JP2018032357A - Client analysis server, client analysis method, and client analysis program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a client analysis server, a client analysis method, and a client analysis program capable of executing a client analysis according to a purchase state after purchasing a merchandise and a service.SOLUTION: An input-output part 106 accepts an input of an analysis base date which is a base date for performing a client analysis. A client state determination part 104 determines a client situation using client purchase information stored in purchase information 120 for storing the client purchase information which associates a client purchase information for uniquely identifying the client, a purchase date on which the client purchases the merchandise or the service, and the number of purchase times which is the total number of purchase times of the client. A client purchase information generation part 103 generates the client purchase information applied with the determined client situation. A client number calculation part 105 calculates each of the number of clients of each of clients situation from the generated client purchase information. The input-output part 106 displays each of the number of clients of the calculated client situation for each number of purchase times.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a customer analysis server, a customer analysis method, and a customer analysis program.

  2. Description of the Related Art Conventionally, companies that provide products and services often analyze a customer's purchase history and consider a sales strategy for maximizing the purchase frequency and purchase price of the customer. As an example, customer analysis, such as RFM analysis, is performed in which a segment of excellent customers is found from the purchase history of existing customers on an EC (electronic commerce) site. In addition, a technique for predicting in advance the results of sales strategies according to customer analysis results is also disclosed (see Patent Document 1).

JP 2008-243090 Gazette

  However, the conventional customer analysis technology described above and the future sales strategy result prediction technology described in Patent Document 1 are customer analysis methods based on the result of the customer purchasing goods or services from time to time. There was a problem that it was not possible to analyze the purchase behavior of customers that would be repeated multiple times and to consider and adopt an effective sales strategy.

  The present invention has been made in view of the above, and includes a customer analysis server, a customer analysis method, and a customer analysis program capable of performing customer analysis according to purchase behavior of a customer who purchases a product or service multiple times. The purpose is to provide.

  In order to solve the above-described problems, in the present invention, the input of an analysis reference date, which is a reference date for customer analysis, is accepted, and the customer purchase information and the analysis reference date stored in the customer purchase information storage means are used to determine the customer situation. Generating customer purchase information including the determined customer status, calculating the number of customers for each customer status from the generated customer purchase information, and displaying the calculated number of customers for each customer status for each number of purchases. And

  According to this invention comprised as mentioned above, there exists an effect that the customer analysis according to the purchase behavior of the customer who purchases goods and a service in multiple times can be implemented.

It is a block diagram which shows the structure of the customer analysis system 10 concerning a present Example. It is explanatory drawing which shows an example of a data structure of the purchase history information storage part. It is explanatory drawing which shows an example of a data structure of the customer purchase information storage part. It is explanatory drawing which shows an example of the customer analysis result of a regular purchase. It is explanatory drawing which shows an example of the customer analysis result of all the purchase types. It is a flowchart which shows the customer analysis processing procedure which the customer analysis server 100 performs. It is a flowchart which shows the customer condition determination processing procedure which the customer analysis server 100 performs. It is explanatory drawing which shows a customer purchase information list. It is explanatory drawing which shows the number of customers for every customer condition, and a customer ratio in time series.

  Embodiments of the present invention will be described below with reference to the accompanying drawings. In addition, the following description is an example of embodiment and this invention is not limited to these Examples.

  FIG. 1 is a block diagram illustrating a configuration of a customer analysis system 10 according to the present embodiment. The customer analysis system 10 includes a customer analysis server 100, an EC server 200, and an information terminal device 300. The customer analysis server 100, the EC server 200, and the information terminal device 300, as shown in FIG. To communicate with each other. The network N is a communication network such as the Internet, an intranet, a LAN (Local Area Network), and a mobile communication network.

  The customer analysis server 100 is a server that performs customer analysis based on purchase history information generated every time a customer purchases and pays for a product or service in the EC server 200. The customer analysis server 100 includes a purchase history information storage unit 110, a customer purchase information storage unit 120, a transmission / reception unit 101, a customer identification information generation unit 102, a customer purchase information generation unit 103, a customer situation determination unit 104, A customer number calculation unit 105 and an input / output unit 106 are provided.

  FIG. 2 is an explanatory diagram illustrating an example of a data configuration of the purchase history information storage unit 110. The purchase history information storage unit 110 acquires and stores purchase history information generated at the time of electronic commerce on the EC server 200 from the EC server 200. The purchase history information is received from the EC server 200 via the network N or via a storage medium. The purchase history information storage unit 110 stores purchaser identification information, purchase date, purchase type, purchaser name, telephone number, and other information in association with each other. As other information, a purchase product name, a purchase price, an inflow route, and the like may be stored in association with each other.

