JP2002279149A - Complex data creating system and center computer for it - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system enabling a user to dispense with inputting of data on household expenses and a store to offer useful information. SOLUTION: The respective users 201, 201 purchase commodities in respective stores. Store computers 101, 102, 103 of respective stores transmit commodity purchase data for every user to a center computer 1. The center computer 1 returns various marketing information from the purchase commodity for every user to the respective store computers 101, 102, 103. The center computer 1 returns the record of household expense data added by predetermined items by the user to the users 201, 201, etc.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a proposal system based on a product purchase result for each individual, and particularly to a mechanism for collecting comprehensive proposal information.

[0002]

2. Description of the Related Art Japanese Unexamined Patent Application Publication No. 10-275185 discloses an automatic household account book input system for converting purchase product data for each individual entered by a user into household account book data input data, and generating marketing data for a store. A system is disclosed. Specifically, it is as follows.

[0003] When a consumer purchases a product at a store, he refers to the receipt, inputs a purchased product code, and transmits it to the center computer. The center computer accesses the POS database of a predetermined store from the purchased product specifying information, searches for purchased product information corresponding to the purchased product specifying information, and automatically stores the purchased product information (product name, product) in the household account book software. JAVA (registered trademark) for inputting the classification code, price, date and time of sale, etc.)
Send the applet to the consumer's computer. This allows the consumer to receive data entry of the household account book software automatically classified into certain items. on the other hand,
The center computer stores the shopping information for each user together with the data of the attributes of the consumer (for example, age, gender, family composition, general income, etc.), analyzes the consumption trend for each attribute of the consumer, and sells the most popular products. Analysis of information such as the specification of the product, the demand amount of the product, and the demand time. From this, it is possible to grasp the overall sales of a specific product, and from the trends of product attributes such as color, pattern, price, etc. of hot selling products, it is extremely important for manufacturers to predict new products that are likely to become popular and to control production of existing products. Useful information can be obtained.

[0004]

However, the above system has the following problems. The system cannot be used if the user does not have a computer, and the data input process is complicated even if each user has a computer. Further, transmission of marketing data is left to the independence of the user, and in that sense, there is a possibility that accurate marketing information cannot be grasped. Further, the marketing information is marketing information to a manufacturer or a wholesaler, and does not indicate a sales strategy for each dealer.
Therefore, each store does not feel much advantage.

[0005] It is an object of the present invention to solve the above-mentioned problem and to provide a composite data generation system or a method thereof that does not require user input processing and can be expected to provide information from each store.

[0006]

Means for Solving the Problems and Effects of the Invention 1) A composite data creation system according to the present invention acquires product purchase history data for each user ID, creates household account book data for each user, A) The center computer generates marketing information based on product purchase history data for each user. 1) Each store has a unique product ID for identifying its own product and a plurality of stores for each product. A correspondence table with generalized product IDs for common specification of products, and 2) household account book cost item group specifying information for specifying which cost group of the household account book the generalized product ID belongs to for each user. B) Each store computer obtains the correspondence table from the center computer, and when a user purchases a product, Referring to respond table, the purchased merchandise, unique product ID and the generalized product I in its price
D), the user ID is specified and transmitted to the center computer. C) The center computer 1) obtains the user ID from the general-purpose product ID and price for each user given from the store computer. And 2) determining related purchase expected products from the user ID and the purchased unique product ID.

[0007] Therefore, the user has a user ID at each store.
By simply specifying and shopping, purchase data classified into a desired expense group can be obtained. In addition, each store can acquire a related purchase expected product.

[0008] 2) The composite data creation system according to the present invention determines a product purchased by a user having a predetermined attribute as the related purchase expected product based on the user attribute of each user. As described above, by determining the related purchase expected product based on the user attribute, the related purchase expected product can be more reliably predicted.

[0009] 3) The composite data creation system according to the present invention determines the related purchase expected product from products purchased by the user having the predetermined attribute across a plurality of stores. Therefore, it is possible to provide information on products that individual users will purchase at a plurality of stores.

