JP7565816B2 - Server device and program - Google Patents

Description

An embodiment of the present invention relates to a server device and a program.

Traditionally, companies that operate retail stores have collected users' purchasing information as big data and analyzed purchasing trends, etc. However, there are cases where information that can identify users is not collected, and in these cases, there is a problem that it is not possible to perform analysis that identifies individuals using only the collected data.

On the other hand, a technology has been proposed that identifies users based on their credit card numbers, allowing them to purchase products and enjoy services offered by stores without providing personal information.

However, due to security restrictions, credit card numbers that can be collected at retail stores can only be stored with some of the numbers masked. As a result, there is a possibility that credit card numbers belonging to different users may overlap, making it difficult to identify a user without the cooperation of the credit card company.

The problem that this invention aims to solve is to provide a server device and a program that can manage purchasing information related to a transaction on a per-user basis, even when information that identifies an individual is not available at the time of the transaction.

The server device of the embodiment includes a first extraction means, a second extraction means, and a storage means. The first extraction means extracts purchasing information having the same number information from a storage device that stores purchasing information including a store identifier that is generated for each transaction at a store and can identify the store, item information indicating a breakdown of products purchased at the store, and number information indicating at least a part of the credit card number used to pay for the products. The second extraction means extracts purchasing information of stores located in the same area from the purchasing information extracted by the first extraction means based on the address of the store corresponding to the store identifier. The storage means stores the purchasing information extracted by the second extraction means as purchasing information related to the same user, in association with a user identifier that identifies the user.

FIG. 1 is a diagram illustrating an example of the configuration of a data collection system according to the first embodiment. FIG. 2 is a diagram illustrating an example of a hardware configuration of a server device according to the first embodiment. FIG. 3 is a diagram illustrating an example of a data configuration of a store information management table according to the first embodiment. FIG. 4 is a diagram illustrating an example of a data configuration of the purchase information management table according to the first embodiment. FIG. 5 is a diagram illustrating an example of PAN mask information according to the first embodiment. FIG. 6 is a diagram illustrating an example of a data configuration of the product purchasing demographic management table according to the first embodiment. FIG. 7 is a diagram illustrating an example of a data configuration of a user management table according to the first embodiment. FIG. 8 is a diagram illustrating an example of a functional configuration of the server device according to the first embodiment. FIG. 9 is a diagram for explaining the operation of the second extraction unit according to the first embodiment. FIG. 10 is a diagram for explaining the operation of the user attribute estimation unit according to the first embodiment. FIG. 11 is a flowchart illustrating an example of processing executed by the server device of the first embodiment. FIG. 12 is a diagram illustrating an example of a functional configuration of a server device according to the second embodiment. FIG. 13 is a diagram for explaining the operation of the user identification unit according to the second embodiment. FIG. 14 is a flowchart illustrating an example of a process executed by the server device according to the second embodiment.

The following describes the embodiments in detail with reference to the drawings. Note that the present invention is not limited to the embodiments described below.

[First embodiment]
Fig. 1 is a diagram showing an example of the configuration of a data collection system according to the first embodiment. As shown in Fig. 1, the data collection system 1 includes a store terminal 10, a card company 20, and a server device 30. The store terminal 10, the card company 20, and the server device 30 are communicatively connected via a network N such as the Internet or a mobile phone network.

The store terminal 10 is a terminal device such as a POS terminal or a PC (Personal Computer) that is installed in each store SP. Note that there is no particular limit to the number of stores SP or the number of store terminals 10 installed in the store SP. In addition, the store SP may be, for example, a chain store or franchise store operated by a single company.

The store terminal 10 executes various processes related to its own store SP under the control of a processor (not shown). Specifically, the store terminal 10 executes payment processing for products purchased by users (consumers) who visit the store SP.

Payment methods for products include cash and credit card payment. When credit card payment is specified, the store terminal 10 executes the payment process by sending information related to the credit card payment, including the user's credit card number and the purchase amount of the product (hereinafter also referred to as payment information), to the card company 20. The store terminal 10 then generates purchase information indicating the details of the payment process and sends it to the server device 30. The purchase information will be described later.