  The purchaser identification information here is information for identifying the purchaser at the EC site on the EC server 200, and is, for example, a user ID input by the purchaser at the time of purchase. The purchase date is the date on which the product or service is purchased, and time may be added to the date. A purchase type is a method for a customer to purchase a product or service. A “regular purchase” in which purchases are made repeatedly with a purchase date or purchase interval, a “normal purchase” in which the purchase is made each time, and a “sample” in which a sample is delivered. There is. In addition, the purchaser name, telephone number, etc. entered by the purchaser are stored.

  FIG. 3 is an explanatory diagram illustrating an example of a data configuration of the customer purchase information storage unit 120. The customer purchase information storage unit 120 stores information related to customer purchases used for customer analysis of the customer analysis server 100, generated from purchase history information stored in the purchase history information storage unit 110. The customer purchase information storage unit 120 stores purchaser identification information, purchase date, purchase type, purchaser name, telephone number, customer identification information, number of purchases, and other information in association with each other. . As other information, similarly to the purchase history information storage unit 110, a purchased product name, a purchase price, an inflow route, and the like may be stored in association with each other.

  Here, the customer identification information is information that uniquely identifies a customer in the customer analysis process executed by the customer analysis server 100. The customer identification information may be the same as the purchaser identification information if the purchaser identification information can uniquely identify the customer, and the customer identification information is uniquely identified by using some information that can identify the customer in the purchase history information. Customer identification information may be generated (name identification). The number of purchases is the total number of times that the customer has purchased goods or services. For example, the total number of purchases is calculated by counting customer identification information for each customer purchase type in the customer identification information “UID0011”.

  When the purchase type is included in the purchase history information, the purchase type of the purchase history information is used as it is. However, when there is no item of purchase type in the purchase history information and the distinction between “regular purchase” and “regular purchase” is made based on the presence or absence of the periodic number included in the purchase history information, the customer purchase information generation unit 103 described later The distinction between “regular purchase” and “regular purchase” is determined based on the presence / absence of the periodic number included in the purchase history information. Further, when the purchase type “sample” is determined by the product category included in the purchase history information, the customer purchase information generation unit 103 described later determines the product category.

  The transmission / reception unit 101 transmits / receives data to / from the EC server 200. The transmission / reception unit 101 receives purchase history information generated every time a customer purchases and settles a product or service by the EC server 200 every time the purchase history information is generated or every predetermined period, and the purchase history information storage unit 110 receives the purchase history information. To store.

  The customer identification information generation unit 102 generates customer identification information that uniquely identifies a customer from a combination of information that identifies the customer included in the purchase history information stored in the purchase history information storage unit 110. For example, customer identification information is generated from the customer name and telephone number.

  The customer purchase information generation unit 103 generates customer purchase information using the purchase history information stored in the purchase history information storage unit 110 and the customer identification information generated by the customer identification information generation unit 102. More specifically, the customer purchase information generation unit 103 counts the number of purchases for each purchase type for each customer, generates customer purchase information including the counted number of purchases and customer identification information, and generates a customer purchase information storage unit 120. To store.

  The customer status determination unit 104 determines the customer status for each customer identification information stored in the customer purchase information storage unit 120. The customer status is information indicating a status related to the purchase of the customer. More specifically, the customer status determination unit 104 determines whether or not the customer status is based on whether or not the last purchase date of the customer exceeds a predetermined period from the analysis reference date. Determine. If the last purchase date does not exceed a certain period from the analysis reference date (hereinafter referred to as the withdrawal decision period), the customer status indicates that the withdrawal decision period has not elapsed after the purchase of the product or service, and the purchase of the product or service is made It is determined as “stay” indicating that the customer is not a customer. If the last purchase date has exceeded the withdrawal decision period from the analysis reference date, the customer status indicates that the customer has not purchased the product or service within the withdrawal decision period after purchasing the product or service. Is determined. If the number of purchases is not the final number of purchases, the customer status is determined to be “continuation” indicating that the customer has purchased a product or service after purchasing the product or service. Details will be described later.

  The customer number calculation unit 105 counts customer purchase information in which the customer status for each purchase type is “stay”, “leave”, and “continue”, and calculates the number of customers and the customer ratio for each purchase type. calculate.

  The input / output unit 106 includes an input unit and an output unit. The input unit is an input device and an input control unit such as a keyboard and a mouse. The output unit is an output device and an output control unit such as a display. A device and a control unit such as a touch panel. The output unit displays the calculation result of the customer number calculation unit 105 on the display screen. The input unit accepts input of information related to analysis such as an analysis reference date. Note that the input unit may acquire purchase history information generated by the EC server 200 via a storage medium.