[0010] 4) The composite data creation system according to the present invention makes the above-mentioned proposal at least for a store that stocks a unique product to which the same generalized product ID is assigned. Therefore, there is no need to provide unnecessary information to stores that do not handle products with the same generalized product ID.

[0011] 5) The composite data creation system according to the present invention stores the handling product group specifying information for each store, and determines the store that makes the proposal based on the handling product group specifying information. Therefore, it is possible to appropriately determine a store that makes the proposal.

6) The composite data creation system according to the present invention determines the related purchase expected product from products purchased by a user at a plurality of stores on the same day. Therefore,
It is possible to provide information on products that individual users will purchase on the same day at a plurality of stores.

7) The center computer of the composite data creation system according to the present invention acquires merchandise purchase history data for each user ID, creates household account data for each user, and purchases merchandise for each user. A center computer for a composite data creation system for generating marketing information based on history data, comprising: A)
1) Unique product I for each store to identify its own product for sale
D and a generalized product ID correspondence table for commonly specifying each of the products at a plurality of stores; and 2) for each user, which cost group of the household account book the generalized product ID belongs to The household account book item group identification information to be specified is stored. B) From each store computer, for a product purchased by the user, the product purchase data including the unique product ID and the price of the purchased product specifies the user ID. C) 1) For each user,
Household account book total data for the user is created from the generalized product ID and the price corresponding to the unique product ID, and 2) the user ID and the purchased unique product ID
The related purchase expected product is determined from.

[0014] Therefore, the user has a user ID at each store.
By simply specifying and shopping, purchase data classified into a desired expense group can be obtained. In addition, each store can acquire a related purchase expected product.

[0018] 8) The center computer of the composite data creation system according to the present invention includes, among products purchased by a user across a plurality of stores, products present only in any one of the plurality of stores, A store other than one of the stores is determined as a related purchase expected product. Therefore, it is possible to provide information on products that individual users will purchase at a plurality of stores.

9) In the composite data creation method according to the present invention, product purchase history data is acquired for each user ID,
This is a composite data creation method that creates household account data for each user and generates marketing information based on product purchase history data for each user. A) 1) Each store computer specifies its own sale product And a correspondence table between a unique product ID for general use and a generalized product ID for commonly specifying each of the products at a plurality of stores; and 2) the generalized product ID for each user in any of the expense groups in the household account book. Household account cost item group specifying information for specifying whether or not to belong to is stored in the center computer. B) From each store computer, for the product purchased by the user,
When product purchase data including the unique product ID and the price of the purchased product is specified and given the user ID, the center computer C) 1) for each user, the general-purpose product corresponding to the unique product ID The household account book total data for the user is created from the structured product ID and the price, and 2) a related purchase expected product is determined from the user ID and the purchased unique product ID.

[0017] Therefore, the user has a user ID at each store.
By simply specifying and shopping, purchase data classified into a desired expense group can be obtained. In addition, each store can acquire a related purchase expected product.

In the present specification, the purchase of a product means that
This concept includes receiving services provided on the spot.

[0019]

BEST MODE FOR CARRYING OUT THE INVENTION Outline One embodiment of the present invention will be described with reference to the drawings. FIG. 1 shows an outline of the present system. Each user 201, 201,.
... purchase goods at each store. The store computers 101, 102, 103,... Of each store transmit merchandise purchase data for each user to the center computer 1.
The center computer 1 sends various marketing information from the purchased products for each user to each store computer 101,
102, 103... Also, the center computer 1 sends back the household account data summed up by the users 201, 201,. In this way, the user does not need to perform cumbersome household account data input processing, and the store can provide useful information.

2. Hardware Configuration The hardware configuration of the center computer 1 shown in FIG. 1 will be described with reference to FIG. FIG. 2 is an example of a hardware configuration in which the center computer 1 is configured using a CPU.

