Marketing information analysis device, method, and program

Abstract

To select a really promising customer from among a plurality of customers with a high probability.SOLUTION: A marketing server SV: collects purchase information of each user from a plurality of customer information databases DB1 to DBn; generates house keeping book information of each user, each income class, and each local area on the basis of the collected purchase information; selects income classes and local areas where consumption rates of notable commodities or services among commodity groups or service groups of identical spending items are the threshold value or more on the basis of the house keeping book information of each income class and the house keeping book information of each local area; and selects, as approaching target users, users whose consumption rates of the notable commodities or services among the commodity groups or service groups of the identical spending items are the threshold value or more from among user sets belonging to either one or both of the selected income class and the selected local area.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a marketing information analysis device, method, and program. [Background technology]

[0002] In recent years, various technologies have been proposed that use computer-based data mining processing to analyze customer information and obtain information useful for business activities. For example, Patent Document 1 describes a technology that sets multiple area clusters for the region to be analyzed, calculates the average profit per customer for each area cluster based on the resident attributes of customers living in that area, identifies high-profit area clusters, and selects promising customers from among customers living in areas that belong to those high-profit area clusters. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5444096 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technology described in Patent Document 1 selects customers solely by focusing on revenue from the customer, i.e., the customer's purchase amount, making it difficult to determine whether the customer is truly a promising customer. For example, if a mass retailer of sporting goods tries to select customers with a high interest in sports as promising customers, simply selecting a customer who spends a lot on sporting goods does not necessarily mean that this customer is highly interested in sports. This is because even if a customer spends a lot on sporting goods, they may only be buying them out of obligation for their children's classes or socializing, and it cannot be said that they are particularly interested in sports.

[0005] The present invention has been made in light of the above-mentioned circumstances, and aims to provide a marketing information analysis device, method, and program that can select truly promising customers from a large number of customers with a high probability. [Means for solving the problem]

[0006] In order to solve the above problem, a first aspect of the present invention is a marketing information analysis device or method comprising: means or a process for acquiring purchase information of a plurality of users from a purchase information management database that manages purchase information for a plurality of types of products or services for each of the plurality of users; means or a process for generating information representing a consumption breakdown of the plurality of types of products or services for each of the users based on the acquired purchase information; and means or a process for calculating, for each of the users based on the generated information representing the consumption breakdown, a consumption ratio between a first product or service of interest among the plurality of types of products or services and a second product or service other than the first product or service, and selecting users to be approached from the plurality of users based on the calculated consumption ratio.

[0007] In a second aspect of the present invention, when the purchasing information of one user is distributed and managed in multiple purchasing information management databases, a means for acquiring the purchasing information of the user accesses each of the multiple purchasing information management databases to acquire multiple pieces of purchasing information related to the user, and organizes the acquired multiple pieces of purchasing information by user and stores them in memory.

[0008] In a third aspect of the present invention, the means for generating information representing the consumption breakdown further comprises means for classifying the users into a plurality of income groups and generating information representing the consumption breakdown of goods or services purchased by the set of users classified into each income group, and the means for selecting the users comprises means for calculating, for each income group, the consumption ratio between the first product or service of interest and a second product or service other than the first product or service based on the information representing the consumption breakdown of the set of users, and selecting an income group to approach from among the plurality of income groups based on the calculated consumption ratio, and means for selecting users to approach from among a plurality of users belonging to the set of users classified into the selected income group based on the consumption ratio between the first product or service purchased by each user and a second product or service other than the first product or service.

[0009] In a fourth aspect of the present invention, the means for generating information representing the consumption breakdown further comprises means for classifying the users into a plurality of regional areas according to their location or place of purchase, and for generating information representing the consumption breakdown of products or services purchased by the set of users classified into each regional area, and the means for selecting the users comprises means for calculating, for each regional area, the consumption ratio between the first product or service of interest and a second product or service other than the first product or service based on the information representing the consumption breakdown of the set of users, and selecting a regional area to approach from among the plurality of regional areas based on the calculated consumption ratio, and means for selecting users to approach from among a plurality of users belonging to the set of users classified into the selected regional area based on the consumption ratio between the first product or service purchased by each user and a second product or service other than the first product or service.

[0010] In a fifth aspect of the present invention, the means for selecting the user includes household account book data in which expenditure items are divided into multiple categories, and generates information representing the breakdown of consumption by classifying the products or services purchased by the user or group of users and their purchase amounts into the corresponding categories of the household account book data based on the purchase information of the user or group of users acquired by the means, by user, income group or regional area.