The timing of transmitting the purchasing information is not particularly important. For example, the store terminal 10 may transmit purchasing information for each transaction, or may transmit all the purchasing information generated up to that point at once on a preset date and time. The store terminal 10 may also transmit purchasing information in response to a request from the server device 30.

The card company 20 is an information processing device (e.g., a credit server, etc.) of the card company that provides credit payment services. In the following description, the card company 20 may be interpreted as a server that is physically different from the server device 30. The card company 20 executes credit and payment processing based on the payment information, etc. sent from the store terminal 10, and returns the payment result to the store terminal 10. For example, if the payment processing is possible, the card company 20 notifies the store terminal 10 that the payment is possible or that the payment processing has been completed as the payment result. If the card company 20 determines that the payment processing is impossible due to insufficient balance, etc., the card company 20 notifies the store terminal 10 that the payment processing is not possible as the payment result. It is assumed that the card company 20 is provided for each card company (card issuing company, etc.).

The server device 30 is an example of a server device according to this embodiment. Note that, in this embodiment, an example is described in which the server device 30 is realized by a single device, but this is not limiting, and the server device 30 may be realized by multiple devices, for example, using a technology such as cloud computing.

The server device 30 collects (acquires) purchasing information from each store SP (store terminal 10). The server device 30 also stores and manages the collected purchasing information in a purchasing information management table 372 described below. The purchasing information stored in the server device 30 is used, for example, for big data analysis.

Next, the configuration of the server device 30 described above will be described.

FIG. 2 is a diagram showing an example of the hardware configuration of the server device 30. As shown in FIG. 2, the server device 30 includes a computer configuration including a CPU 31, a ROM (Read Only Memory) 32, and a RAM (Random Access Memory) 33.

The CPU 31 is an example of a processor, and controls each part of the server device 30. The ROM 32 stores various programs. The RAM 33 is a workspace in which programs and various data are deployed.

The server device 30 also includes a display unit 34, an operation unit 35, a communication unit 36, and a memory unit 37.

The display unit 34 is a display device such as an LCD (Liquid Crystal Display). The display unit 34 displays various information and screens under the control of the CPU 31. The operation unit 35 has input devices such as a keyboard and a mouse, and outputs signals to the CPU 31 according to the operation content.

The communication unit 36 is a communication interface that can be connected to the network N. The communication unit 36 communicates with external devices such as the store terminal 10 and the card company 20 via the network N.

The memory unit 37 is an example of a storage device. The memory unit 37 is composed of a storage medium such as a hard disk drive (HDD) or flash memory, and maintains the stored contents even when the power is cut off. The memory unit 37 stores programs that the CPU 31 can execute and various setting information. The CPU 31 executes various processes by operating according to the programs stored in the ROM 32 or the memory unit 37 and deployed in the RAM 33.

The memory unit 37 also stores a store information management table 371, a purchasing information management table 372, a product purchasing demographic management table 373, and a user management table 374.

The store information management table 371 is a data table for storing and managing information about each store SP. The store information management table 371 has, for example, the data structure shown in FIG. 3.

Figure 3 is a diagram showing an example of the data configuration of the store information management table 371. As shown in Figure 3, the store information management table 371 stores the store name, postal code, address, etc. in association with the store ID of each store SP.

The store ID is an example of a store identifier, and is identification information for identifying each store SP. The store name is information indicating the store name or trade name of the store SP corresponding to the store ID. The postal code is the postal code of the store SP corresponding to the store ID. Furthermore, the address is information indicating the address of the store SP corresponding to the store ID. Here, the postal code and address are used to identify the region (area) in which the store SP is located.

The data configuration of the store information management table 371 is not limited to the example in FIG. 3. For example, the store information management table 371 may store a telephone number in association with a store ID. In this case, the area code or the like included in the telephone number may be used as information for identifying the area in which the store SP is located. In addition, map data including the area in which each store SP is located may be stored in the memory unit 37.

The purchasing information management table 372 is a data table for storing and managing purchasing information generated by each store SP (store terminal 10). The purchasing information management table 372 has, for example, the data structure shown in FIG. 4.

Figure 4 is a diagram showing an example of the data configuration of the purchasing information management table 372. As shown in Figure 4, the purchasing information management table 372 stores the components of purchasing information, such as a store ID, a transaction ID, a transaction date and time, PAN (Primary Account Number) mask information, a destination code, a purchase amount, and a purchased item, in association with each other.