The center computer 1 includes a CPU 23, a memory 27, a hard disk 26, a CRT 30, and a CDD.
(CD ROM drive) 25, keyboard 28, mouse 31, network management unit 32, and bus line 29. The CPU 23 controls each unit via a bus line 29 according to each program stored in the hard disk 26.

The hard disk 26 has an operating program (OS) storage unit 26o, a program storage unit 26p, an expense item conversion table storage unit 26c, and a data storage unit 26d. Processing by the program stored in the program storage unit 26p will be described later.

The above program is read from the CD ROM 25a storing the program via the CDD 25 and installed on the hard disk 26.
In addition to the CDROM, a flexible disk (F
D), a program such as an IC card may be installed on a hard disk from a computer-readable recording medium. Furthermore, you may make it download using a communication line.

In this embodiment, the program is stored on a CD.
By installing the program from the ROM to the hard disk 26, the program stored in the CD ROM is indirectly executed by the computer. But,
Without being limited to this, the program stored in the CDROM may be directly executed from the CDD 25. Note that, as a program executable by a computer, not only a program that can be directly executed by simply installing it as it is, but also a program that needs to be temporarily converted into another form (for example, decompresses a data-compressed program) Etc.), and also includes those which can be executed in combination with other module parts.

As shown in FIG. 3, the cost item conversion table storage unit 26c of the hard disk 26 stores, for each store, an individual product code unique to the store and a common code for a plurality of stores. A correspondence table with general-purpose product codes is stored. For example, in the individual product code, "10011 bread xx" specified up to the manufacturer name
However, in the general-purpose product code, the maker name of “D00011 bread” is omitted.

The data storage section 26d has a user database (hereinafter abbreviated as DB), a user setting DB, a detail DB, a sales DB, a regional characteristic DB, a data DB before cost conversion, a data DB after cost conversion, analysis data, and the like.

The user DB stores user attribute data, for example, data such as user ID, address, name, age, gender, family structure, income, and the like for each user.

In the user setting DB, as shown in FIG.
When a household account book is created for each user, an expense code to be summarized is stored. For example, user code 100000
User A of 01 puts the product of the general-purpose product code D0001 * as food expenses, and puts the product of the general-purpose product code D0007 * as food expenses, and User B of the user code 10000002 takes the product of the general product code D0001 *, and General-purpose product code D000
This indicates that 7 * items are to be collected together as food expenses.

Note that d0001 * means that all commodities whose d0001 part matches are specified.

The setting method of the user setting DB will be described with reference to FIG. FIG. 5 shows that the user has i-mode (trademark)
FIG. 9 shows display transition of a screen when a predetermined URL is accessed and set by a terminal or the like.

First, the user accesses a predetermined URL, inputs a user ID and a password, and logs in. As a result, the screen 50 shown in FIG.
1 is transmitted, and an initial screen is displayed on the screen. In this case, the user performs the initial setting, and thus selects “initial setting”. As a result, the screen 505 is transmitted from the center computer and displayed on the screen. The user decides whether to set the expense item as “recommended” or “favorite”,
Choose one. If you select "Recommended",
A screen 507 is displayed in the same manner. When the end button is selected, the setting ends.

On the other hand, when the screen 505 is displayed and "Preference" is selected, the screen 509 is similarly displayed.
Is displayed. When the user selects “daily expenditure” from the pull-down menu from the expense item setting to determine the details, a screen 511 is displayed. Thereafter, by repeating such processing, the desired cost item desired by the user can be freely determined. Thereafter, the cost code constituting each desired cost item may be determined in the same manner.

The user setting DB is not limited to a portable terminal, and a user who has applied in a conventional paper format may be input to the center computer by an operator of the center computer.

The statement DB stores the history of the products purchased for each user. The sales DB stores a history of products sold for each store. The regional characteristics DB blocks the region under certain conditions (for example, by prefecture), and provides economic indicators such as products that sell well in blocks and expenditures per household. These are used as regional economic indicators. I do. It also stores a regional event calendar and climate data.