[0011] In a sixth aspect of the present invention, the means for selecting the user calculates the consumption ratio between a first product or service of interest and another second product or service classified in the same category as the first product or service based on information representing a consumption breakdown generated using the household account book data, and selects users, income groups, or regional areas to be approached based on the calculated consumption ratio. [Effects of the Invention]

[0012] According to a first aspect of the present invention, for each user, a consumption ratio of a product or service is calculated from the purchase information, and users to be approached are selected based on this calculated consumption ratio. Generally, among multiple types of products or services, products or services with relatively high consumption ratios often reflect users' purchasing intentions. Therefore, by focusing on the consumption ratio, it is possible to select users who have a high purchasing intention for the product or service of interest as users to be approached.

[0013] According to a second aspect of the present invention, the purchase information of one user is acquired from multiple purchase information management databases and stored in association with each other. Therefore, even if the purchase information of products or services purchased by one user using a common point card or multiple credit cards or point cards is stored in multiple purchase information management databases, it is possible to collect a wide range of purchase information without omission, thereby making it possible to more accurately grasp the user's consumption breakdown.

[0014] According to a third aspect of the present invention, for each income group, the consumption ratio of a product or service by a set of users belonging to that income group is calculated, and based on the calculation result, an income group with a large number of users with a high consumption ratio of a product or service of interest is first selected from among multiple income groups. Then, from the group of users belonging to this selected income group, users with a high consumption ratio of the product or service of interest are selected as approach targets. Therefore, if there is a correlation between income and users who purchase a large amount of the product or service of interest, it is possible to efficiently narrow down users who are highly interested in purchasing the product or service of interest.

[0015] According to a fourth aspect of the present invention, for each regional area, the consumption ratio of a product or service by a group of users whose main activity area is that regional area is calculated, and based on this calculation result, a regional area with a high consumption ratio of the product or service of interest is first selected from among multiple regional areas. Then, users with a high consumption ratio of the product or service of interest are selected from the group of users belonging to this selected regional area. Therefore, when there is a correlation between users who purchase a lot of the product or service of interest and the activity area of ​​the users, it is possible to efficiently narrow down users who are highly interested in purchasing the product or service of interest.

[0016] According to a fifth aspect of the present invention, household account book data is used to classify products or services purchased by a user by type. A household account book is a tool that most clearly represents personal consumption. Therefore, by using household account book data as a template, information about products or services purchased by a user can be efficiently and accurately classified by item. Therefore, it is possible to generate information showing a breakdown of consumption without preparing a special classification application.

[0017] According to a sixth aspect of the present invention, the consumption ratio of a first product or service of interest is calculated as the consumption ratio relative to other products or services classified under the same expenditure category in the household account book data. For example, if the product or service of interest is classified under the expenditure category of culture and entertainment, the consumption ratio is calculated as the consumption ratio relative to other products or services classified under the same expenditure category of culture and entertainment. This makes it possible to accurately determine the characteristics of a user's purchase history for the product or service of interest, thereby enabling a high probability of selecting users who are strongly interested in purchasing the product or service of interest.

[0018] That is, according to each aspect of the present invention, it is possible to provide a marketing information analysis device, method, and program that can select truly promising customers from among a large number of customers with a high probability. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram showing the configuration of a system equipped with a marketing information analysis device according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of a marketing information analysis device according to an embodiment of the present invention. [Figure 3] FIG. 3 is a flowchart showing the procedure and processing contents of the marketing information analysis process performed by the marketing information analysis device shown in FIG. [Figure 4] FIG. 4 is a flowchart showing the steps and details of the user narrowing down process in the marketing information analysis process shown in FIG. [Figure 5] FIG. 5 is a flowchart showing the procedure and processing contents of the process for creating approach target information in the marketing information analysis process shown in FIG. [Figure 6] FIG. 6 is a diagram showing an example of a household account book used in the marketing information analysis process shown in FIG. [Figure 7]FIG. 7 is a diagram showing the relationship between the individual household ledger, the income bracket household ledger, and the area household ledger created by the marketing information analysis process shown in FIG. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. [One embodiment] (composition) FIG. 1 is a diagram showing the overall configuration of a system equipped with a marketing information analysis device according to an embodiment of the present invention, in which SV indicates a marketing server as a marketing information processing device.

[0021] The marketing server SV is capable of communicating with a plurality of customer information databases DB1 to DBn via a communication network NW. The customer information databases DB1 to DBn are managed by, for example, multiple card operating companies that use common point cards, or multiple affiliated operating companies of payment cards such as credit cards and point cards, and store multiple pieces of transaction information for individual member users or customer users across different industries. The transaction information includes personal information of the member users or customer users and product or service purchase information. The personal information includes, for example, contact information such as user name, age, gender, address, telephone number, and email address, as well as user attribute information such as annual income. The purchase information includes an identification code of the product or service purchased by the user, attribute information of the purchase store, purchase date and time, and purchase amount. The attribute information of the purchase store includes the store name, location, contact information, etc. Note that the personal information may be anonymized.

