Server device, program, and transaction history collection method

Abstract

To provide a server device, a program, and a transaction history collection method which can collect the history of transaction including information on a customer.SOLUTION: A server device includes update means, acquisition means, first estimation means, and first generation means. The update means updates a purchase statistics master in which scores for each attribute of a customer having purchased a commodity are registered for each of the commodities, on the basis of commodity sales information in transaction information and attribute information. The acquisition means acquires the transaction information. The first estimation means estimates attribute information indicating the attribute of the customer by the commodity sales information in the transaction information acquired by the acquisition means, on the basis of the purchase statistics master. The first generation means generates estimation transaction history information indicating that the customer of the attribute indicated by the attribute information estimated by the first estimation means has purchased the commodity included in the commodity sales information in the transaction information acquired by the acquisition means.SELECTED DRAWING: Figure 11

Description

Technical Field

[0001] Embodiments of the present invention relate to a server device, a program, and a transaction history collection method.

Background Art

[0002] Conventionally, a transaction management system collects transaction information indicating the content of transactions conducted at a retail store or the like. Based on the transaction information collected by the transaction management system, an administrator analyzes what kind of customers are purchasing what kind of products, etc. The analysis results serve as important indicators for marketing activities. Therefore, it is preferable that the transaction information includes information about customers, such as the age and gender of the customers.

[0003] However, in recent years, strict handling of personal information has been required. Therefore, it has become difficult to collect transaction histories that include information about customers.

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problem to be solved by the present invention is to provide a server device, a program, and a transaction history collection method capable of collecting transaction histories including information about customers.

Means for Solving the Problems

[0005] The server device according to the embodiment includes an update unit, an acquisition unit, a first estimation unit, and a first generation unit. Output means and When the transaction information including product sales information indicating products sold to a customer includes attribute information indicating the attributes of the customer, based on the product sales information and the attribute information included in the transaction information, quotient purchase the product The attributes of each were aggregated. The score is Each productThe registered purchase statistics master is updated. The acquisition means acquires transaction information including product sales information indicating products sold to customers. The first estimation means estimates attribute information indicating customer attributes based on the purchase statistics master and the product sales information of the transaction information acquired by the acquisition means. The first generation means generates estimated transaction history information indicating that the products included in the product sales information of the transaction information acquired by the acquisition means were purchased by a customer with attributes indicated by the attribute information estimated by the first estimation means. The output means outputs the estimated transaction history information generated by the first generation means. [Brief explanation of the drawing]

[0006] [Figure 1] Figure 1 is an explanatory diagram illustrating an example of the configuration of the transaction management system according to this embodiment. [Figure 2] Figure 2 shows an example of the data structure of simple transaction information. [Figure 3] Figure 3 shows an example of the data structure of identified transaction information. [Figure 4] Figure 4 shows an example of a data device for detailed transaction information. [Figure 5] Figure 5 shows an example of the hardware configuration of the management server. [Figure 6] Figure 6 shows an example of the data structure of the store master. [Figure 7] Figure 7 shows an example of the data structure of a customer identification master by product. [Figure 8] Figure 8 shows an example of the data structure of the purchasing statistics master. [Figure 9] Figure 9 shows an example of the data structure of a customer characteristics master. [Figure 10] Figure 10 shows an example of the data structure of estimated transaction history information. [Figure 11] Figure 11 is a block diagram showing an example of a characteristic functional configuration of a management server. [Figure 12] Figure 12 is a flowchart showing an example of output processing performed by the management server according to this embodiment. [Modes for carrying out the invention]

[0007] The following describes in detail embodiments of the server device, program, and transaction history collection method with reference to the attached drawings. Note that the embodiments described below are just one example of the server device, program, and transaction history collection method, and do not limit their configuration or specifications. The server device in this embodiment is, for example, an example of application to a management server 30 that manages the transaction management system 1.

[0008] Figure 1 is an explanatory diagram illustrating an example of the configuration of the transaction management system 1 according to this embodiment. The transaction management system 1 comprises multiple POS (Point of Sales) terminals 10, multiple store servers 20, and a management server 30. The POS terminals 10 and the store servers 20 are connected to each other via a store network or the like. The store servers 20 and the management server 30 are also connected to each other via a network.

[0009] POS terminal 10 is a sales data processing device installed in retail stores and other locations. More specifically, POS terminal 10 performs product registration processing to register products to be sold, and accounting processing for products registered through product registration processing. POS terminal 10 may also acquire customer identification information by reading membership cards or the like to identify customers. Furthermore, POS terminal 10 generates transaction information indicating the details of the transaction based on the product registration processing and accounting processing. Finally, POS terminal 10 transmits the transaction information to the store server 20.

[0010] Furthermore, the POS terminal 10 may be a fully self-service type device in which the customer operates both the product registration process and the accounting process. In a semi-self-service system in which a store employee operates the product registration process and the customer operates the accounting process, the POS terminal 10 may be either a registration device or an accounting device. In a self-scanning system in which the customer operates a customer-owned mobile device or a rental mobile device provided by the store, and the customer operates an accounting device, the POS terminal 10 may be a customer-owned mobile device, a rental mobile device, or an accounting device.

[0011] The store server 20 manages the POS terminals 10 installed in the store. The store server 20 is an information processing device such as a personal computer or cloud computing. Furthermore, the store server 20 is not limited to a single information processing device, but may be composed of multiple information processing devices. When a transaction takes place with a customer in the store, the store server 20 transmits the transaction information to the management server 30.