The store ID is information indicating the store ID of the store SP that generated the purchase information. The transaction ID is an identifier (transaction number, etc.) for identifying the transaction related to the generation of the purchase information. The transaction date and time is information indicating the date and time when the transaction corresponding to the transaction ID was made.

PAN mask information is an example of number information. PAN mask information is a character string that indicates part of the credit card number (also called PAN) that was entered during a transaction corresponding to the transaction ID. For example, as shown in FIG. 5, PAN mask information is a character string (sequence of numbers) that indicates a credit card number, such as 16 digits, with some of the numbers masked.

Figure 5 is a diagram showing an example of PAN mask information. As shown in Figure 5, PAN mask information is a method in which a certain number of digits of a credit card number, which is made up of a sequence of a specified number of digits such as 16 digits, are represented by masked characters (MS in the figure) that make the numbers indistinguishable.

The reason for masking credit card numbers here is due to security requirements. For example, the PCI DSS (Payment Card Industry Data Security Standard) generally only permits retention of a portion of the number, such as the first six digits and the last four digits, as shown in FIG. 5. Therefore, credit card numbers, which should be unique, are masked with the mask character MS, making it impossible to identify individuals. In other words, with PAN mask information, there is a possibility that the numbers may be duplicated among multiple users.

Returning to FIG. 4, the destination code is an identifier for identifying the card company 20 (such as a card issuing company) to which the payment information (credit card number) was sent in the transaction corresponding to the transaction ID. The purchase amount is information indicating the total amount of the items purchased in the transaction corresponding to the transaction ID. The purchased items are an example of item information indicating the details of the items purchased in the transaction corresponding to the transaction ID. Note that the item information may be, in addition to the purchased items, department information associated with the purchased items, or supplemental information identifying the purchased items (such as information about the manufacturer, place of production, etc.).

The data structure of the purchasing information management table 372 is not limited to the example shown in FIG. 4. For example, the purchasing information management table 372 may store the terminal identifier of the store terminal 10 that executed the payment process for the transaction corresponding to the transaction ID.

The product purchasing demographic management table 373 is a data table that associates the type of product with the attributes of the user demographic that purchases the product. The product purchasing demographic management table 373 has, for example, the data structure shown in FIG. 6.

Figure 6 is a diagram showing an example of the data configuration of the product purchase demographic management table 373. As shown in Figure 6, the product purchase demographic management table 373 stores product names, categories, user demographics, etc. in association with product IDs.

The product ID is an identifier for identifying a product sold at the store SP. For example, a JAN code can be used as the product ID. The product name is information indicating the product name of the product corresponding to the product ID. The category is information indicating the category of the product corresponding to the product ID. The user demographic stores the attributes of users who are expected to purchase the product corresponding to the product ID. Figure 6 shows an example in which gender and age group are set as user attributes.

For example, when the gender and age group of users who are likely to purchase a certain product are derived from the results of an analysis of product purchasing trends at a certain store SP, the product ID of the product is associated with the user attributes and registered in the product purchasing group management table 373. Also, when a certain product is targeted at a specific user group (for example, men's cosmetics, girls' toys, etc.), the product ID of the product is associated with the user attributes and registered in the product purchasing group management table 373.

The data configuration of the product purchasing demographic management table 373 is not limited to the example shown in FIG. 6. For example, if the same product or similar products are assigned different product IDs at multiple stores SP, the same product name, category, and user demographic may be associated with these multiple product IDs.

The user management table 374 is a data table for storing and managing information about users who are presumed to be the same person in the process described below. The user management table 374 has, for example, the data structure shown in FIG. 7.

Figure 7 is a diagram showing an example of the data configuration of user management table 374. As shown in Figure 7, user management table 374 stores PAN mask information, addresses, user attributes, transaction IDs, etc. in association with user IDs.

The user ID is an identifier that identifies users who are presumed to be the same person in the process described below. The PAN mask information is the PAN mask information of the user corresponding to the user ID. Note that, as mentioned above, PAN mask information is not unique information, so there is a possibility that it may overlap between different user IDs.