[0022] The marketing server SV is also capable of communicating with the service providing server GM via the communication network NW. The service providing server GM is operated by manufacturers, sellers, or service providers commissioned by them, and sends, for example, direct mail related to products or services to user terminals TM1 to TMm based on a customer list provided by the marketing server SV, or performs recommendation services. Recommendation services include paper direct mail delivered by home delivery or mail, e-mail, web advertisements, etc., as well as inserts and posted advertisements distributed to users' homes based on the customer list provided by the marketing server SV.

[0023] The user terminals TM1 to TMm may be portable terminals such as mobile phones, smartphones, and tablet terminals. Besides portable terminals, it is also possible to use stationary personal computers, television sets with network communication functions, and the like. The communication network NW is made up of an Internet Protocol (IP) network, such as the Internet, and an access network for accessing this IP network. The access network may be, for example, a wired telephone network, a mobile phone network, a local area network (LAN), a wireless LAN, or a CATV network.

[0024] The marketing server SV is configured as follows: Figure 2 is a block diagram showing its functional configuration. That is, the marketing server SV includes a control unit 10, a storage unit 20, and a communication interface unit 30.

[0025] The communication interface unit 30, under the control of the control unit 10, performs data communication between the customer information databases DB1 to DBn and the service providing server GM via the communication network NW. The communication protocol used is a protocol defined by the communication network NW. Specifically, the Transmission Control Protocol / Internet Protocol (TCP / IP), User Datagram Protocol / Internet Protocol (UDP / IP), etc. are used.

[0026] The storage unit 20 uses as its storage medium a nonvolatile memory that can be written to and read from at any time, such as a hard disk drive (HDD) or a solid state device (SSD), and a volatile memory that can be written to and read from at any time, such as a random access memory (RAM), and has the following storage areas necessary for implementing one embodiment of the present invention: a purchase information storage unit 21, a household account book storage unit 22, an analysis result storage unit 23, and an approach information storage unit 24. The storage unit 20 can also use a database provided on a cloud server or the like.

[0027] The purchase information storage unit 21 has a personal information storage area and a purchase information storage area. The personal information storage area and the purchase information storage area respectively store personal information and purchase information of each user collected from the customer information databases DB1 to DBn in association with user identification information (user ID).

[0028] The household account book storage unit 22 stores household account book information created by the household account book creation unit 12 (described later) for each user, income group, and regional area, in association with the user ID, income group identification information (income group ID), and regional area identification information (regional area ID), respectively.

[0029] The analysis result memory unit 23 stores the analysis results of the breakdown of consumption of purchased goods or services by user, income group, and regional area obtained by the analysis unit 13 described below, in association with the user ID, income group ID, and regional area ID.

[0030] The approach information storage unit 24 stores the user IDs of the approach targets selected by the approach target selection unit 14, which will be described later.

[0031] The control unit 10 has a processor and working memory, and is equipped with the following control functions necessary to implement one embodiment of the present invention: a purchase information acquisition control unit 11, a household account book creation unit 12, an analysis unit 13, an approach target selection unit 14, and a transmission control unit 15.

[0032] The above-mentioned purchase information acquisition control unit 11, household account book creation unit 12, analysis unit 13, approach target selection unit 14 and transmission control unit 15 are all realized by having the above-mentioned processor execute programs stored in the program memory in the storage unit 20.

[0033] The purchase information acquisition control unit 11 receives the personal information and purchase information of a plurality of users stored in each of the customer information databases DB1 to DBn via the communication interface unit 30. Then, the personal information and purchase information of each user received from the customer information databases DB1 to DBn is integrated by associating it with the user ID for each user, and the integrated information is stored in the purchase information storage unit 21.

[0034] The household account book creation unit 12 uses a household account book, which is a tool that most clearly shows personal consumption, to classify the user's purchase information by expenditure item, and has the following processing functions. (1) For each user, based on the purchase information stored in the purchase information storage unit 21, the products or services included in the purchase information and their purchase amounts are classified into multiple expenditure items defined in a pre-prepared household account book template. The classification results are then stored as household account book information for each user in the household account book storage unit 22 in association with the user ID.