[0012] The management server 30 is a server device such as a personal computer or a cloud computing device. Furthermore, the management server 30 is not limited to a single server device; it may be composed of multiple server devices. The management server 30 collects transaction information from multiple store servers 20 connected via a network.

[0013] Here, transaction information is classified into simple transaction information, identified transaction information, and detailed transaction information. Figure 2 shows an example of the data structure of simple transaction information. Simple transaction information includes a transaction code and product sales information. The transaction code is identification information used to identify a transaction. Product sales information is product information for the goods sold in the transaction. Product information includes information about the goods purchased by the customer, such as the product code, product name, and unit price. The product code is identification information used to identify a product. The product name is information indicating the name of the product. The unit price is information indicating the unit price of the product.

[0014] FIG. 3 is a diagram showing an example of the data configuration of identification transaction information. The identification transaction information has a customer code, a transaction code, and product sales information. The customer code is identification information for identifying a customer, and is information indicating a customer who purchased a product in a transaction.

[0015] FIG. 4 is a diagram showing an example of a data device for detailed transaction information. The detailed transaction information has a customer code, customer information, a transaction code, and product sales information. The customer information is information regarding a customer who purchased a product in a transaction. The customer information has attribute information and customer characteristic information. The attribute information is information indicating attributes of a customer, such as the gender and age of the customer. The purchase characteristic information is information indicating the purchase characteristics of a customer. For example, the purchase characteristic information is household composition information indicating the household composition of a customer, purchase tendency information indicating the tendency of products purchased by the customer, and the like.

[0016] Also, the management server 30 estimates information regarding a customer based on the collected transaction information. Then, the management server 30 generates a database including the transaction information and the estimated information regarding the customer.

[0017] Next, the hardware configuration of the management server 30 will be described.

[0018] FIG. 5 is a diagram showing an example of the hardware configuration of the management server 30. The management server 30 includes a control unit 310, a storage unit 320, a communication unit 330, a display unit 340, and an operation unit 350. These units are interconnected via a system bus 360 such as a data bus and an address bus.

[0019] The control unit 310 is a computer that controls the overall operation of the management server 30 and implements the various functions of the management server 30. The control unit 310 comprises a processor, ROM (Read Only Memory), and RAM (Random Access Memory). The processor is a processing circuit that controls the operation of the management server 30, such as the CPU (Central Processing Unit). ROM is a storage medium that stores various programs and data. RAM is a storage medium that temporarily stores various programs and data. The processor then uses RAM as a work area to execute programs stored in ROM or the storage unit 320, etc.

[0020] The storage unit 320 is a storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive). The storage unit 320 stores the control program 321, transaction information master 322, product master 323, store master 324, product-specific customer determination master 325, purchase statistics master 326, customer details master 327, and estimated transaction history master 328. Note that all or part of the transaction information master 322, product master 323, store master 324, product-specific customer determination master 325, purchase statistics master 326, customer details master 327, and estimated transaction history master 328 may be stored on a device other than the management server 30.

[0021] The control program 321 is a program that enables the operation system and the management server 30 to perform their functions. The control program 321 includes a program that enables the characteristic functions of this embodiment.

[0022] The transaction information master 322 is a database that stores transaction information transmitted from multiple store servers 20.

[0023] Product Master 323 holds information about multiple products, including information about each individual product. Product Master 323 associates information such as product code, GP code, department code, class code, category code, and category name. The product code is identification information used to identify a product. The GP (group) code indicates the group to which the product belongs. The department code indicates the department to which the product belongs. The class code indicates the class to which the product belongs. The category code indicates the category of the product. The category name is the name that indicates the category of the product.

[0024] Figure 6 shows an example of the data structure of the store master 324. The store master 324 contains information for each individual store. The store master 324 also includes a purchasing customer classification that indicates whether the person who purchases a product and the person who uses the product are often the same.

[0025] For example, store master 324 contains information such as company code, region (major category), region (medium category), prefecture, region (minor category), city / ward / town / village, company name, trade name, store code, store name, business type, business hours, location category, purchasing customer category, and transaction information category.

[0026] The company code is identification information used to identify the company operating the store. The region (broad division), region (medium division), prefecture, region (minor division), and municipality are information indicating the location of the store. Specifically, the region (broad division) is information indicating the broad area in which the store is located. The region (medium division) is information indicating the medium-sized area in which the store is located. The prefecture is information indicating the prefecture in which the store is located. The region (minor division) is information indicating the medium-sized area in which the store is located. The municipality information indicates the city, town, or village where the store is located.

[0027] The company name is information indicating the name of the company that operates the store. The store name is a group name used for multiple stores. The store code is identification information used to identify a store. The store name is the name that identifies an individual store. The business type is information indicating the type of business the store operates. For example, the business type may be a convenience store, supermarket, drug store, etc. The business hours are information indicating the hours the store is open. The location classification is information indicating the area in which the store is located. For example, the location classification may be a residential area, in front of a train station, in an office district, in the suburbs, in a commercial area, or as a tenant.