The data before cost item conversion is data in which sales data (individual code and amount of each product) for each user at each store is added with data represented by a general-purpose product code at each store. The data before cost item conversion is generated at each store and transmitted to the center computer, as described later. The post-conversion-to-cost data is data represented by a general-purpose product code added to each store in the pre-conversion-to-cost data, and is stored for each user.

The store computers 101 and 10 shown in FIG.
The hardware configuration of 2, 103... Will be described with reference to FIG. Store computers 101, 102, ...
The hardware configuration is almost the same as that of the center computer 1. However, the correspondence table between the individual product code and the general-purpose product code specific to the store is downloaded from the center computer to the cost conversion table storage unit 126c of the hard disk 126. And have been remembered. Each store computer uses the table to create expense item converted data as described later.

In the present embodiment, Windows 2000 (trademark) manufactured by Microsoft Corporation is used as the OS program 26o and the OS program 126o.
If the size of the center computer is large, UNI
X (registered trademark), LINUX, or the like may be employed. Further, the processing of the center computer may be distributed to a plurality of computers.

3. Flowchart Next, data processing in the center computer 1 will be described with reference to FIG. Below, user code 10
It is set that the customer A of 000001 manages the food expenses and the eating out expenses as separate items, and the customer B of the user code 10000002 manages the eating out expenses in the food expenses, and the closing dates are both set at the end of the month. In this case, a case where both the customers A and B make a card payment for the following shopping will be described as an example.

(1) 9:40 am on February 1st: at store X
Purchase 5 slices of bread xx (250 yen) and 5 manufacturers' butter (300 yen); (2) 10:00 a.m. on February 1st: Y at Y store
○ Purchase milk (200 yen); (3) 8:30 pm on February 3rd: Eat A dinner set at store Z (5000 yen).

The store computer of store X has previously downloaded the expense conversion table (see FIG. 3) from the center computer, and when customer A makes a card payment, adds a general-purpose product code to the purchased product information. Transmission to the center computer (Step S in FIG. 7)
1). In this case, as the product information, "customer ID, date and time, purchase store, (specific product code; general-purpose product code; product name; price) (specific product code; general-purpose product code; product name; price) ..." Send. As described above, in the present embodiment, when there are a plurality of purchased products in the same store, (unique product code; general-purpose product code; product name; price) is repeated. Specifically, in this case, "user code
10000001, February 1, 9:40 am, X Store, (10011; D0
0011; bread xx; 250 yen) (10021; D00012; butter; 30)
0 yen) is sent.

The center computer specifies the user from the user ID (step S3), and among the received product information, the date, the purchase store, (specific product code; product name; price) (specific product code; product name; price) ) ... is the detail DB
(Additional storage). In this case, user code 10
000001, February 1, 9:40 am, Store X, (10011; bread xx; 250 yen) (10021; @ butter; 300 yen) "is stored.

The center computer collects the received product information for each desired cost item of the user and reflects it in the converted cost item DB (step S7 in FIG. 7). In this case, the purchased product is a product specified by the general-purpose product codes D00011 and D00012, and referring to the user setting DB of the user code 10000001, the product specified by the general-purpose product codes D00011 and D00012 is the expense item “food expenses”. Is set so as to be summarized, so as the total data of the user with the user code 10000001, the sum of the prices of these products is calculated as “(Food cost
550 yen) "is additionally stored.

The center computer specifies the received merchandise information for the store, and specifies and reflects the merchandise in the sales DB with the individual merchandise code (step S9 in FIG. 7). in this case,
As sales data of the X store, "user code 10000001, 2
9:40 am on the 1st of the month, (10011; bread xx; 250 yen) (10
021; ◇◇ butter; 300 yen) is additionally stored.

The center computer analyzes the purchase tendency of the goods from the sales DB, the user DB, and the regional characteristic DB (step S11). The attribute data of the user may be read from the user DB, and the purchase tendency of the user having the specific attribute may be analyzed. For example, the following analysis.