The address is information indicating the address of the user corresponding to the user ID. The user attributes are information indicating the user attributes of the user corresponding to the user ID. Here, the address and user attributes are estimated values estimated in the process described below. Furthermore, the transaction ID is information indicating the transaction ID included in the purchasing information of the user corresponding to the user ID. The user ID and purchasing information are stored in association with each other using such transaction ID.

The data configuration of the user management table 374 is not limited to the example in FIG. 6. For example, the user management table 374 may store, in association with a user ID, the number of pieces of purchasing information used in the estimation, information indicating the reliability of the estimation result, and the like.

Next, the functional configuration of the server device 30 will be described with reference to FIG. 8.

FIG. 8 is a diagram showing an example of the functional configuration of the server device 30. As shown in FIG. 8, the server device 30 includes a purchase information collection unit 311, a first extraction unit 312, a second extraction unit 313, a user attribute estimation unit 314, and a memory control unit 315 as functional units.

Some or all of the functional units of the server device 30 may be software configurations realized by cooperation between the processor (e.g., CPU 31) of the server device 30 and a program stored in a memory (e.g., ROM 32, storage unit 37). Also, some or all of the functional units of the server device 30 may be hardware configurations realized by a dedicated circuit or the like mounted on the server device 30.

The purchasing information collection unit 311 is an example of a collection means. The purchasing information collection unit 311 collects (acquires) purchasing information from each store SP (store terminal 10). In addition, the purchasing information collection unit 311 registers the collected purchasing information in the store information management table 371.

The method of collecting the purchasing information is not particularly important. For example, the purchasing information collection unit 311 may receive purchasing information transmitted from the store SP (store terminal 10), or may request the store SP (store terminal 10) to transmit purchasing information at a preset date and time.

The first extraction unit 312 is an example of a first extraction means. The first extraction unit 312 extracts purchasing information having the same PAN mask information from the purchasing information stored in the purchasing information management table 372. Specifically, the first extraction unit 312 refers to the PAN mask information included in each piece of purchasing information, and extracts purchasing information that includes the same PAN mask information.

The timing at which the first extraction unit 312 extracts the purchasing information is not particularly important. For example, the first extraction unit 312 may extract the purchasing information by checking for overlapping PAN mask information with existing purchasing information each time new purchasing information is registered in the purchasing information management table 372. Also, for example, the first extraction unit 312 may extract the purchasing information at a predetermined timing (e.g., once a month).

The second extraction unit 313 is an example of a second extraction means. Based on the addresses of the stores SP stored in the store information management table 371, the second extraction unit 313 extracts purchasing information of stores SP located in the same area from the purchasing information extracted by the first extraction unit 312. Specifically, based on the store ID included in each piece of purchasing information extracted by the first extraction unit 312, the second extraction unit 313 identifies the address and postal code of the store SP corresponding to the store ID from the store information management table 371. Next, the second extraction unit 313 compares the addresses and postal codes identified for each piece of purchasing information, and extracts each piece of purchasing information related to the same area. The operation of the second extraction unit 313 will be described below with reference to FIG. 9.

Figure 9 is a diagram for explaining the operation of the second extraction unit 313. The three pieces of purchasing information Da, Db, and Dz shown on the left side of the figure are examples of purchasing information extracted by the first extraction unit 312. Each of the purchasing information Da, Db, and Dz includes a different store ID and the same PAN mask information.

In the case of FIG. 9, the second extraction unit 313 refers to the store information management table 371 and identifies the address (or postal code) corresponding to the store ID included in each of the purchasing information Da, Db, and Dz. If the identified address is the information shown below the purchasing information Da, Db, and Dz, the second extraction unit 313 determines that the purchasing information Da and the purchasing information Db are related to the same area. There is no particular method for determining whether the area is the same, and various determination criteria can be set. For example, the area may be determined to be the same if the city or ward level is the same, or the area may be determined to be the same if the postal code is the same.

Furthermore, the second extraction unit 313 infers that the purchase information Da and the purchase information Db are purchase information related to a transaction of the same user, and assigns a user ID that identifies the user. Figure 9 shows an example in which the user ID "123456890" is assigned to a virtual user Ua related to the purchase information Da and the purchase information Db.