  FIG. 4 is an explanatory diagram showing an example of a customer analysis result of regular purchase, and shows an analysis result of the purchase type “regular purchase”. The number of customers 42 in the display screen example 41 indicates the number of customers who made the purchase “one time (first time)” and the customer ratio, and in this example is 7604 (100%). The number of customers 43 indicates the number of customers with the customer status “stay”, that is, the number of customers whose analysis reference date is within the withdrawal determination period and for which the second regular purchase was not made. The number of customers 44 indicates the number of customers with the customer status “continuation”, that is, the number of customers who have made a second regular purchase. The number of customers 45 indicates the number of customers with the customer status “leave”, that is, the number of customers who did not make a second regular purchase within the leave determination period. It should be noted that the number of customers with the customer status “leave” may be counted only for customers whose subscription has been canceled instead of the number of customers with “leave” described above.

  FIG. 5 is an explanatory diagram showing an example of customer analysis results for all purchase types, and shows calculation results for purchase types “regular purchase”, “normal purchase”, and “sample”. The number of customers 52 in the display screen example 51 indicates the number of customers “7412 (72.4%)” whose purchase type is “regular purchase” for the first time in the purchase period. The number of customers 53 indicates the number of customers whose initial purchase type in the purchase period is “normal purchase”. The number of customers 54 indicates the number of customers whose initial purchase type in the purchase period is “sample”.

  The number of customers 55 indicates the number of customers with the customer status “stay”, that is, the number of customers who did not make a second regular purchase, normal purchase, or withdrawal within the withdrawal determination period. The number of customers 56 indicates the number of customers who made a “regular purchase” after the first regular purchase. The number of customers 57 indicates the number of customers who “normally purchased” after the first normal purchase. The number of customers 58 indicates the number of customers who “leave” after the first normal purchase. 4 and 5 may be displayed as one screen.

  The EC server 200 is a web server that performs electronic commerce with an information terminal device 300 such as a smartphone, a tablet terminal, or a personal computer used by a customer, and generates purchase history information every time a product or service is purchased and settled. And stored in the purchase history information storage unit 210. The EC server 200 is a web server such as a mail order site or an online shopping mall as an example. The transmission / reception unit 201 transmits / receives data to / from the customer analysis server 100 and the information terminal device 300. The transmission / reception unit 201 acquires purchase history information to be analyzed by the customer analysis server 100 from the purchase history information storage unit 210 and transmits the purchase history information to the customer analysis server 100 via the network N. Further, the EC server 200 may write the purchase history information stored in the purchase history information storage unit 210 to the storage medium and deliver it to the customer analysis server 100 via the storage medium.

  A customer analysis process executed by the customer analysis server 100 configured as described above will be described. FIG. 6 is a flowchart showing a customer analysis processing procedure executed by the customer analysis server 100.

  The input / output unit 106 receives input of analysis conditions (step S601). As analysis conditions, an analysis reference date, a withdrawal reference day, a purchase period, a target range, a target product, a target category, a non-target product, an inflow medium, and the like are set.

  Here, the analysis reference date is a date used as a reference when calculating the number of non-purchase days, which is the number of days for which a customer does not purchase goods or services. The number of non-buying days is the number of days in the period from the last purchase date to the analysis reference date. The analysis reference date can be set outside the purchase period and within the purchase period.

  The leaving standard days is the number of days used as a reference for determining whether or not the customer status is “leave”. The purchase period is a condition for determining customer purchase information to be subject to customer analysis, and the customer purchase information whose purchase date is included in the purchase period is the analysis target. The target range is a condition for further narrowing down the analysis target in the customer purchase information of the purchase period. Specifically, either “first time” that targets only the customer who made the initial purchase during the purchase period or “all” that targets customers other than the customer who purchased the first time during the purchase period is selected.

  The target product specifies a target product or service among the products and services purchased by the customer. The target category designates a target product category (product group) and a service category (service group) among products and services purchased by the customer. Non-target products specify products and services that are not targeted among products and services purchased by customers. By specifying or excluding the products, services, product categories, and service categories to be analyzed in this way, more detailed analysis is possible. The analysis target may be specified for each purchase type and for each number of purchases.

  The inflow medium is a route through which the customer flows into the EC site of the EC server 200, and for example, media such as web advertisement A, web advertisement B, and advertisement mail are set. Thereby, the advertising effect for every medium can be analyzed.

  The customer identification information generation unit 102 acquires purchase history information from the purchase history information storage unit 110 (step S602). The customer identification information generation unit 102 generates customer identification information from the purchase history information (step S603). For example, a customer whose purchaser name and telephone number (or address) included in the purchase history information match is regarded as the same customer and is given unique customer identification information within the system. The customer purchase information generation unit 103 counts the number of purchases for each purchase type for each purchase history information (step S604). Note that the number of purchases may be counted by the customer purchase information generation unit 103 or may be used as long as it is stored in the purchase history information generated by the EC server 200. The customer purchase information generation unit 103 generates customer purchase information obtained by adding the customer identification information and the number of purchases for each purchase type to the purchase history information, and stores it in the customer purchase information storage unit 120 (step S605).