1) □ Manufacturer's 5-piece bread xx is purchased relatively widely except for the elderly. Among them, butter buyers are more likely to be housewives who earn more than 5 million income; 2) butter tends to be purchased in the 30s and 40s, and butter half-size tends to be purchased in the 50s. ; 3) The households that purchase ○○ milk from ○ manufacturers tend to have parents and high school students in their 40s in their age group. 4) The households who purchase ○○ milk from ○ manufacturers are in the evening. There is a tendency to buy it around 4:00 to 6:00.

As described above, the regional characteristic DB includes economic indicators such as products that sell well in blocks and expenditures per household, and can be used as regional economic indicators. You can also refer to local event calendars and climate data.

For example, the following analysis is possible.

1) In families in their thirties and forties, bread and butter are consumed quickly during long vacations such as spring break and summer vacation; 2) Butter buyers are more expensive than ordinary eggs.
3) In this area, junior high school students do not have lunch, so the consumption cycle during the semester is short, but during long holidays the consumption cycle is long; 4) during the semester before the intermediate test. Even without lunch, the egg consumption cycle is short. On the other hand, the bread and butter consumption cycle is almost the same as before, even before the intermediate test.

As described above, based on the customer ID, it is possible to grasp the purchase tendency in consideration of the attributes of the customer.

Similarly, when customer A purchases XX milk (¥ 200) from maker Y at 10:00 am on February 1, the store computer of store Y performs the following processing. . The store computer of store Y downloads the item conversion table (see FIG. 3) of its store from the center computer, and when customer A makes a card payment, adds a general-purpose product code to the purchased product information, The data is transmitted to the computer (step S1 in FIG. 7). In this case, "user code 10000001, February 1 10:00:00
0 minutes, Y store, (38; D00017; XX milk; 200 yen) "is transmitted.

The center computer specifies the user from the user ID (step S3), and among the received product information, the date, the purchase store, (specific product code; product name; price) (specific product code; product name; price) ) ... is the detail DB
(Additional storage). In this case, user code 10
000001, February 1 10:00 am, Store Y, (38;
Milk; 200 yen) is stored.

The center computer collects the received product information for each desired cost item of the user and reflects it in the converted cost item DB (step S7 in FIG. 7). In this case, the purchased product is a product specified by the general-purpose product code D00017, and by referring to the user setting DB of the user code 10000001, the product specified by the general-purpose product code D00017 may be summarized as a cost item “food expenses”. Is set as the total data of these products as the total data of the user with the user code 10000001.
Yen) is additionally stored.

The center computer specifies the store based on the received product information, and specifies and reflects the product by the individual product code in the sales DB (step S9 in FIG. 7). in this case,
As sales data of store Y, “user code 10000001, 2
10:00 am on the 1st of the month, (38; XX milk; 200 yen) "is additionally stored.

The center computer analyzes the purchase tendency of the goods from the sales DB, the user DB and the regional characteristic DB (step S11). For example, the purchaser of the □ manufacturer's 5 slices of bread xx and △ butter is ○ manufacturer's ○
○ It is analyzed that the tendency to purchase milk is high.

In the same manner, the customer A receives the request at 8:03 pm on February 3.
When eating out the A dinner set at the Z store at 0 minute (5000 yen), the store computer of the Z store performs the following processing. The store computer of store Z downloads the cost item conversion table of its store from the center computer, and when customer A makes a card payment, adds a general-purpose product code to the purchased product information and sends it to the center computer ( FIG. 7 step S1). In this case, "user code 10000001, February 3, 8:30 pm, Z store, (E
D201; D00077; A dinner set; 5000 yen) "is transmitted.

The center computer specifies the user from the user ID (step S3), and among the received product information, the user code 10000001, February 3, 8:30 pm
Minutes, Z store, (ED201; A dinner set; 5000 yen) "is stored in the statement DB (step S5).

The center computer collects the received merchandise information for each desired cost item of the user and reflects it in the cost item converted DB (step S7 in FIG. 7). In this case, the purchased product is a product specified by the general-purpose product code D00077, and by referring to the user setting DB of the user code 10000001, the product specified by the general-purpose product code D00077 may be summarized as a cost item “eating cost”. Is set as the total data of these products as total data for the user with user code 10000001,
Yen) is additionally stored.