[0028] The purchasing customer classification is a classification that shows the relationship between the customer who purchases the product at the store and the person who uses the product. For example, at a convenience store, the customer purchases the product for their own use. At a supermarket, the customer purchases the product for their family to use. The purchasing customer classification is a classification that shows this kind of relationship. The classification can be categorized as match, mismatch, or unknown. Match indicates that the customer who purchases the product at the store and the person who uses the product are the same. Mismatch indicates that the customer who purchases the product at the store and the person who uses the product are different. Unknown indicates that it is unclear whether there is a match or a mismatch. The transaction information classification is information that shows the classification of product information transmitted from the store server 20. In other words, the transaction information classification is information that shows whether the store server 20 transmits simple transaction information, identified transaction information, or detailed transaction information.

[0029] Figure 7 shows an example of the data structure of the product-specific customer identification master 325. The product-specific customer identification master 325 is information that registers the purchasing characteristics of customers who have purchased each product. The product-specific customer identification master 325 associates a company code, product identification information, judgment conditions, and judgment results. The management server 30 determines that a customer has the purchasing characteristics shown in the judgment result when a product identified by the product identification information is purchased from a company identified by the company code, and the conditions shown in the judgment conditions are met.

[0030] The company code is identification information that identifies the company operating the store. Product identification information is information used to identify a product. For example, product identification information may include a company code, GP code, department code, class code, product code, and product name. The GP code is information that indicates the group to which the product belongs. The department code is identification information that indicates the department to which the product belongs. The class code is identification information that indicates the class to which the product belongs. The product code is identification information used to identify a product. The product code may be unique to each store or may be identification information used in multiple stores. The product name is the name of the product.

[0031] The judgment criteria are the conditions for whether or not a customer's purchasing characteristics are met. For example, the judgment criteria may include price and quantity. Price is the condition for the price of the product. Quantity is the condition for the number of items in the product. The judgment result is the customer's purchasing characteristics when the judgment criteria are met. For example, the judgment result may include household composition and purchasing tendency. Household composition is the customer's household composition. For example, household composition may include multi-person households, single-person households, etc. Also, household composition is not limited to multi-person households or single-person households; it may include households with children, three-generation households, or indicate the number of people, such as a family of three. Purchasing tendency is the customer's tendency to purchase products. For example, purchasing tendency may include "bargain," "preference," "convenience," "luxury goods," etc.

[0032] Figure 8 shows an example of the data structure of the Purchase Statistics Master 326. The Purchase Statistics Master 326 is information in which attribute-specific scores of customers who purchased each product are registered. The Purchase Statistics Master 326 associates product identification information, target flags, and customer attribute scores. Product identification information is information used to identify the target product. Product identification information includes a product code, department code, GP code, and product name. The product code is identification information used to identify a product. The department code is identification information indicating the department to which the product belongs. The GP code is information indicating the group to which the product belongs. The product name is the name of the product.

[0033] The target flag indicates whether the associated product is a target product. The customer attribute score indicates the score for each attribute of the customer who purchased the associated product. For example, the customer attribute score includes total gender, total age group, age group for women, and age group for men. Total gender is the score for each gender. Total age group is the score for each age group, without distinction by gender. Age group for women is the score for each age group of women. Age group for men is the score for each age group of men. The customer attribute score is counted up according to the attributes of the customer who purchased the associated product. For example, if the management server 30 obtains detailed transaction information indicating that a customer with the product name "AAA" purchased 3 units, it will count up 3 each for "Male" in the total gender, "30s" in the total age group, and "30s" for men associated with the product name "AAA". Also, "Unknown Age Group" indicates the number of times the customer's age group is unknown made a purchase. In this way, the customer attribute score indicates the number of times customers with each attribute have made a purchase. Furthermore, customer attribute scores are not limited to total gender, total age group, age group for women, and age group for men; they may also include scores for other attributes, and may not include any of the total gender, total age group, age group for women, and age group for men.

[0034] Figure 9 shows an example of the data structure of the Customer Details Master 327. The Customer Details Master 327 is a database containing customer attributes and characteristics. The Customer Details Master 327 is an example of a customer master. The Customer Details Master 327 associates company code, customer code, master attributes, estimated attributes, household composition, and purchase tendency score. The company code is identification information that indicates the company operating the store that sold the product to the customer. The customer code is identification information used to identify a customer.

[0035] Master attributes are information that indicates customer attributes obtained from detailed transaction information. Estimated attributes are information that indicates estimated customer attributes. For example, estimated attributes are estimated based on product sales information contained in the identifying transaction information and the purchase statistics master 326.

[0036] Household composition is information that indicates the estimated household composition of an associated customer. For example, household composition may be registered as either "single person" indicating a single-person household or "multiple people" indicating a multi-person household. For example, household composition is estimated based on the product sales information contained in the identification transaction information and the product-specific customer determination master 325. The customer with customer code "123456" shown in Figure 9 indicates that the customer is "single person". Note that household composition is not limited to single person or multiple people; it may also include "with children" indicating the presence of children, or "three generations" indicating the presence of relatives within two degrees of kinship, etc.

[0037] The purchase tendency score is a score of the purchase tendencies of an associated customer. For example, the purchase tendency score is calculated by counting items corresponding to the products purchased by the associated customer. As shown in Figure 9, the customer with customer code "123456" has purchased 91 "convenient" products, 130 "premium" products, 5 "value" products, and 31 "luxury" products, according to the purchase tendency score.

[0038] Figure 10 shows an example of the data structure of the estimated transaction history master 328. The estimated transaction history master 328 is a database where estimated transaction history information is stored. Estimated transaction history information is information that estimates a portion of the information about customers who have conducted transactions. Estimated transaction history information includes transaction store information, customer details information, and target product information.