The storage control unit 315, which will be described later, registers the transaction IDs of the purchasing information Da and purchasing information Db in the user management table 374 in association with the user ID of the user Ua. The storage control unit 315 also extracts the PAN mask information and address of the user Ua from the purchasing information Da and purchasing information Db, and registers them in the user management table 374 in association with the user ID of the user Ua.

The second extraction unit 313 also extracts the purchasing information Dz separately from the purchasing information Da and Db. The second extraction unit 313 then assumes that the purchasing information Dz is purchasing information related to a transaction of a virtual user Ub other than user Ua, and assigns a user ID that identifies the user Ub. Figure 9 shows an example in which the user ID "2010304050" is assigned to the virtual user Ub related to the purchasing information Dz.

In this case, the storage control unit 315, which will be described later, also registers the transaction ID of the purchasing information Dz in the user management table 374 in association with the user ID of user Ub. The storage control unit 315 also extracts the PAN mask information and address of user Ub from the purchasing information Dz, and registers them in the user management table 374 in association with the user ID of user Ub.

In the above example, the purchasing information relating to the same area is purchasing information relating to transactions by the same user. However, as a further narrowing down condition, if the transaction date and time included in the purchasing information satisfies a predetermined condition, it may be determined that the purchasing information relates to a transaction by the same user. For example, the second extraction unit 313 may extract purchasing information in the same area but with different transaction dates and times.

In addition, it is preferable that the address of the user registered in the user management table 374 be of the same accuracy as the criteria for determining the same area. In addition, if an existing user ID is associated with the purchase information, the user ID may be inherited, or may be updated to a new user ID.

Returning to FIG. 8, the user attribute estimation unit 314 is an example of an estimation means. The user attribute estimation unit 314 estimates the user attributes of the user related to the purchasing information extracted by the second extraction unit 313 based on the product purchasing demographic management table 373. Specifically, the user attribute estimation unit 314 refers to the product purchasing demographic management table 373 and identifies the user attributes of the user demographic corresponding to the purchased product included in the purchasing information. The user attribute estimation unit 314 then estimates the user attributes of the user related to the purchasing information from the identified user attributes. The operation of the user attribute estimation unit 314 will be described below with reference to FIG. 10.

Figure 10 is a diagram for explaining the operation of the user attribute estimation unit 314. The two pieces of purchase information Da and Db shown on the left side of the figure are examples of purchase information extracted by the second extraction unit 313. Note that Figure 10 shows the breakdown of purchased items included in the purchase information Da and Db described in Figure 9.

The user attribute estimation unit 314 refers to the product purchase demographic management table 373 for each of the purchased products, products A to D, included in the purchase information Da, and reads out the corresponding product classification and user attributes (gender, age group). Similarly, the user attribute estimation unit 314 refers to the product purchase demographic management table 373 for each of the purchased products, products E to J, included in the purchase information Db, and identifies the corresponding product classification and user attributes. In Figure 10, the user attributes identified from the product purchase demographic management table 373 are shown to the right of the purchase information Da and Db. Note that for products that do not require user attributes, "none" is shown, indicating no attribute.

When the user attribute estimation unit 314 identifies the user attributes for each of the purchased products included in the purchasing information Da and Db, it estimates the user attributes of the user ID (user Ua) related to the purchasing information Da and Db from among those user attributes.

For example, the user attribute estimation unit 314 may estimate all of the identified user attributes as the user attributes of user Ua. The user attribute estimation unit 314 may also estimate the user attributes of user Ua based on the frequency or number of occurrences of the user attributes. As an example, a user attribute whose frequency or number of occurrences exceeds a threshold value may be estimated as the user attribute of user Ua. The user attribute estimation unit 314 may also estimate the user attributes of user Ua based on the user attributes of a predetermined category (e.g., clothing, etc.) among the categories of purchased items.

As shown on the right side of the figure, FIG. 10 shows an example in which the user attributes of user Ua are estimated to be gender "male" and age group "adult," and the family structure is estimated to include a child (male). When the user attribute estimation unit 314 estimates the user attributes, the memory control unit 315, which will be described later, registers the estimated user attributes in the user management table 374 in association with the user ID of user Ua related to the purchasing information Da and Db.