The center computer specifies the received merchandise information for the store, and specifies and reflects the merchandise in the sales DB with the individual merchandise code (step S9 in FIG. 7). in this case,
As Z store and sales data, "user code 10000001, 2
8:30 pm on March 3, (ED201; A dinner set; 500
0 yen) "is additionally stored.

The center computer analyzes the product purchase tendency from the sales DB, the user DB, and the regional characteristic DB (step S11). For example, A dinner set is 2
It is analyzed that there is a tendency to be preferred by men in their 0s.

Similarly, for user B, (1)
February 1: 9:40 am: At store X, □ 5 slices of bread xx (¥ 250) from maker and ◇◇ butter from manufacturer (3
(2) 10:00 am on February 1st: Y
Buy maker's milk (200 yen) at the shop; (3) 2
8:30 pm on March 3rd: Based on purchase data of eating out A dinner set at store Z (5000 yen), statement DB,
The data is reflected in the post-consumption item conversion DB and the sales DB, and an analysis process is performed.

It should be noted that for the user B, the cost item converted D
When reflecting on B, the product specified by the general-purpose product code D00077 refers to the user setting DB of the user code 10000001, and the product specified by the general-purpose product code D00077 is set to be grouped as an expense item “meal expenses”. As the total data of the user with the user code 10000001, the sum of the prices of these products was calculated as "(Food cost 5000 yen)"
Is additionally stored in the expense item “meal expenses”.

Next, an order management process for a store computer will be described with reference to FIG. The center computer stores the order management set time for each store computer in the hard disk 26, and determines whether or not the time is reached at any store. At that time,
The order management processing of FIG. 8 starts. The center computer requests the store computer that manages the order to transmit the inventory data (step S21 in FIG. 8).
Upon receiving such a request, the store computer transmits the store arrangement number and the stock number for each individual product to the center computer (step S23). The center computer reads the analysis result processed in step S11 in FIG. 7 (step S25). It is determined whether or not there is a product that is expected to be short of the number of store locations (step S27). For example, today is before the intermediate test, and based on the analysis result that the egg consumption cycle is short, if the number of eggs arranged in the store is small, it may be determined that there is a missing product. In addition, since the product K1 is purchased at a certain store, there is a high possibility that the product K2, which is a related purchase expected product, will be purchased. In this case, the center computer transmits an instruction to increase the number of stores arranged (step S29). The store computer displays such an instruction (step S35).

If it is determined in step S27 that there is no missing product, it is determined whether there is a product that requires order processing (step S31). This is because it is determined that there is a product that requires order processing not only when the stock quantity is equal to or less than a predetermined amount but also when the purchase is predicted from the analysis result. For example, since a product K3 is purchased at a certain store, a product K4 that is a related purchase expected product
Is highly likely to be purchased, and order processing of the product K2 is necessary. If there is such a product, the center computer transmits order prompting data (step S33). The store computer displays such an instruction (step S35).

In this way, the store computer can obtain order processing information based on the analysis result in consideration of the user attributes.

Further, in the present system, a product which the user has purchased in a plurality of stores is predicted as a related purchase predicted product, and a store which sells only one of the related purchase predicted products is provided. Then, the store computer provides the store computer with proposal information as to whether or not the product should be stocked as a sale product. Hereinafter, description will be made with reference to FIG.

Further, the center computer repeats the processing of FIG. 9 every predetermined time. The center computer reads the analysis result processed in step S11 in FIG. 7 (step S41). It is determined whether there is proposal information that can be provided to any of the stores (step S43). In the present embodiment, a related purchase expected product is adopted as the proposal information. For example, if there is an analysis that the purchaser of the maker's 5-piece sliced bread xx and the △ butter is more likely to purchase the maker's XX milk, the □ manufacturer's 5-piece sliced bread xx xx, △ butter, メ ー milk from メ ー manufacturers will be related purchase expected products. If there is proposal information, the center computer specifies the store to be proposed and transmits the proposal information (step S45). In the present embodiment, a general-purpose product group is registered as selling a general-purpose product code for each store, and a store to be proposed is specified from such group information. The store computer displays such an instruction (step S4).
7).