[0039] Transaction store information refers to information about the store where the transaction took place. For example, transaction store information may include information such as business type, transaction date and time, region (major category), region (medium category), prefecture, region (minor category), and location conditions. Note that the transaction store information shown in Figure 10 is just an example, and the store does not have to have all of this information, and may have other information as well.

[0040] Customer information refers to information about customers who have conducted transactions. For example, customer information may include information such as gender, age, household composition, and purchasing trends. Note that the customer information shown in Figure 10 is just an example, and a company does not need to have all of this information, nor does it need to have other types of information.

[0041] The target product information is information about the products that are the subject of the transaction information. For example, the target product information may include information such as category code, category name, product code, product name, unit price, and number of items traded. Note that the target product information shown in Figure 10 is just an example, and it is not necessary to have all of this information, or to have other information as well.

[0042] The communication unit 330 is an interface that performs communication with external devices via a network. For example, the communication unit 330 performs communication with the store server 20.

[0043] The display unit 340 is a display device that displays various images. For example, the display unit 340 is a liquid crystal display.

[0044] The control unit 350 is an input device such as a keyboard, mouse, or touch panel that accepts various operations.

[0045] Next, we will describe the characteristic functions of each device provided by the management server 30.

[0046] Figure 11 is a block diagram showing an example of the characteristic functional configuration of the management server 30. The control unit 310 of the management server 30 loads the control program 321 of the storage unit 320 into RAM and operates according to the control program 321 to generate each of the functional units shown in Figure 11 on RAM. Specifically, the control unit 310 of the management server 30 includes, as functional units, a transaction information acquisition unit 3101, a store master registration unit 3102, a customer detail master registration unit 3103, a purchase statistics update unit 3104, a customer attribute estimation unit 3105, a customer characteristic estimation unit 3106, an estimated transaction history generation unit 3107, and an estimated transaction history output unit 3108.

[0047] The transaction information acquisition unit 3101 acquires transaction information, including product sales information indicating the products sold to customers. The transaction information acquisition unit 3101 is an example of an acquisition method. More specifically, the transaction information acquisition unit 3101 receives transaction information from multiple store servers 20. The transaction information acquisition unit 3101 also registers the received transaction information in the transaction information master 322.

[0048] The store master registration unit 3102 registers the item details for each item in the store master 324. More specifically, the store master registration unit 3102 registers the following items from the store master 324 as shown in Figure 6: region (major category), region (medium category), prefecture, region (minor category), city / ward / town / village, company name, trade name, store code, store name, business type, business hours, location category, purchasing customer category, and transaction information category. For example, the store master registration unit 3102 registers the content specified by an administrator of the management server 30 or other operator.

[0049] The customer details master registration unit 3103 registers the item contents for each item in the product-specific customer determination master 325. More specifically, the customer details master registration unit 3103 registers the company code, each item of product identification information, each item of determination conditions, and each item of determination result in the product-specific customer determination master 325 shown in Figure 7.

[0050] The purchase statistics update unit 3104 updates the purchase statistics master 326, which registers attribute-specific scores for customers who purchased each product, based on the product sales information and attribute information contained in the transaction information, when the transaction information, which includes product sales information indicating products sold to a customer, also includes attribute information indicating customer attributes. The purchase statistics update unit 3104 is an example of an update method. More specifically, the purchase statistics update unit 3104 updates the customer attribute scores in the purchase statistics master 326 when the transaction information acquired by the transaction information acquisition unit 3101 is detailed transaction information. The purchase statistics update unit 3104 increases the value of the customer attribute score item that matches the product code included in the product sales information of the detailed transaction information and the attribute information included in the detailed transaction information by a value corresponding to the number of items purchased.

[0051] The customer attribute estimation unit 3105 estimates attribute information indicating customer attributes based on the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, using the purchase statistics master 326, which contains attribute-specific scores for customers who have purchased each product. The customer attribute estimation unit 3105 is an example of the first estimation means.

[0052] More specifically, if the transaction information acquired by the transaction information acquisition unit 3101 is detailed transaction information, the customer attribute estimation unit 3105 registers the attribute information contained in the detailed transaction information into the master attributes of the customer detail master 327.

[0053] The customer attribute estimation unit 3105 estimates customer attributes based on the product sales information contained in the identified transaction information or simple transaction information, and the purchase statistics master 326, if the transaction information acquired by the transaction information acquisition unit 3101 is identified transaction information or simple transaction information. The customer attribute estimation unit 3105 extracts product codes from the product sales information. If the target flag of the product identified by the extracted product code in the purchase statistics master 326 indicates that it is an estimated target, the customer attribute estimation unit 3105 estimates gender and age as customer attributes. For example, the customer attribute estimation unit 3105 estimates that the gender is the one with the higher customer attribute score among the genders of the customer attributes in the purchase statistics master 326. The customer attribute estimation unit 3105 also estimates that the age is the one with the highest customer attribute score among the ages of the customer attributes in the purchase statistics master 326. Then, the customer attribute estimation unit 3105 performs the above processing for each product code included in the product sales information.