[0035] (2) Classifying each user into income brackets by referring to the annual income included in the personal information of each user stored in the purchase information storage unit 21. Then, for each income bracket, the user-specific household ledger information of each user classified into that income bracket is integrated to create household ledger information by income bracket, and this household ledger information by income bracket is stored in the household ledger storage unit 22 in association with an income bracket ID.

[0036] (3) The area in which the user resides (for example, set by town name) is identified based on the user's address included in the personal information of each user stored in the purchase information storage unit 21, and each user is classified into one of the identified multiple area areas. Then, for each area, the user-specific household account book information of each user classified into the corresponding area is integrated to create household account book information for each area, and the household account book information for each area is stored in the household account book storage unit 22 in association with the area ID.

[0037] The analysis unit 13 has the following processing functions. (1) A process of calculating, for each expenditure item, the ratio of consumption of a product or service of interest to the product or service included in the item based on the user-specific household account information created by the household account creation unit 12 for each user.

[0038] (2) A process for calculating the ratio of consumption of a product or service of interest to the product or service included in each expenditure item based on the income-class household account information created by the household account creation unit 12 for each income group.

[0039] (3) A process for calculating, for each expenditure item, the ratio of consumption of a product or service of interest to the product or service included in the item based on the regional area-specific household account book information created by the household account book creation unit 12 for each regional area.

[0040] The approach target selection unit 14 has the following processing functions. (1) For each income group, a process of selecting an income group whose consumption ratio of the first product or service of interest calculated by the analysis unit 13 is equal to or greater than a predetermined threshold value (second threshold value) for determining income groups, and storing the income group ID of the selected income group in the approach information storage unit 24.

[0041] (2) For each regional area, a process is performed to select a regional area in which the consumption ratio of the first product or service of interest calculated by the analysis unit 13 is equal to or greater than a predetermined threshold value (third threshold value) for determining the regional area, and to store the regional area ID of the selected regional area in the approach information storage unit 24.

[0042] (3) A process of selecting, from a set of users belonging to either or both of the selected income group and regional area, users whose consumption ratio of the first product or service of interest calculated for each user by the analysis unit 13 is equal to or greater than a predetermined threshold value for user selection (first threshold value) as targets to be approached, and storing the user ID of the selected user in the approach information storage unit 24.

[0043] The transmission control unit 25 generates a list of users selected as approach targets (approach target information) based on the information stored in the approach information storage unit 24. Then, it performs processing to transmit this generated approach target information from the communication interface unit 30 to the service providing server GM.

[0044] (operation) Next, the operation of the marketing server SV configured as above will be described. FIG. 3 is a flowchart showing the overall processing procedure and processing contents by the marketing server SV.

[0045] (1) Collection of purchase information The customer information databases DB1 to DBn store personal information of registered users in advance. When a user purchases a desired product or service using a payment card such as a credit card or point card, the purchase information is stored in one of the customer information databases DB1 to DBn in association with the user ID.

[0046] First, in step S10, the marketing server SV accesses each of the customer information databases DB1 to DBn under the control of the purchase information acquisition control unit 11. The access destination information, i.e., URLs, for the customer information databases DB1 to DBn are stored in advance in the access destination memory in the storage unit 20.

[0047] By the access, the personal information and purchase information of the multiple users are downloaded from each of the customer information databases DB1 to DBn. ​​Under the control of the purchase information acquisition control unit 11, the marketing server SV associates the downloaded personal information and purchase information of the multiple users with the user IDs and stores them in the purchase information storage unit 21.

[0048] Therefore, even if the purchase information of one user is stored in various locations across the customer information databases DB1 to DBn, all of this purchase information is collected and stored in an integrated manner by being associated with the user ID. The purchase information acquisition process is performed, for example, at a predetermined time each day, thereby updating the purchase information stored in the purchase information storage unit 21. Alternatively, the purchase information may be acquired each time new purchase information is added to the database, or in real time at regular intervals. Personal information may be downloaded only the first time, and from the second time onwards, only the user ID and purchase information may be downloaded.

[0049] (2) Creating household accounting information When the process of acquiring the purchase information is completed, the marketing server SV proceeds to step S20, and under the control of the household account book creation unit 12, executes the process of creating household account book information based on the purchase information stored in the purchase information storage unit 21 as follows.

[0050] That is, first, in step S21, the purchase information stored in the purchase information storage unit 21 is read for each user. Then, the products or services included in the purchase information are classified into a plurality of expenditure items using a pre-prepared household account template. In other words, the purchase information is automatically converted into household account information, which is a tool that most succinctly represents personal consumption.