When the user has purchased such related purchase expected products at a plurality of stores, it is particularly difficult to grasp this. However, by specifying a purchased product for each user and performing an analysis based on the user attributes as in the present embodiment, it is possible to grasp such a related purchased expected product.

If there is no proposal information in step S43, the process ends.

In the present embodiment, it is determined whether or not to make a proposal from the group information. Therefore, it is also conceivable to transmit, as proposal information, the presence of such a related purchase expected product even at a store where no such related purchase expected product is stocked. Therefore, at least stores that sell any of the related purchase expected products may be limited.

[0070] The stores that provide the information include stores that sell products with the same general-purpose product code,
A store that sells the same unique product or a store that was purchased on the same day may be selected regardless of the type of business.

Next, household account book data sent to each user will be described with reference to FIG. The detail data of the center computer stores the detail data, and the post-conversion item DB stores the total data for each user (FIG. 10).
A, see FIG. 10B). When the closing date of each user is reached, the center computer transmits such detailed data and total data to the user. As a transmission method, you may send the printed out by fax or mail,
A mail may be sent to an address specified by the user. Alternatively, as shown in FIG. 5, when reference is selected from the initial screen 501, the total information may be displayed.

As can be seen from FIGS. 10A and 10B, even when the same shopping is performed by the user A and the user B, the data after summing up the cost items is different because the cost items to be summarized in advance are different. Specifically, the user A has a general-purpose product code d0.
This is because 007 * is counted as the meal cost, but the user B collects the general-purpose product code d0007 * like other food items and counts as the meal cost.

As described above, in the present system, the user can receive household account book data, and each store can receive inventory management information and various kinds of provided information only by shopping with a card. Therefore, it is expected that the user can use the card for shopping.
Membership of each store can be expected. Thereby, more accurate information according to the user attribute can be provided. Also,
The household account data is totaled at a cost item according to each user's request. As a result, many users can acquire household account data at an expense item that is not irritable.

4. Other Embodiment In the above embodiment, the conversion table for the store is transmitted to the store computer in advance, and a general-purpose product code is added to the conversion table and transmitted to the center computer.
However, the center computer may acquire the general-purpose product code from the conversion table. In this case, the data before cost item conversion is sales data for each user in each store (individual code and amount of each product)
When transmitted from each store computer to the center computer, the center computer generates data after conversion of the cost item represented by the general-purpose product code.

Further, in the above embodiment, the case of making a card payment has been described, but the point is that it is sufficient to specify the user ID and purchase the product. Similarly, the present invention can be similarly applied to settlement by a debit card or the like.

In the present embodiment, the functions shown in FIG. 1 are realized by using a CPU and software. However, part or all of it,
It may be realized by hardware such as a logic circuit.

Note that a part of the processing of the program may be performed by an operating system (OS).

[Brief description of the drawings]

FIG. 1 is a diagram showing an overall outline.

FIG. 2 is a diagram illustrating an example of a hardware configuration in which the center computer 1 illustrated in FIG. 1 is implemented using a CPU.

FIG. 3 shows a data structure of an expense item conversion table.

FIG. 4 shows an example of a user setting DB.

FIG. 5 is a diagram illustrating a setting procedure of a user setting DB.

FIG. 6 is a diagram illustrating an example of a hardware configuration in which a store computer is implemented using a CPU.

FIG. 7 is a data processing flowchart from a purchased product.

FIG. 8 is a flowchart of an order management process.

FIG. 9 is a flowchart of a provided information determination process.

FIG. 10 is an example of detailed data and total data.