[0054] Furthermore, product sales information may have multiple product codes. In this case, the customer attribute estimation unit 3105 estimates attribute information by aggregating it for each product included in the product sales information of the transaction information, based on the customer attribute score, which is a score for each customer attribute registered for each product in the purchase statistics master 326. That is, the customer attribute estimation unit 3105 estimates gender and age as customer attributes using statistical methods. For example, if the product sales information has three product codes that are estimated to be male and two product codes that are estimated to be female, the customer attribute estimation unit 3105 will estimate the customer to be male. Note that the customer attribute estimation unit 3105 may estimate customer attributes by other methods, not limited to the number of product codes. The customer attribute estimation unit 3105 then registers the attribute information indicating the estimated customer attributes in the estimated attributes of the customer details master 327.

[0055] Furthermore, the customer attribute estimation unit 3105 may estimate customer attributes based on some product codes included in the product sales information. For example, if the product sales information includes product codes of products that serve as indicators for estimating customer attributes, the customer attribute estimation unit 3105 may estimate customer attributes based on gender and age estimated for the product codes of the indicator products.

[0056] The customer characteristic estimation unit 3106 estimates the customer's purchasing characteristics from the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, based on the product-specific customer determination master 325, which contains registered purchasing characteristics of customers who have purchased each product. The customer characteristic estimation unit 3106 is an example of a second estimation means.

[0057] More specifically, the customer characteristic estimation unit 3106 estimates that the household composition matches the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, based on the product-specific customer determination master 325, which contains the household composition of customers who purchased each product. In other words, the customer characteristic estimation unit 3106 compares the product sales information of the transaction information with the product-specific customer determination master 325 and extracts product codes that satisfy the determination conditions. Then, the customer characteristic estimation unit 3106 estimates that the household composition of the target customer is associated with the extracted product code.

[0058] Furthermore, if the customer characteristic estimation unit 3106 extracts multiple product codes that satisfy the determination criteria, it estimates the customer's household composition using statistical methods. For example, if there are multiple single-person households and multiple multi-person households, the customer characteristic estimation unit 3106 determines that the household belongs to the category with the larger number of product codes that satisfy the determination criteria. The customer characteristic estimation unit 3106 then registers the estimation result in the customer detail master 327.

[0059] Furthermore, the customer characteristic estimation unit 3106 estimates purchasing trends based on the product-specific customer determination master 325, which registers the purchasing tendencies of customers who have purchased each product, and the product sales information of the transaction information acquired by the transaction information acquisition unit 3101. Specifically, the customer characteristic estimation unit 3106 determines whether each product code included in the product sales information of the transaction information satisfies the determination conditions for each purchasing trend registered in the product master 323. The customer characteristic estimation unit 3106 then counts the number of product codes that satisfy the determination conditions for each type of purchasing trend. The customer characteristic estimation unit 3106 then aggregates the number of product codes for products that fit each of the purchasing trend types: "bargain," "preference," "convenience," and "luxury goods." Finally, the customer characteristic estimation unit 3106 adds the number of product codes for each type of purchasing trend to the customer detail master 327 as a purchasing trend score.

[0060] In this way, the customer characteristic estimation unit 3106 registers the estimation results in the product master 323. In other words, the customer characteristic estimation unit 3106 generates a customer detail master 327 that has either the attribute information included in the transaction information or the attribute information estimated by the customer attribute estimation unit 3105, and the customer's purchasing characteristics estimated by the customer characteristic estimation unit 3106. The customer characteristic estimation unit 3106 is an example of a second generation means.

[0061] The estimated transaction history generation unit 3107 generates estimated transaction history information indicating that a customer with attributes indicated by the attribute information estimated by the customer attribute estimation unit 3105 purchased a product included in the product sales information of the transaction information acquired by the transaction information acquisition unit 3101. The estimated transaction history generation unit 3107 is an example of the first generation means. That is, the estimated transaction history generation unit 3107 generates estimated transaction history information indicating that a customer with attributes indicated by the attribute information estimated by the customer attribute estimation unit 3105 purchased a product included in the product sales information of the transaction information acquired by the transaction information acquisition unit 3101.

[0062] Furthermore, the estimated transaction history generation unit 3107 may generate estimated transaction history information indicating that a customer possessing attributes indicated by attribute information estimated by the customer attribute estimation unit 3105 and purchase characteristics estimated by the customer characteristic estimation unit 3106 purchased a product included in the product sales information of the transaction information acquired by the transaction information acquisition unit 3101.

[0063] Furthermore, the estimated transaction history generation unit 3107 may generate estimated transaction history information indicating that a customer with attributes indicated by the attribute information estimated by the customer attribute estimation unit 3105 purchased a product from a store in a purchasing customer classification that shows whether the product purchaser and the product user are often the same person.

[0064] More specifically, the estimated transaction history generation unit 3107 generates estimated transaction history information, which is a history of transactions that estimates a portion of the customer information in the transaction information, based on the product master 323, store master 324, product-specific customer determination master 325, purchase statistics master 326, and customer detail master 327. The estimated transaction history generation unit 3107 then registers the generated estimated transaction history information in the estimated transaction history master 328, which is a database. The estimated transaction history generation unit 3107 is an example of a registration means.

[0065] The estimated transaction history output unit 3108 outputs the estimated transaction history information generated by the estimated transaction history generation unit 3107. More specifically, the estimated transaction history output unit 3108 extracts estimated transaction history information from the estimated transaction history master 328. Then, the estimated transaction history output unit 3108 outputs the extracted estimated transaction history information. For example, the estimated transaction history output unit 3108 transmits it to another device via a network. Note that the estimated transaction history output unit 3108 may output the information not only by transmission, but also by storing it on another storage medium, by printing it, or by other methods.