[0051] Figure 6 shows an example of a household account book template, with expenditure items divided into fixed expenses, food, daily necessities, medical and hygiene expenses, cultural and entertainment expenses, clothing expenses, pocket money, savings, and special expenses. Each expenditure item is broken down into various goods or services, as shown in Figure 6. Of the above expenditure items, food, daily necessities, and medical and hygiene expenses are defined as necessary expenses, while cultural and entertainment expenses, clothing expenses, and pocket money are defined as leisure expenses. Leisure expenses are expenses that are not necessarily necessary for living, but are used to enrich your life.

[0052] The household account book creation unit 12 calculates the total purchase amount for each of the products or services classified into each expenditure item, and stores the identification information of the products or services classified into each expenditure item and the total purchase amount in association with the user ID as household account book information for each user in the household account book storage unit 22.

[0053] Next, in step S22, the household account book creation unit 12 reads personal information of each user from the purchase information storage unit 21 and classifies each user into an income bracket based on the annual income included in the personal information. Then, for each income bracket, it reads user-specific household account book information for each user classified into that income bracket from the household account book storage unit 22, and calculates the average or variance of purchase amounts for each expenditure item and for each product or service included in that expenditure item based on this user-specific household account book information. Then, it stores this household account book information created for each income bracket in the household account book storage unit 22 in association with an income bracket ID.

[0054] As a result, for example, the user-specific household ledger of each user U1 to Uk shown in (a) of Figure 7 is classified by income group, and based on the household ledger information of multiple users classified into each income group, household ledger information by income group is created as shown in (b) of Figure 7.

[0055] In step S23, the household account book creation unit 12 then reads out the personal information of each user from the purchase information storage unit 21, identifies the area in which the user lives (for example, set by town name) based on the home address included in the personal information, and classifies each user into one of the identified multiple area books. For each area book, the household account book creation unit 12 also reads out the individual household account book information of each user classified into that area from the household account book storage unit 22, and calculates the average or variance of the purchase amount for each expenditure item and for each product or service included in that expenditure item based on this user household account book information. The household account book information created for each area book is then stored in the household account book storage unit 22 in association with the area book ID.

[0056] As a result, for example, the user-specific household ledger of each user U1 to Uk shown in (a) of Figure 7 is classified by regional area based on the user's residential address, and household ledger information by regional area is created as shown in (c) of Figure 7 based on the household ledger information of multiple users classified into each regional area.

[0057] For example, based on the address of the store where the purchase was made, which is included in the purchase information, the local area (the user's typical activity area) that the user visits most frequently or for the most time may be identified for each user, and household accounting information may be created by classifying each user into the similarly identified activity area.

[0058] (3) Selecting users to approach The marketing server SV monitors input of an analysis request in step S30. Then, when it receives an analysis request from, for example, the service providing server GM, it executes the following process to select approach target users who meet the conditions requested by the analysis request under the control of the analysis unit 13 and the approach target selection unit 14. The analysis request includes information specifying the product or service of interest and information specifying whether income or residential area will be used to narrow down the approach target users (narrowing specification information).

[0059] (3-1) When selecting target users from all users First, in step S31, the analysis unit 13 determines whether the narrowing-down designation information is included in the analysis request. If the narrowing-down designation information is not included, in step S60, all users stored in the purchase information storage unit 21 are selected, and in step S70, a process is performed to select users to be approached from among all users. Figure 5 is a flowchart showing the process procedure for selecting users to be approached and the process contents.

[0060] First, in step S71, the analysis unit 13 sets a threshold value (first threshold value) for user selection based on the consumption ratios of all users. This first threshold value is set based on the average value of the consumption ratios obtained for all users stored in the purchase information storage unit 21.

[0061] It is also possible to set the first threshold based on statistical data on the expenditure structure of a typical household. In this case, statistical data can be found, for example, in "Report on Consumer Issues and Consumer Policy, Part 1: Current Status of Consumer Issues, Chapter 1: Trends in the Socio-Economic Situation Surrounding Consumers and Consumer Behavior and Attitudes," Chart 1-1-1-3, etc. (2009-2011), [Retrieved February 14, 2017], and the Internet.<URL: http: / / www.caa.go.jp / adjustments / houkoku / honbun_1_1_1.html> is available.

[0062] Next, in step S72, the analysis unit 13 selects one user from all the users selected in step S60. Then, for this selected user, the analysis unit 13 calculates the consumption ratio between the product or service of interest specified in the analysis request and other products or services in the same expenditure item, based on the user-specific household account book information stored in the household account book storage unit 22.