[Explanation of symbols]

 23: CPU 27: Memory

Claims (10)

[Claims] 1. A composite data creation system for acquiring merchandise purchase history data for each user ID, creating household account data for each user, and generating marketing information based on the merchandise purchase history data for each user. The center computer includes: 1) a correspondence table of a unique product ID for each store to specify its own product for sale and a generalized product ID for common specification of each product at a plurality of stores; and ) Stores household account cost item group specifying information for specifying to which item group of the household account book the general-purpose product ID belongs to each user, and each store computer acquires the correspondence table from a center computer. In addition, when the user purchases the product, the unique product ID and the purchased product are referenced with reference to the correspondence table. And the price is given the general-purpose product ID, and the user ID is specified and transmitted to the center computer. The center computer 1) the general-purpose product ID for each user given from each of the store computers In addition to creating household account book total data for the user from the price and the price, 2) the user ID and the purchased unique product I
Determining a related purchase expected product from D; 2. The composite data creation system according to claim 1, wherein a product purchased by a user having a predetermined attribute is determined as the related purchase expected product based on a user attribute of each user. . 3. The composite data creation system according to claim 2, wherein the related purchase expected product is determined from products purchased by the user having the predetermined attribute across a plurality of stores. 4. The composite data creation system according to claim 2, wherein said proposal is made at least to a store that stocks a unique product to which the same generalized product ID is assigned. 5. The composite data creation system according to claim 2, wherein the handling product group specifying information for each store is stored.
Determining a store that makes the proposal based on the handled product group specifying information. 6. The composite data creation system according to claim 1, wherein a user purchases goods at a plurality of stores on the same day from a plurality of stores.
Determining the related purchase expected product. 7. A composite data creation system for acquiring merchandise purchase history data for each user ID, creating household account data for each user, and generating marketing information based on the merchandise purchase history data for each user. A center computer, 1) a unique product I for each store to identify its own product for sale
D and a generalized product ID correspondence table for commonly specifying each of the products at a plurality of stores; and 2) for each user, which cost group of the household account book the generalized product ID belongs to The household account expense item group identification information to be specified is stored, and from each store computer, for the product purchased by the user, for the purchased product, the product purchase data including the unique product ID and the price specifies the user ID. When given, 1) for each user, the household account book total data for the user is created from the generalized product ID and the price corresponding to the unique product ID, and 2) the user ID and the purchased unique product ID Determining a related purchase expected product from the center computer of the complex data creation system. 8. The center computer of the composite data creation system according to claim 7, wherein, among the products purchased by a user across a plurality of stores,
A product that exists only in any one of the plurality of stores is determined as a related purchase expected product in a store other than the one of the stores. 9. A composite data creation method for acquiring merchandise purchase history data for each user ID, creating household account data for each user, and generating marketing information based on the merchandise purchase history data for each user. 1) The center computer has a correspondence table between a unique product ID for specifying a product for sale at each store and a generalized product ID for common specification of each product at a plurality of stores; and Household account book cost item group specifying information for specifying which item group of the household account book the generalized product ID belongs to for each user is stored, and from each store computer, the product purchased by the user is purchased. When a user ID is specified and given to a product purchase data including a unique product ID and the price of the product, the center computer , 1) for each user, the generalized product I corresponding to the unique product ID
D and the price to create household account book total data for the user, and 2) determine a related purchase expected product from the user ID and the purchased unique product ID. 10. A computer which acquires merchandise purchase history data for each user ID, creates household account data for each user, and generates marketing information based on the merchandise purchase history data for each user. A program for functioning as a creation computer, including the following steps: 1) Each store has a unique product I for identifying its own product for sale.
D and a generalized product ID correspondence table for commonly specifying each of the products at a plurality of stores; and 2) which cost group of the household account book the generalized product ID belongs to for each user. The household account book cost item group identification information to be specified is stored, and from each store computer, for the product purchased by the user, for the purchased product, the product purchase data including the unique product ID and the price specifies the user ID. When given, 1) for each user, household account book total data is created for the user from the generalized product ID and price corresponding to the unique product ID, and 2) the user ID and the purchased unique product ID A computer-readable program, wherein the related purchase expected product is determined from.