[0066] Furthermore, the estimated transaction history output unit 3108 may accept the specification of conditions for the estimated transaction history information to be output from the estimated transaction history information held by the estimated transaction history master 328. For example, the estimated transaction history output unit 3108 may accept the specification of one or more items of the estimated transaction history information as output conditions. For example, the estimated transaction history output unit 3108 may accept the specification of "supermarket" as the business type. In this case, the estimated transaction history output unit 3108 will output estimated transaction history information for business types that are "supermarkets".

[0067] Next, the output processing performed by the management server 30 will be described. Here, Figure 12 is a flowchart showing an example of the output processing performed by the management server 30 according to this embodiment.

[0068] The transaction information acquisition unit 3101 determines whether or not it has received transaction information from the store server 20 (step S1). If it has not received transaction information (step S1; No), the transaction information acquisition unit 3101 waits.

[0069] If transaction information is received (Step S1; Yes), the transaction information acquisition unit 3101 registers the received transaction information in the transaction information master 322 (Step S2).

[0070] The transaction information acquisition unit 3101 determines whether or not detailed transaction information has been registered in the transaction information master 322 (step S3). That is, the transaction information acquisition unit 3101 determines whether or not the transaction information registered in the transaction information master 322 includes both the customer code and customer information.

[0071] If detailed transaction information is registered (Step S3; Yes), the purchase statistics update unit 3104 updates the customer attribute score in the product-specific customer determination master 325 based on the detailed transaction information (Step S4). More specifically, the customer attribute estimation unit 3105 counts up the items that match the customer attribute score based on the product code of the product sales information included in the detailed transaction information and the attribute information included in the detailed transaction information.

[0072] The customer characteristic estimation unit 3106 registers various information in the customer detail master 327 based on the detailed transaction information (step S5). Specifically, the customer characteristic estimation unit 3106 registers the attribute information contained in the detailed transaction information as a master attribute in the customer detail master 327. The customer characteristic estimation unit 3106 also registers the estimated household composition in the customer detail master 327 based on the product sales information contained in the detailed transaction information and the product-specific customer determination master 325. Furthermore, the customer characteristic estimation unit 3106 registers the estimated purchase tendency score in the customer detail master 327 based on the product sales information contained in the detailed transaction information and the product-specific customer determination master 325.

[0073] The estimated transaction history generation unit 3107 registers the estimated transaction history information in the estimated transaction history master 328 (step S6). Specifically, the estimated transaction history generation unit 3107 obtains transaction store information from the store master 324, indicating the store of the store server 20 that sent the detailed transaction information. The estimated transaction history generation unit 3107 also obtains master attributes associated with the customer code contained in the detailed transaction information, household composition, and the purchase tendency with the highest score among the purchase tendency scores from the customer detail master 327. The estimated transaction history generation unit 3107 also obtains information associated with the product code contained in the product sales information contained in the detailed transaction information from the product master 323. Then, the estimated transaction history generation unit 3107 registers the estimated transaction history information generated using the obtained information in the estimated transaction history master 328.

[0074] If detailed transaction information has not been registered (Step S3; No), the transaction information acquisition unit 3101 determines whether or not identification transaction information has been registered in the transaction information master 322 (Step S7). That is, the transaction information acquisition unit 3101 determines whether or not customer information is not included in the transaction information registered in the transaction information master 322, and whether or not a customer code is included.

[0075] If the identified transaction information is registered (Step S7; Yes), the customer characteristic estimation unit 3106 registers various information in the customer detail master 327 based on the identified transaction information (Step S8). Specifically, the customer characteristic estimation unit 3106 registers the estimated customer attributes in the estimated attributes of the customer detail master 327 based on the customer attribute score in the product-specific customer determination master 325 and the product code included in the product sales information of the identified transaction information. The customer characteristic estimation unit 3106 also registers the estimated household composition in the customer detail master 327 based on the product sales information of the identified transaction information and the product-specific customer determination master 325. Furthermore, the customer characteristic estimation unit 3106 registers the estimated purchase tendency score in the customer detail master 327 based on the product sales information of the identified transaction information and the product-specific customer determination master 325.

[0076] The estimated transaction history generation unit 3107 registers the estimated transaction history information in the estimated transaction history master 328 (step S9). Specifically, the estimated transaction history generation unit 3107 obtains transaction store information from the store master 324, indicating the store of the store server 20 that transmitted the identified transaction information. The estimated transaction history generation unit 3107 also obtains estimated attributes associated with the customer code contained in the identified transaction information, household composition, and the purchase tendency with the highest score among the purchase tendency scores from the customer detail master 327. The estimated transaction history generation unit 3107 also obtains information associated with the product code contained in the product sales information contained in the identified transaction information from the product master 323. Then, the estimated transaction history generation unit 3107 registers the estimated transaction history information generated using the obtained information in the estimated transaction history master 328.

[0077] If no identified transaction information is registered (Step S7; No), the estimated transaction history generation unit 3107 registers estimated transaction history information in the estimated transaction history master 328 (Step S10). Here, if no identified transaction information is registered in the transaction information master 322, the transaction information acquisition unit 3101 registers simple transaction information in the transaction information master 322 that does not include either customer information or a customer code. Therefore, the estimated transaction history generation unit 3107 acquires transaction store information from the store master 324 that indicates the store of the store server 20 that sent the simple transaction information. The estimated transaction history generation unit 3107 also acquires gender, age group, household composition, and purchasing tendencies based on the product sales information contained in the simple transaction information and the product-specific customer determination master 325. The estimated transaction history generation unit 3107 also acquires information associated with the product code included in the product sales information contained in the simple transaction information from the product master 323. Then, the estimated transaction history generation unit 3107 registers the estimated transaction history information generated using the acquired information in the estimated transaction history master 328.

