 is a schematic diagram showing an example of the configuration of the associated information database 13G according to this embodiment.

The associated information database 13G according to this embodiment registers the associated information described above, and is constructed by the purchasing status analysis support process described below. As shown in FIG. 7, the associated information database 13G according to this embodiment stores information on the area to be analyzed, attributes, trends, and probabilities, and the trends include information on amounts, emotions, and behavioral patterns.

The area to be analyzed is the same information as the area to be analyzed in emotion information database 13E. The attributes are the same information as the attributes in purchasing information database 13D, and the amount in the trend is the same information as the amount in purchasing information database 13D. The emotions are the same information as the emotions in emotion information database 13E, and the behavior patterns are the same information as the behavior patterns in behavior pattern information database 13F.

In this embodiment, the age in the attribute of the associated information database 13G is specified in 10-year increments, such as teens and twenties, but this is not limited to this. For example, the age may be specified in other increments, such as under 20 years old, 20 to 40 years old, or by the year of birth, such as born in Showa, born in Heisei, or born in Reiwa. In this embodiment, the amount in the trend of the associated information database 13G is specified in 1000 yen increments, such as in the 5000 yen range and the 6000 yen range, but this is not limited to this. For example, the amount may be specified in other increments, such as less than 500 yen, or 500 to less than 1000 yen.

The above probability is information indicating the probability that a person who matches the corresponding attribute will match the corresponding tendency in the corresponding analysis area. The example shown in Figure 7 indicates that, for example, in Otemachi, the probability that a teenage male living in Shinagawa Ward will purchase an item in the 5,000 yen range with positive emotions and visit only Otemachi is 28%.

Next, the operation of the purchasing status analysis support system 90 according to this embodiment will be described with reference to Figs. 8 to 12. Fig. 8 is a flowchart showing an example of a purchasing status analysis support process according to this embodiment. Fig. 9 is a flowchart showing an example of an associated information presentation process according to this embodiment. Fig. 10 is a flowchart showing an example of an associated information display process according to this embodiment. Fig. 11 is a front view showing an example of the configuration of an initial screen according to this embodiment. Furthermore, Fig. 12 is a front view showing an example of the configuration of an association result screen according to this embodiment.

First, referring to FIG. 8, the operation of the purchasing situation analysis support device 10 according to this embodiment when executing the purchasing situation analysis support process will be described. When a user of the purchasing situation analysis support device 10 (e.g., an administrator of the purchasing situation analysis support system 90) inputs an instruction to start execution of the purchasing situation analysis support process via the input unit 14, the CPU 11 of the purchasing situation analysis support device 10 executes the purchasing situation analysis support program 13A, thereby executing the purchasing situation analysis support process shown in FIG. 8. Note that, in order to avoid confusion, a case will be described here in which the target area information database 13C, purchasing information database 13D, emotion information database 13E, and behavior pattern information database 13F have already been constructed.

In step 100 of FIG. 8, the CPU 11 reads out attribute and amount information (hereinafter referred to as "purchase-related information") corresponding to one of the areas to be analyzed (hereinafter referred to as the "area to be processed") from the purchase information database 13D. Also in step 100, the CPU 11 reads out attribute and emotion information (hereinafter referred to as "emotion-related information") corresponding to the area to be processed from the emotion information database 13E. Furthermore, in step 100, the CPU 11 reads out attribute and behavior pattern information (hereinafter referred to as "behavior pattern-related information") included in the behavior pattern for the area to be processed from the behavior pattern information database 13F.

In step 102, the CPU 11 uses the read information to perform classification processing of the information as shown below.

First, the CPU 11 converts the age in each attribute of the read purchase-related information, emotion-related information, and behavior pattern-related information into age groups in 10-year increments, such as under 10 years old, teens, 20s, etc. The CPU 11 also converts the amount in the read purchase-related information into amount groups in 1000 yen increments, such as under 1000 yen, 1000 yen range, 2000 yen range, etc.

Next, the CPU 11 classifies each of the purchase-related information, emotion-related information, and behavioral pattern-related information that have been converted into age and amount strata into combinations that share common information included in the attributes and common amounts, emotions, and behavioral patterns. Through this classification, each piece of information is classified into groups (hereinafter referred to as "common groups") of people who share common information on gender, age group (in this embodiment, 10-year age groups), place of residence, amount strata (in this embodiment, 1000 yen strata), emotions, and behavioral patterns (hereinafter referred to as "information groups").

Then, the CPU 11 next calculates the probability for each common group using the following formula (1). Note that in formula (1), Pi represents the probability of the i-th common group, CNi represents the number of information groups belonging to the i-th common group, and TN represents the total number of information groups.