Returning to FIG. 8, the storage control unit 315 is an example of a storage means. The storage control unit 315 stores the purchasing information extracted by the second extraction unit 313 as purchasing information relating to the same user, in association with the user ID of the user. The storage control unit 315 also stores the user attributes estimated from the purchasing information by the user attribute estimation unit 314, in association with the user ID of the user related to the purchasing information.

Specifically, the storage control unit 315 associates the user ID assigned by the second extraction unit 313 with the transaction ID of the purchasing information related to the user with that user ID and registers (stores) the user attributes in the user management table 374. As a result, the user management table 374 stores, for each user ID of a virtual user, the transaction ID of the purchasing information estimated to be the transaction of that user and the user attributes estimated from that purchasing information in association with each other.

Below, an example of the operation of the server device 30 is described with reference to FIG. 11.

Figure 11 is a flowchart showing an example of processing performed by the server device 30. Note that, as a prerequisite for this processing, it is assumed that the purchasing information collected by the purchasing information collection unit 311 is stored in the purchasing information management table 372.

First, the first extraction unit 312 extracts purchasing information that includes the same PAN mask information from the purchasing information management table 372 (step S11). Next, the second extraction unit 313 refers to the store information management table 371, identifies the address of the store ID included in the purchasing information extracted in step S11, and further extracts purchasing information of stores SP located in the same area from the purchasing information as purchasing information related to the same user (step S12).

Then, the second extraction unit 313 estimates the user attributes of the user related to the purchasing information based on the purchased products included in the purchasing information extracted in step S12 (step S13). Then, the storage control unit 315 stores the transaction ID of the purchasing information extracted in step S12 and the user attributes estimated in step S13 in the user management table 374 in association with the user ID (step S14), and ends this process.

As described above, the server device 30 of this embodiment extracts purchasing information with the same PAN mask information from the purchasing information management table 372, which stores purchasing information generated for each transaction at the store SP. Furthermore, the server device 30 further extracts purchasing information of stores SP located in the same area from the extracted purchasing information based on the addresses of the stores SP stored in the store information management table 371. The server device 30 then stores the extracted purchasing information as purchasing information related to the same user, in association with the user ID that identifies the user.

As a result, even if the purchasing information is collected randomly without identifying individuals, the server device 30 can combine the information contained in the purchasing information to estimate purchasing information of transactions made by the same user and store it in association with the user ID. Therefore, even if information that identifies an individual is not available at the time of the transaction, the server device 30 can manage the purchasing information related to the transaction for each user.

The server device 30 also estimates the user attributes of the user based on the details of the purchased items included in the extracted purchasing information, and stores the estimated user attributes in association with the corresponding user ID. This allows the server device 30 to manage purchasing information by user, and to associate and manage the user attributes of users who have made transactions related to the purchasing information, thereby improving convenience when performing big data analysis, etc.

The server device 30 also estimates the user attributes based on a product purchasing demographic management table 373 that associates products with the user attributes of the user demographic that purchases the products. This allows the server device 30 to efficiently and accurately estimate the user attributes from the breakdown of purchased products included in the purchase information.

In this embodiment, the storage unit 37 of the server device 30 stores the store information management table 371, the purchase information management table 372, the product purchase demographic management table 373, and the user management table 374, but this is not intended to be limiting. For example, an external device such as a database server accessible to the server device 30 may store any or all of the store information management table 371, the purchase information management table 372, the product purchase demographic management table 373, and the user management table 374. In addition, any or all of the store information management table 371, the purchase information management table 372, the product purchase demographic management table 373, and the user management table 374 may be stored in the form of cloud storage, etc.

Second Embodiment
In the first embodiment, a form was described in which purchasing information of transactions presumably performed by the same user is extracted from randomly collected purchasing information, and stored in association with the user ID and user attributes of that user.

On the other hand, when a user issues a credit card, the user registers his/her personal information with a credit card company (e.g., card company 20). Therefore, it is common for the credit card company to manage the credit card number as user information together with the user's personal information. However, it is expected that the credit card number provided by the credit card company will be provided in the form of PAN mask information, part of which is masked, due to the security requirements mentioned above.

Therefore, in this embodiment, a server device 30 is described that, when user information is provided by the card company 20, can use the user information to complement the information stored in the user management table 374. Note that configurations similar to those described in the first embodiment are given the same reference numerals and descriptions are omitted.