[0063] Next, in step S74, the approach target selection unit 14 compares the calculated consumption ratio with the first threshold value set in step S71, and if the consumption ratio is equal to or greater than the first threshold value, selects the user as an approach target in step S75. On the other hand, if the consumption ratio is less than the first threshold value, the user is not selected as an approach target.

[0064] For example, suppose a service provider specifies "sports goods or services" as a product or service of interest. In this case, the analysis unit 13 refers to the household account book information shown in FIG. 6 and calculates the consumption ratio between "sports" and the same expenditure item as the expenditure item containing the sports, i.e., other products or services in the "Culture and Entertainment Expenses" category, such as "entertainment," "leisure and travel," and "gardening." If the calculation results in the consumption ratio of "sports" within the expenditure item "Culture and Entertainment Expenses" being equal to or higher than a first threshold, the user is deemed to have a strong desire to purchase "sports goods or services," and the user is selected as a target for approach. On the other hand, even if the purchase amount for "sports goods or services" is high, if the consumption ratio of "sports" within the expenditure item "Culture and Entertainment Expenses" is less than the first threshold, the user is not selected as a target for approach.

[0065] The approach target selection unit 14 stores the user ID of the selected approach target user in the approach information storage unit 24. At this time, personal information associated with the user ID is read from the purchase information storage unit 21, and the personal information is stored in the approach information storage unit 24 in association with the user ID.

[0066] In step S76, the analysis unit 13 determines whether the selection process has been completed for all users who are candidates for selection. If there are any users left that have not yet been selected, the process returns to step S72 to select the next user, and the processes of steps S73 to S75 are repeated. The above processes are repeated until there are no more unselected users.

[0067] (3-2) When selecting target users after narrowing down the user set by income level and area Assume that narrowing-down specification information is included in the analysis request in step S31. In this case, the marketing server SV performs a process of narrowing down users in step S40 under the control of the analysis unit 13 and the approach target selection unit 14. Figure 4 is a flowchart showing the process procedure and process contents.

[0068] (3-2-1) Narrowing down by income bracket First, in step S41, the analysis unit 13 sets a second threshold value for selecting an income group and a third threshold value for selecting a regional area. These threshold values ​​are set based on the average value of the consumption ratios calculated for each expenditure item based on the household account book information by income group and the household account book information by region stored in the household account book storage unit 22.

[0069] The analysis unit 13 selects one income group in step S42. Then, in step S43, for the selected income group, the analysis unit 13 calculates the consumption ratio between the product or service of interest specified by the analysis request and other products or services in the same expenditure item, based on the income-group-specific household account book information stored in the household account book storage unit 22.

[0070] Next, in step S44, the approach target selection unit 14 compares the calculated consumption ratio with the second threshold set in step S41, and if the consumption ratio is equal to or greater than the second threshold, selects the income group in step S45. On the other hand, if the consumption ratio is less than the second threshold, the income group is not selected.

[0071] For example, suppose a service provider specifies the aforementioned "sports goods or services" as a product or service of interest. In this case, the analysis unit 13 refers to household account book information by income group and calculates the consumption ratio between "sports" and the same expenditure item as the expenditure item containing the sports, i.e., other goods or services in the "Culture and Entertainment Expenses" category, such as "entertainment," "leisure and travel," and "gardening." If the calculation results in the consumption ratio of "sports" within the expenditure item "Culture and Entertainment Expenses" being higher than the second threshold, the user set belonging to that income group is deemed to have a high willingness to purchase "sports goods or services," and the user set of that income group is selected as a candidate to be approached. On the other hand, even if the purchase amount for "sports goods or services" is high, if the consumption ratio of "sports" within the expenditure item "Culture and Entertainment Expenses" is less than the second threshold, the user set belonging to that income group is not selected.

[0072] The approach target selection unit 14 stores the IDs of the income brackets selected as the approach target candidates in the approach information storage unit 24. In step S46, the analysis unit 13 determines whether the selection process for all income classes to be selected has been completed. If there are any income classes that have not yet been selected, the process returns to step S42 to select the next income class, and the process of steps S43 to S45 is repeated. The above process is repeated until there are no more unselected income classes.

[0073] (3-2-2) Narrowing down by region After the process of narrowing down the user set by income class is completed, the analysis unit 13 then executes the process of narrowing down the user set by regional area as follows. That is, the analysis unit 13 first selects one regional area in step S47. Then, in step S48, for the selected regional area, the analysis unit 13 calculates the consumption ratio between the product or service of interest specified by the analysis request and other products or services in the same category, based on the regional household account book information stored in the household account book storage unit 22.