[0078] The estimated transaction history output unit 3108 determines whether or not it has received an operation to output estimated transaction history information (step S11). If it has not received an operation to output (step S11; No), the estimated transaction history output unit 3108 proceeds to step S1.

[0079] If the system accepts an operation to output (step S11; Yes), the estimated transaction history output unit 3108 outputs the estimated transaction history (step S12).

[0080] Based on the above, the management server 30 terminates the output processing.

[0081] As described above, when the management server 30 according to this embodiment acquires detailed transaction information, it updates the purchase statistics master 326, which registers attribute-specific scores for customers who purchased each product, based on the product sales information and attribute information contained in the transaction information. Furthermore, when the management server 30 acquires transaction information, it estimates the customer's attributes based on the product sales information of the transaction information, using the purchase statistics master 326. The management server 30 then generates estimated transaction history information indicating that the products included in the product sales information of the transaction information were purchased by customers with the attributes indicated by the estimated attribute information. Thus, the management server 30 can collect transaction history including information about customers.

[0082] Furthermore, the customer attribute estimation unit 3105 estimates attribute information by aggregating it for each product included in the product sales information of the transaction information, based on the customer attribute score, which is a score for each customer attribute registered for each product in the purchase statistics master 326. Therefore, the management server 30 can estimate customer attributes even if the transaction information does not contain attribute information indicating customer attributes. Consequently, the management server 30 can generate estimated transaction history information including the estimated customer attributes, even if the transaction information does not contain attribute information indicating customer attributes.

[0083] Furthermore, the customer characteristic estimation unit 3106 estimates the customer's purchase characteristics from the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, based on the product-specific customer determination master 325, which registers the purchase characteristics of customers who have purchased each product. In addition, the estimated transaction history generation unit 3107 generates estimated transaction history information indicating that the products included in the product sales information of the transaction information acquired by the transaction information acquisition unit 3101 were purchased by a customer whose attributes are indicated by the attribute information estimated by the customer attribute estimation unit 3105 and whose purchase characteristics are estimated by the customer characteristic estimation unit 3106. Thus, the management server 30 can estimate the customer's purchase characteristics and generate estimated transaction history information that includes the estimated customer's purchase characteristics.

[0084] Furthermore, the customer characteristic estimation unit 3106 estimates that the household composition of a customer matches the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, based on the product-specific customer determination master 325, which contains the household composition of customers who purchased each product. Therefore, the management server 30 can estimate the customer's household composition as a characteristic of the customer's purchase. Consequently, the management server 30 can generate estimated transaction history information that includes the estimated customer's household composition.

[0085] Furthermore, the customer characteristic estimation unit 3106 estimates that the household composition matches the product sales information of the transaction information acquired by the transaction information acquisition unit 3101, based on the product-specific customer determination master 325, which contains the household composition of customers who have purchased each product. Therefore, the management server 30 can estimate the purchasing trends that indicate the tendency of a customer to purchase products, categorized by product characteristics such as "convenience," "preference," "value," and "luxury goods." Consequently, the management server 30 can generate estimated transaction history information that includes the estimated purchasing trends of the customer.

[0086] The customer characteristic estimation unit 3106 generates a customer detail master 327 which includes either the attribute information included in the transaction information or the attribute information estimated by the customer attribute estimation unit 3105, and the customer's purchasing characteristics estimated by the customer characteristic estimation unit 3106. Therefore, even if the transaction information does not include attribute information, the management server 30 can generate estimated transaction history information including attribute information and customer purchasing characteristics based on the generated customer detail master 327. Furthermore, by generating the customer detail master 327 in advance, the management server 30 can generate estimated transaction history information more easily than when estimating attribute information and customer purchasing characteristics each time estimated transaction history information is generated.

[0087] Furthermore, the estimated transaction history generation unit 3107 generates estimated transaction history information indicating that a product included in the product sales information of the transaction information acquired by the transaction information acquisition unit 3101 was purchased by a customer with attributes indicated by the attribute information estimated by the customer attribute estimation unit 3105 at a store classified as a purchasing customer classification that indicates whether the purchaser and the user of the product are often the same person.Therefore, the management server 30 can generate estimated transaction history information that includes a purchasing customer classification that indicates whether the purchaser and the user of the product are often the same person.As such, when using the estimated transaction history information for marketing purposes, it is possible to identify whether the product was purchased by the customer indicated by the estimated transaction history information according to their own preferences.

[0088] Furthermore, the estimated transaction history generation unit 3107 registers the generated estimated transaction history information in the estimated transaction history master database 328. Therefore, the management server 30 can store estimated transaction history information. Consequently, the management server 30 can generate data for statistical analysis in marketing and other applications.

[0089] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents.

[0090] The programs executed in each of the above embodiments and modified devices shall be provided pre-installed in the storage medium (ROM or storage unit) provided in each device, but are not limited to this. For example, the programs may be configured to be provided as installable or executable files recorded on a computer-readable recording medium such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk). Furthermore, the storage medium is not limited to a medium independent of the computer or embedded system, but also includes storage media that store or temporarily store programs downloaded from a LAN, the Internet, etc.