Pi=CNi/TN×100 (1)

In step 104, the CPU 11 associates the processing target area with the information on gender, age group, place of residence, amount group, emotion, behavior pattern, and probability of each common group obtained by the processing in step 102, and stores the information in the associated information database 13G.

In step 106, the CPU 11 determines whether the above processing has been completed for all analysis target districts. If the determination is negative, the process returns to step 100, whereas if the determination is positive, the process ends. Note that when the processing from step 100 to step 106 is repeatedly executed, in step 100, the analysis target districts that have not been processed up to that point become the processing target districts.

The above purchasing status analysis support process will result in the construction of an associated information database 13G, as shown in Figure 7 as an example.

Next, referring to FIG. 9, the operation of the purchasing status analysis support device 10 according to this embodiment when executing the associated information presentation process will be described.

In the purchasing status analysis support system 90 according to this embodiment, when a subject wants to refer to the results of associating various pieces of information in a purchasing status analysis support process for a certain analysis target area, the subject uses the subject's own subject terminal 30 to execute the associated information display process described below. In this associated information display process, the subject transmits reference request information including information indicating the analysis target area for which the subject wants to refer to the above-mentioned association results (hereinafter referred to as "designated target area information") to the purchasing status analysis support device 10. When this reference request information is received, the CPU 11 of the purchasing status analysis support device 10 executes the associated information presentation program 13B, thereby executing the associated information presentation process shown in FIG. 9. Note that, in order to avoid confusion, a case will be described here in which the associated information database 13G has already been constructed.

In step 150 of FIG. 9, the CPU 11 extracts the designated target district information from the received reference request information. In step 152, the CPU 11 reads out the attribute, tendency, and probability information corresponding to the analysis target district (hereinafter referred to as the "processing target district") indicated by the designated target district information from the associated information database 13G.

In step 154, the CPU 11 reads out from the target area information database 13C the target area position corresponding to the processing target area and a social heat map image corresponding to the target area that includes the processing target area and corresponding to the target person who is the access source.

In step 156, the CPU 11 creates information (hereinafter referred to as "association result screen information") showing an association result screen with a predetermined configuration using the read social heat map image, the attribute, tendency, and probability information corresponding to the processing target area, and the target area location. In step 158, the CPU 11 transmits the created association result screen information to the target user terminal 30 that is the access source, and then ends this association information presentation process.

Next, referring to FIG. 10, the operation of the subject terminal 30 according to this embodiment when executing the associated information display process described above will be described. The associated information display process shown in FIG. 10 is executed by the CPU 31 of any of the subject terminals 30 executing the associated information display program 33A. The associated information display process shown in FIG. 10 is executed, for example, when an instruction to execute the associated information display process is input from any of the subjects (hereinafter referred to as the "subject") via the input unit 34 of his/her subject terminal 30.

In step 200 of FIG. 10, the CPU 31 controls the display unit 35 to display an initial screen having a predetermined configuration, and in step 202, the CPU 31 waits until the specified information is input.

11, the initial screen according to this embodiment displays a message prompting the user to input the name of the target area, and also displays an input area 35A for inputting the name of the area to be analyzed for which the results of the association of various information by the purchasing status analysis support process are to be viewed. When the initial screen shown in FIG. 11 is displayed on the display unit 35, the subject uses the input unit 34 to input the name of the area to be analyzed for which the results of the association are to be viewed in the input area 35A, and then selects the end button 35C. In response to this, step 202 is judged to be positive, and the process proceeds to step 204. Note that in this embodiment, the name of the area to be analyzed is input on the initial screen in a form in which the name of the area to be analyzed is directly input, but this is not limited thereto. The names of all areas to be analyzed for which the results of the association can be viewed may be displayed in a pull-down format, and the name of the desired area to be analyzed may be selected from the displayed names of the areas to be analyzed.

In step 204, the CPU 31 transmits the above-mentioned reference request information to the purchasing status analysis support device 10. In response to this, the purchasing status analysis support device 10 executes the association information presentation process as described above, and transmits the association result screen information to the target user terminal 30 that is the access source.

Therefore, in step 206, the CPU 31 waits until association result screen information is received from the purchasing status analysis support device 10. In step 208, the CPU 31 controls the display unit 35 to display the association result screen indicated by the received association result screen information, and in step 210, the CPU 31 waits until the specified information is input, and then ends this association information display process.

As an example, as shown in FIG. 12, the association result screen according to this embodiment displays analysis result information 35B indicating attributes, tendencies, and probabilities of people who purchased a purchase target in the analysis target area at a corresponding position on the social heat map image of the target area that includes the analysis target area. Note that this corresponding position is the position indicated by the target area position described above.