FIG. 12 is a diagram showing an example of the functional configuration of server device 40 according to this embodiment. Note that server device 40 is a server device that replaces server device 30 described above, and has the same hardware configuration as server device 30.

As shown in FIG. 12, the server device 40 includes a purchase information collection unit 311, a first extraction unit 312, a second extraction unit 313, and a user attribute estimation unit 314, as well as a user information acquisition unit 411, a user identification unit 412, and a memory control unit 413.

Some or all of the functional parts of the server device 40 may be software configurations realized by cooperation between the processor (e.g., CPU 31) of the server device 40 and a program stored in a memory (e.g., ROM 32, storage unit 37). Also, some or all of the functional parts of the server device 40 may be hardware configurations realized by a dedicated circuit or the like mounted on the server device 40.

The user information acquisition unit 411 is an example of an acquisition means. The user information acquisition unit 411 acquires user information from the card company 20. Here, the user information provided by the card company 20 includes personal information such as the address, gender, date of birth, etc. of the relevant user, in addition to the PAN mask information.

The method of acquiring user information is not particularly important. For example, the user information acquisition unit 411 may receive purchasing information provided by the card company 20, or may request the card company 20 to transmit user information at a preset date and time.

The user identification unit 412 is an example of an identification means. The user identification unit 412 identifies a user corresponding to the user information acquired by the user information acquisition unit 411 from among the users corresponding to the user IDs registered in the user management table 374. Specifically, the user identification unit 412 identifies a user ID that meets the conditions of PAN mask information and address included in the user information from among the user IDs registered in the user management table 374.

The storage control unit 413 is an example of a storage means. The storage control unit 413 registers (stores) in the user management table 374 some or all of the information included in the user information of the corresponding user, in association with the user ID identified by the user identification unit 412.

The operation of the user identification unit 412 is described below with reference to Figure 13.

Figure 13 is a diagram for explaining the operation of the user identification unit 412. The data UD shown on the right side of the figure is an example of user information acquired by the user information acquisition unit 411. The data UD includes user information UDX relating to user X, user information UDY relating to user Y, and user information UDZ relating to user Z. In addition, each piece of user information UDX to UDZ has the PAN mask information, address, gender, date of birth, etc. of the corresponding user.

The user identification unit 412 uses the PAN mask information and address contained in each of the user information UDX to UDZ as search keys, and searches the user management table 374 for a user ID that meets the conditions of the search key. Specifically, the user identification unit 412 searches the user management table 374 for a user ID that completely matches the PAN mask information contained in each of the user information UDX to UDZ, and that partially matches or completely matches the address contained in each of the user information UDX to UDZ. Note that the match determination for the address may be performed with the same level of accuracy (for example, at the city or ward level) as the address stored in the user management table 374.

For example, if the conditions of the user information UDX match the conditions of the user ID "123456890" of the virtual user Ua stored in the user management table 374, the user identification unit 412 determines (identifies) that user X and user Ua are the same user. Also, for example, if the conditions of the user information UDZ match the conditions of the user ID "2010304050" of the virtual user Ub stored in the user management table 374, the user identification unit 412 determines that user Z and user Ub are the same user. Also, if the conditions of the user information UDY do not match the conditions of any of the user IDs, the user identification unit 412 determines that there is no applicable user.

The storage control unit 413 executes a process of registering (storing) in the user management table 374 some or all of the information included in the user information of the corresponding user, in association with the user ID identified by the user identification unit 412. For example, the storage control unit 413 extracts new information (elements) included in the user information that do not exist in the user management table 374, and stores the extracted elements in association with the user ID.

Here, FIG. 13 shows the state in which the date of birth included in the user information is stored in the user management table 374. Note that if the address included in the user information is more detailed than the address stored in the user management table 374, the address stored in the user management table 374 may be updated with the address included in the user information.

This allows the server device 40 to supplement the information stored in the user management table 374 using user information provided by the card company 20.

In the above example, the user is identified using the address along with the PAN mask information included in the user information, but this is not limiting and the user may be identified using other information included in the user information. For example, the user may be measured using the address and gender along with the PAN mask information, or the user may be identified using gender instead of the address.