[0074] Next, in step S49, the approach target selection unit 14 compares the calculated consumption ratio with the third threshold value set in step S41, and if the consumption ratio is equal to or greater than the third threshold value, selects the regional area in step S51. On the other hand, if the consumption ratio is less than the third threshold value, the regional area is not selected.

[0075] For example, if "sports goods or services" is specified as the product or service of interest as mentioned above, if the consumption ratio of "sports" within the expenditure category of "culture and entertainment" is higher than the third threshold, the user set residing in that local area is deemed to have a high willingness to purchase "sports goods or services," and the user set in that local area is selected as a candidate to be approached. On the other hand, even if the purchase amount for "sports goods or services" is high, if the consumption ratio of "sports" within the expenditure category of "culture and entertainment" does not meet the third threshold, the user set residing in that local area is deemed to have a low interest in sports and is not selected.

[0076] The approach target selection unit 14 stores the IDs of the regional areas selected as the approach target candidates in the approach information storage unit 24. In step S52, the analysis unit 13 determines whether the selection process for all regional areas to be selected has been completed. If there are any regional areas that have not yet been selected, the process returns to step S47 to select the next regional area, and the processes in steps S48 to S51 are repeated. The above processes are repeated until there are no more unselected regional areas.

[0077] When the narrowing down process by income group and region is completed, the approach target selection unit 14 selects a set of users who belong to the selected income group and reside in the selected regional area in step S53. Therefore, for example, from a set of users in an income group who are highly interested in "sports," a set of users who reside in a regional area who are also highly interested in "sports" is selected.

[0078] When the narrowing down process by income group and region has been performed, in step S70, the analysis unit 13 and the approach target selection unit 14 select users to be approached from among the users included in the user set who belong to the selected income group and reside in the selected regional area.

[0079] Thus, in this case, the approach information storage unit 24 stores as approach targets users who have a strong desire to purchase "sports goods," selected from a group of users who are in an income bracket where there are many users who are highly interested in "sports" and who live in a regional area where there are many users who are highly interested in "sports."

[0080] In the above description, users to be approached are selected from a set of users selected by narrowing down by income group and by region. However, this is not limiting, and users to be approached may be selected from a set of users selected by narrowing down by income group, and also from a set of users selected by narrowing down by region.

[0081] (4) Providing approach information When the marketing server SV receives a request for distribution of approach target information from the service providing server GM and detects receipt of the request in step S80, it reads out approach information from the approach information storage unit 24 in step S81 under the control of the transmission control unit 15. Then, it transmits this approach information from the communication interface unit 30 to the requesting service providing server GM.

[0082] When the service providing server GM receives the approach information, it transmits direct mail to the terminals TM1 to TMm of the users listed in the approach information to introduce new products, for example, "sports goods or services."

[0083] (effect) As described above in detail, in one embodiment, the marketing server SV collects purchase information for each user from multiple customer information databases DB1 to DBn, and creates household account book information for each user, income group, and regional area based on this collected purchase information. First, based on the household account book information for each income group and the household account book information for each regional area, an income group and a regional area are selected in which the consumption ratio of a product or service of interest among a group of products or services with the same expenditure item is equal to or exceeds a threshold value. From a set of users belonging to either or both of these selected income groups and regional areas, users whose consumption ratio of a product or service of interest among a group of products or services with the same expenditure item is equal to or exceeds a threshold value are selected as approach target users.

[0084] Generally, among multiple types of products or services, those with a relatively high consumption ratio tend to reflect users' purchasing intentions. Therefore, by selecting target users by focusing on the consumption ratio as described above, it is possible to select users with a high purchasing intention for the product or service of interest with a high probability.

[0085] Furthermore, prior to selecting users to approach, the system selects the income bracket and regional area in which the consumption ratio of the product or service of interest is above a threshold value, thereby narrowing down the set of users who are candidates to approach from among a large number of users, thereby enabling efficient selection of users to approach.

[0086] Furthermore, household account book information is created by user, income bracket, and regional area based on purchase information collected from customer information databases DB1 to DBn, and based on this household account book information, the system narrows down and selects target users by focusing on the consumption breakdown of multiple products or services with the same expenditure item, making it possible to accurately select users who are highly interested in the products or services of interest.

[0087] Furthermore, since the purchase information of one user is collected from each of multiple customer information databases DB1 to DBn to create household account book information, it is possible to collect a wide range of purchase information on products or services purchased by one user from multiple stores using a common point card or multiple credit cards or point cards, thereby making it possible to more accurately grasp the user's consumption breakdown.

[0088] [Other embodiments] When selecting users to be approached, the consumption ratio of goods or services classified as necessary expenses among the multiple expenditure items in the household account book data to goods or services classified as leisure expenses that are not necessarily necessary but are used to enrich life may be calculated, and users to be approached may be selected based on the calculated consumption ratio.