Therefore, by referring to the association results screen, the target person can understand the results of associating various information for the desired analysis area using the purchasing behavior analysis support process, along with the social heat map image.

As described above, according to this embodiment, the system includes an acquisition unit 11A that acquires purchasing information including at least one of the purchase items and the purchase price by a plurality of people in a space to be analyzed, acquires at least one of emotion information indicating an emotional state and behavior pattern information indicating a behavior pattern, and acquires attribute information indicating the attributes of each of the plurality of people, a classification unit 11B that classifies the purchasing information for each attribute indicated by the attribute information using each piece of information acquired by the acquisition unit 11A, and classifies at least one of the emotion information and the behavior pattern information, and an association unit 11C that associates the classification result of the purchasing information with the classification result of at least one of the emotion information and the behavior pattern information for each common attribute using the classification result by the classification unit 11B. Therefore, it is possible to analyze at least one characteristic of a person's emotion and behavior pattern when engaging in purchasing activities.

Furthermore, according to this embodiment, information is presented showing the results of associating the classification results of purchase information for each common attribute with the classification results of at least one of emotion information and behavior pattern information. Therefore, it is possible to more effectively analyze at least one of the characteristics of a person's emotions and behavior patterns when engaging in purchasing activities.

In addition, according to this embodiment, information showing the results of the association is synthesized and presented on a map image. This makes it possible to more effectively analyze at least one of the characteristics of a person's emotions and behavioral patterns when engaging in purchasing activities.

Furthermore, according to this embodiment, the map image is a social heat map image. Therefore, it is possible to more effectively analyze at least one of the characteristics of people's emotions and behavioral patterns when engaging in purchasing activities.

Furthermore, according to this embodiment, the attributes include at least one of gender, age, and place of residence. Therefore, it is possible to analyze at least one characteristic of emotions and behavioral patterns when a person is engaged in purchasing activities for each of the included attributes.

Furthermore, according to this embodiment, the plurality of people are different from the people corresponding to the purchasing information and the people corresponding to at least one of the emotion information and the behavior pattern information. Therefore, a general-purpose analysis can be performed.

In the above embodiment, the association result screen includes a social heat map image, but is not limited to this. For example, the association result screen may display only information indicating the results of the association made by the purchasing status analysis support process, without displaying a social heat map image.

In the above embodiment, the subject himself/herself specifies the area to be analyzed, but this is not limiting. For example, a GPS 40 built into the subject terminal 30 held by the subject may be used to automatically apply the area including the location of the subject terminal 30 as the area to be analyzed. In addition, information indicating the subject's preference trends may be acquired in advance by the purchasing status analysis support device 10, and information on the target area according to the subject's preferences may be provided to the subject at any time.

In the above embodiment, the purchasing situation analysis support process is executed in the purchasing situation analysis support device 10, but this is not limited to the above. For example, the purchasing situation analysis support process may be executed by each target person terminal 30. In this case, the purchasing situation analysis support device of the present invention is included in the target person terminal 30.

In the above embodiment, the analysis target area is input on the initial screen using the input unit 34, but this is not limited to the above. For example, the analysis target area may be input as voice information using the microphone 39.

In the above embodiment, a case has been described in which the analysis targets do not include the purchase target, but this is not limiting. For example, the analysis targets may include the purchase target (corresponding to the above-mentioned "item name") in addition to the purchase price. In this case, it is possible to grasp the tendency of purchase targets for each person's attributes, and as a result, it is possible to more effectively analyze at least one characteristic of a person's emotions and behavior patterns when engaging in purchasing activities.

In the above embodiment, a case has been described in which the date and time of purchase of the purchase target is not included in the analysis target, but this is not limiting. For example, the analysis target may include the date and time of purchase of the purchase target in addition to the purchase price. In this case, it is possible to grasp the trend of purchase dates and times for each person's attributes, and as a result, it is possible to more effectively analyze at least one characteristic of a person's emotions and behavior patterns when engaging in purchasing activities.

In the above embodiment, the classification unit 11B uses a relatively simple classification method in which all types of information that are common are grouped together. However, the present invention is not limited to this. For example, the classification unit 11B may use a conventionally known cluster analysis or a classification method using artificial intelligence.

It goes without saying that formula (1) is merely an example and can be modified as appropriate without departing from the spirit of the present invention.

In the above embodiment, for example, the hardware structure of the processing unit that executes each process of the acquisition unit 11A, classification unit 11B, association unit 11C, and presentation unit 11D can be the various processors shown below. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacture, such as an FPGA (Field-Programmable Gate Array), a dedicated electrical circuit, which is a processor with a circuit configuration designed specifically to execute a specific process, such as an ASIC (Application Specific Integrated Circuit), etc.

The processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (e.g., a combination of multiple FPGAs, or a combination of a CPU and an FPGA). The processing unit may also be configured with a single processor.

As an example of configuring the processing unit as a single processor, first, there is a form in which one processor is configured as a combination of one or more CPUs and software, as typified by computers such as client and server, and this processor functions as the processing unit. Secondly, there is a form in which a processor is used that realizes the functions of the entire system, including the processing unit, on a single IC (Integrated Circuit) chip, as typified by systems on chips (SoCs). In this way, the processing unit is configured as a hardware structure using one or more of the various processors mentioned above.

More specifically, the hardware structure of these various processors can be an electrical circuit that combines circuit elements such as semiconductor elements.

10 Purchase status analysis support device 11 CPU
Reference Signs List 11A Acquisition unit 11B Classification unit 11C Association unit 11D Presentation unit 12 Memory 13 Storage unit 13A Purchase status analysis support program 13B Association information presentation program 13C Target area information database 13D Purchase information database 13E Emotion information database 13F Action pattern information database 13G Association information database 14 Input unit 15 Display unit 16 Medium reading and writing device 17 Recording medium 18 Communication I/F unit 30 Target person terminal 31 CPU
31A Receiving unit 31B Display control unit 32 Memory 33 Storage unit 33A Association information display program 34 Input unit 35 Display unit 35B Analysis result information 36 Medium reading and writing device 37 Recording medium 38 Camera 39 Microphone 40 GPS
42 Wireless communication unit 80 Network 90 Purchasing situation analysis support system

Claims (10)

an acquisition unit that acquires purchase information including at least one of purchase items and purchase prices by a plurality of people in a space to be analyzed, acquires at least one of emotion information indicating an emotion state and behavior pattern information indicating a behavior pattern, and acquires attribute information indicating attributes of each of the plurality of people;
a classification unit that classifies the purchase information for each attribute indicated by the attribute information using each piece of information acquired by the acquisition unit, and classifies at least one of the emotion information and the behavior pattern information;
an association unit that associates, for each of the common attributes, a classification result of the purchase information with a classification result of at least one of the emotion information and the behavior pattern information, using a classification result by the classification unit;
Equipped with
the associating unit further associates, with the corresponding attribute, a probability that a person matching the corresponding attribute matches a tendency represented by a classification result of the purchasing information for each of the associated attributes and a classification result of at least one of the emotion information and the behavior pattern information;
Purchasing situation analysis support device. a presentation unit that presents information indicating a result of the association by the association unit;
The purchasing status analysis support device according to claim 1 , further comprising: The presentation unit presents information indicating a result of the association by combining the information with a map image.
3. The purchasing status analysis support device according to claim 2. The map image is a social heatmap image.
4. The purchasing status analysis support device according to claim 3. The attributes include at least one of gender, age, and place of residence.
The purchasing status analysis support device according to any one of claims 1 to 4. a person corresponding to the purchase information and a person corresponding to at least one of the emotion information and the behavior pattern information of the plurality of people are different from each other;
The purchasing status analysis support device according to any one of claims 1 to 5. The emotion information is at least one of three types of information: positive, which indicates an optimistic emotion; negative, which indicates a pessimistic emotion; and information indicating a neutral emotion.
2. The purchasing status analysis support device according to claim 1. The acquisition unit collects information posted on a social networking site that can be used to infer emotions felt by people who visited a corresponding space to be analyzed, and derives the emotion information by analyzing the collected information.
2. The purchasing status analysis support device according to claim 1. The space to be analyzed is an area including a location where a user terminal, which is a terminal owned by a subject to be used, is located.
2. The purchasing status analysis support device according to claim 1. Acquire purchase information including at least one of purchase items and purchase prices by a plurality of people in a space to be analyzed, acquire at least one of emotion information indicating an emotion state and behavior pattern information indicating a behavior pattern, and acquire attribute information indicating attributes of each of the plurality of people;
Using each piece of acquired information, the purchase information is classified for each attribute indicated by the attribute information, and at least one of the emotion information and the behavior pattern information is classified;
using a classification result, associating the classification result of the purchase information with at least one of the classification results of the emotion information and the behavior pattern information for each of the common attributes ;
further associating, with the corresponding attribute, a probability that a person who matches the corresponding attribute matches a tendency represented by the classification result of the purchasing information for each of the associated attributes and the classification result of at least one of the emotion information and the behavior pattern information;
A purchasing status analysis support program for causing a computer to execute processing.