Below, an example of the operation of the server device 40 is described with reference to FIG. 14.

Figure 14 is a flowchart showing an example of processing performed by the server device 40. Note that, as a premise of this processing, it is assumed that the user ID of the virtual user estimated in the processing of Figure 11 is stored in the user management table 374.

First, the user information acquisition unit 411 acquires user information provided by the card company 20 (step S21).

Next, the user identification unit 412 searches the user management table 374 for a user ID that meets the conditions of the user information based on the PAN mask information and address included in the user information (step S22). Next, the user identification unit 412 determines whether or not a user ID that meets the conditions exists (step S23).

If there is no user ID that meets the conditions of the user information (step S23; No), the user identification unit 412 ends this process. On the other hand, if there is a user ID that meets the conditions of the user information (step S23; Yes), the user identification unit 412 determines that the user has been identified and proceeds to step S24.

Then, the storage control unit 413 associates the information contained in the user information with the user ID identified by the user identification unit 412 and stores it in the user management table 374 (step S24), and ends this process.

As a result, the server device 40 can supplement the information about each user classified based on purchase information using the method of the first embodiment with user information provided by the credit card company.

The programs executed by each device in each of the above-described embodiments are provided in a state where they are pre-installed in a ROM, a storage unit, etc. The programs executed by each device in the above-described embodiments may be provided by being recorded in an installable or executable format on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk).

Furthermore, the programs executed by each device in each of the above-mentioned embodiments may be configured to be stored on a computer connected to a network such as the Internet and provided by downloading via the network. Also, the programs executed by each device in the above-mentioned embodiments may be configured to be provided or distributed via a network such as the Internet.

Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These new embodiments and their modifications can be implemented in various other forms, and various omissions, substitutions, changes, and combinations can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims.

REFERENCE SIGNS LIST 1 Data collection system 10 Store terminal 20 Card company 30, 40 Server device 311 Purchase information collection unit 312 First extraction unit 313 Second extraction unit 314 User attribute estimation unit 315 Memory control unit 411 User information acquisition unit 412 User identification unit 413 Memory control unit

JP 2018-49537 A

Claims (6)

a first extraction means for extracting purchase information having the same number information from a storage device that stores purchase information including a store identifier that is generated for each transaction at a store and is capable of identifying the store, item information indicating the item details of the products purchased at the store, and number information indicating at least a part of the credit card number used to pay for the products;
a second extraction means for extracting, from the purchase information extracted by the first extraction means, purchase information of a store located in the same area based on an address of the store corresponding to the store identifier;
a storage means for storing the purchase information extracted by the second extraction means as purchase information related to a single user in association with a user identifier that identifies the single user;
A server device comprising: The method further includes estimating a user attribute of the user based on breakdown information included in the purchase information extracted by the second extraction means,
The server device according to claim 1 , wherein the storage means stores the user attribute estimated by the estimation means in association with the user identifier. The server device according to claim 2, wherein the estimation means estimates the user attributes of the user based on setting information that associates a product with the user attributes of a user group that purchases the product. an acquisition means for acquiring user information including information indicating an address of a user who uses the number information together with the number information from an external device;
a specifying means for specifying, from the user identifiers stored in the storage means, a user identifier that meets the conditions of the number information and the address included in the user information acquired by the acquisition means;
Further comprising:
4. The server device according to claim 1, wherein the storage means stores a part or all of the information included in the user information in association with the user identifier identified by the identification means. A collection means for collecting the purchase information from each of the plurality of stores is further provided,
5. The server device according to claim 1, wherein the storage means stores the purchase information collected by the collection means in the storage device. The computer of the server device,
a first extraction means for extracting purchase information having the same number information from a storage device that stores purchase information including a store identifier that is generated for each transaction at a store and is capable of identifying the store, item information indicating the item details of the products purchased at the store, and number information indicating at least a part of the credit card number used to pay for the products;
a second extraction means for extracting, from the purchase information extracted by the first extraction means, purchase information of a store located in the same area based on an address of the store corresponding to the store identifier;
a storage means for storing the purchase information extracted by the second extraction means as purchase information related to a single user in association with a user identifier that identifies the single user;
A program to make it function as such.

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