[0089] In this way, when focusing on products or services related to hobbies or entertainment, for example, users with a high ratio of leisure expenses to necessary expenses can be considered to have a strong desire to purchase products or services related to hobbies or entertainment, and can be selected with a high probability.

[0090] In the embodiment, household account book information is created for each income group and each regional area, and a user set is selected using the household account book information, and target users to be approached are selected from the selected user set. However, without being limited to this, for example, household account book information may be created for each age group or family structure, and a user set may be selected using the household account book information, and target users to be approached may be selected from the selected user set.

[0091] Furthermore, instead of grouping users by user, it is also possible to form user groups based on, for example, regional information, income, or purchasing information, and collect purchasing information for each user group, so that the purchasing information of the users included in the user group can be mutually complemented. Furthermore, if the recommendation service involves inserts or posting advertisements, a distribution control unit for flyers, etc. is added to the marketing server SV or the service provider server GM. Then, it can be configured to send a flyer distribution request together with print data to the terminals of the company or posting company that undertakes the distribution of inserts or posting advertisements.

[0092] In addition, the means for acquiring purchase information, the means for generating information representing consumption breakdowns, the functions of the means for selecting users, the configuration of the marketing information analysis device, etc. can be modified and implemented in various ways without departing from the spirit of this invention.

[0093] In short, this invention is not limited to the above-described embodiments, and in the implementation stage, the components can be modified and embodied without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining multiple components disclosed in the above-described embodiments. For example, some components may be omitted from all the components shown in the embodiments. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0094] SV...marketing server, DB1 to DBn...purchase information management server, GM...data provision server, TM to TMm...user terminal, NW...communication network, 10...control unit, 20...storage unit, 30...communication interface unit, 11...purchase information acquisition control unit, 12...household account book creation unit, 13...analysis unit, 14...approach target selection unit, 15...transmission control unit, 21...purchase information memory unit, 22...household account book memory unit, 23...analysis result memory unit, 24...approach information memory unit.

Claims

1. an acquisition means for acquiring purchase information of a plurality of users from a purchase information management database that manages purchase information of a plurality of types of products or services for each of the plurality of users; a generation means for generating, for each user, information indicating a consumption breakdown of products or services purchased by the user based on the acquired purchase information; and a calculation means for calculating, for each user, a consumption ratio, which is the ratio of consumption of a product or service of interest to other products or services included in a predetermined expenditure item, based on the information representing the generated consumption breakdown; The consumption ratio is used to select a user to be approached from the plurality of users. Marketing information analysis device.

2. 2. The marketing information analysis device according to claim 1, wherein, when the purchase information of one user is managed in a plurality of purchase information management databases in a distributed manner, the acquisition means accesses each of the plurality of purchase information management databases to acquire a plurality of pieces of purchase information related to the user, and integrates the acquired plurality of pieces of purchase information by user and stores the integrated information in memory.

3. The generating means A means for classifying the users into a plurality of income groups and generating information for each income group that indicates a breakdown of consumption of goods or services purchased by a group of users classified into the income group. The marketing information analysis device according to claim 1 or 2, further comprising:

4. The generating means A means for classifying the users into a plurality of regional areas according to their location or place of purchase, and generating information for each regional area that indicates a breakdown of consumption of goods or services purchased by a group of users classified into the corresponding regional area. The marketing information analysis device according to claim 1 or 2, further comprising:

5. 2. The marketing information analysis device of claim 1, wherein the generation means includes household account book data in which expenditure items are divided into a plurality of items, and generates information representing the consumption breakdown by classifying, for each user, income bracket, or regional area, the products or services purchased by the user or user group and the purchase amounts thereof into corresponding items of the household account book data based on the acquired purchase information of the user or user group.

6. A marketing information analysis method executed by an information processing device having a processor and a memory, comprising: a step in which the information processing device acquires purchase information of the plurality of users from a purchase information management database that manages purchase information of a plurality of types of products or services for each of the plurality of users; a step of generating, by the information processing device, information representing a consumption breakdown of products or services purchased by each user, based on the acquired purchase information; and a step in which the information processing device calculates, for each user, a consumption ratio, which is the ratio of consumption of a product or service of interest to other products or services included in a predetermined expenditure item, based on the generated information representing the consumption breakdown, The consumption ratio is used to select a user to be approached from the plurality of users. Marketing information analysis methods.

7. 6. A marketing information analysis program that causes a processor to operate as each of the means provided in the marketing information analysis device according to claim 1.

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