[0091] Furthermore, the programs executed by each of the above embodiments and modified devices may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network, or they may be provided or distributed via a network such as the Internet. [Explanation of symbols]

[0092] 1. Transaction Management System 10 POS (Point of Sale) terminals 20 Store Servers 30 Management Server 310 Control Unit 320 Storage section 321 Control Program 322 Transaction Information Master 323 Product Master 324 Store Master 325 Product-Specific Customer Identification Master 326 Purchase Statistics Master 327 Customer Details Master 328 Estimated Transaction History Master 330 Communications Department 340 Display section 350 Operation section 360 System Bus 3101 Transaction Information Acquisition Department 3102 Store Master Registration Department 3103 Customer Details Master Registration Department 3104 Purchasing Statistics Update Department 3105 Customer attribute estimation section 3106 Customer Characteristics Estimation Department 3107 Estimated Transaction History Generation Unit 3108 Estimated Transaction History Output Unit [Prior art documents] [Patent Documents]

[0093] [Patent Document 1] Japanese Patent Publication No. 2016-118975

Claims

1. When transaction information, which includes product sales information indicating products sold to a customer, also includes attribute information indicating customer attributes, an update means updates a purchase statistics master in which a score is registered for each product, based on the product sales information and attribute information contained in the transaction information, which aggregates the attributes of each customer who purchased the product. A means for acquiring transaction information, including product sales information that shows the products sold to customers, Based on the purchase statistics master, a first estimation means estimates attribute information indicating customer attributes using the product sales information of the transaction information acquired by the acquisition means, A first generation means generates estimated transaction history information indicating that a customer with attributes indicated by the attribute information estimated by the first estimation means purchased the product included in the product sales information of the transaction information acquired by the acquisition means, An output means for outputting the estimated transaction history information generated by the first generation means, A server device equipped with the following features.

2. The first estimation means estimates the attribute information by aggregating the scores of each customer attribute registered for each product in the purchase statistics master for each product, for each product included in the product sales information of the transaction information. The server device according to claim 1.

3. The system further includes a second estimation means that estimates the customer's purchasing characteristics from the product sales information of the transaction information acquired by the acquisition means, based on a product-specific customer determination master in which the purchasing characteristics of customers who purchased the product are registered for each product. The first generation means generates estimated transaction history information indicating that a customer having the attributes indicated by the attribute information estimated by the first estimation means and the purchase characteristics estimated by the second estimation means purchased the product included in the product sales information of the transaction information acquired by the acquisition means. The server device according to claim 1 or 2.

4. The second estimation means estimates, based on the product-specific customer determination master in which the household composition of customers who purchased the product is registered for each product, that the household composition matches the product sales information of the transaction information acquired by the acquisition means. The server device according to claim 3.

5. The second estimation means estimates purchasing trends based on the product-specific customer determination master, which registers the purchasing tendencies of customers who have purchased the product for each product, and the product sales information of the transaction information acquired by the acquisition means. The server device according to claim 3 or claim 4.

6. The system includes a second generation means for generating a customer master having either the attribute information included in the transaction information or the attribute information estimated by the first estimation means, and the customer's purchasing characteristics estimated by the second estimation means. A server device according to any one of claims 3 to 5.

7. The system further includes a store master with a customer classification that indicates whether the purchaser of a product and the user of that product are often the same person. The first generation means generates estimated transaction history information indicating that the products included in the product sales information of the transaction information acquired by the acquisition means were purchased by a customer with attributes indicated by the attribute information estimated by the first estimation means at a store of the purchasing customer classification. A server device according to any one of claims 1 to 6.

8. The system further comprises a registration means for registering the estimated transaction history information generated by the first generation means into a database. A server device according to any one of claims 1 to 7.

9. Computers, When transaction information, which includes product sales information indicating products sold to a customer, also includes attribute information indicating customer attributes, an update means updates a purchase statistics master in which a score is registered for each product, based on the product sales information and attribute information contained in the transaction information, which aggregates the attributes of each customer who purchased the product. A means for acquiring transaction information, including product sales information that shows the products sold to customers, Based on the purchase statistics master, a first estimation means estimates attribute information indicating customer attributes using the product sales information of the transaction information acquired by the acquisition means, A first generation means generates estimated transaction history information indicating that a customer with attributes indicated by the attribute information estimated by the first estimation means purchased the product included in the product sales information of the transaction information acquired by the acquisition means, An output means for outputting the estimated transaction history information generated by the first generation means, A program to make it work.

10. When transaction information, which includes product sales information indicating products sold to a customer, also includes attribute information indicating customer attributes, an update step updates the purchase statistics master, which is registered for each product, based on the product sales information and attribute information contained in the transaction information, by aggregating the scores of each attribute of the customer who purchased the product. A step to acquire transaction information, including product sales information that shows the products sold to the customer, Based on the aforementioned purchase statistics master, a first estimation step is performed to estimate attribute information indicating customer attributes using the product sales information of the transaction information acquired in the acquisition step, A first generation step generates estimated transaction history information indicating that the products included in the product sales information of the transaction information acquired in the acquisition step were purchased by a customer with attributes indicated by the attribute information estimated in the first estimation step, An output step which outputs the estimated transaction history information generated in the first generation step, A method for collecting transaction history performed by a server device.

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