  The customer situation determination unit 104 executes a customer situation determination process (step S606). Details will be described later. The number-of-customers calculation unit 105 calculates the number of customers and the customer ratio for each customer status for each purchase type and the number of purchases (step S607). The input / output unit 106 displays the calculation result on the display screen (step S608). As an example, a display screen as shown in FIGS. 4 and 5 is displayed.

  Next, the customer situation determination process in step S606 will be described. FIG. 7 is a flowchart showing a customer situation determination processing procedure executed by the customer analysis server 100.

  The customer situation determination unit 104 acquires customer purchase information from the customer purchase information storage unit 120 (step S701). The customer situation determination unit 104 determines whether or not the customer purchase information is a final purchase (step S702). Specifically, it is determined whether or not the customer purchase information is stored on the purchase date after the purchase date of the target customer purchase information. When it is determined that the customer purchase information is not the final purchase (step S702: No), the customer status is determined to be “continuation” (step S703).

  When it is determined that the customer purchase information is the final purchase (step S702: Yes), the number of days from the analysis reference date to the last purchase date, that is, the number of non-purchase days is calculated (step S704). For example, when the analysis reference date is “July 15, 2016” and the last purchase date is “May 20, 2016”, the number of non-purchased days is calculated as “56 days”. The customer situation determination unit 104 determines whether or not the number of non-purchased days is equal to or greater than the departure standard days (step S705). When it is determined that the number of non-purchased days is equal to or greater than the departure standard days (step S705: Yes), the customer status is determined to be “leave” (step S706). For example, if the number of non-purchased days is “93 days” and the withdrawal standard days is “90 days”, it is determined as “leave”. When it is determined that the number of non-purchased days is not equal to or greater than the departure standard days (step S705: No), the customer status is determined to be “stay” (step S707). For example, when the number of non-purchased days is “56 days” and the reference days for leaving is “90 days”, it is determined as “stay”.

  The customer situation determination unit 104 stores the customer situation as a determination result in the customer purchase information storage unit 120 (step S708). For example, “continuation” is stored in the customer status of the customer purchase information 31 in FIG. The customer situation determination unit 104 determines whether or not all customer purchase information stored in the customer purchase information storage unit 120 has been acquired (step S709). When it is determined that not all customer purchase information has been acquired (step S709: No), the process proceeds to step S701. If it is determined that all customer purchase information has been acquired (step S709: Yes), the process ends.

  In this way, for example, in the purchase type “regular purchase”, the customer status is determined as “continue”, “leave”, or “stay” for each number of purchases. Can be easily grasped and measures can be taken to customers at an appropriate timing.

  In addition, since it is possible to grasp the number of customers and the customer ratio for each purchase status for each purchase type, measures for changing the purchase type, for example, from “regular purchase” to “regular purchase” It is possible to determine when the measure should be implemented.

  As another example, the customer purchase information constituting the number of customers and the customer ratio in FIGS. 4 and 5 is stored in the storage unit in association with the numerical values of the number of customers and the customer ratio. When accepted, the customer purchase information associated with the numerical value is displayed. FIG. 8 is an explanatory diagram showing a list of customer purchase information. In this way, by displaying the customer purchase information constituting the number of customers, it is possible to confirm the real image of each customer for each purchase type and the number of purchases. For example, as customer purchase information, by storing purchase price, purchased product, number of days of final purchase, cumulative number of purchases, cumulative purchase price, mail distribution history acquired from the mail system, etc., more specific information about the customer Can be confirmed.

  As another example, when an instruction to display customer transition is received, the transition of the number of customers for each customer situation and the transition of the customer ratio from the customer purchase information stored in the customer purchase information storage unit 120 in chronological order. indicate. Specifically, from the customer purchase information stored in the customer purchase information storage unit 120, the number of “continue” customers and the number of “leave” customers for each predetermined period (for example, every month) for each purchase type are counted. Create a list. FIG. 9 is an explanatory diagram showing the number of customers and the customer ratio for each customer situation in time series. In this way, by displaying the number of customers and the percentage of customers in a time series, it is possible to confirm whether or not the customer has settled in the regular purchase every predetermined period, and confirm the effect and retention rate of the campaign executed for a limited period. Can do.

  As described above, the EC server 200 is a web server such as a mail-order sales site or an online shopping mall as an example, but as an example of cooperation between the customer analysis server 100 and other systems, sales information on products and services at actual stores is provided. The purchase history information generated by the POS system in cooperation with a POS system (Point Of Sales system) that manages the client may be transmitted to the customer analysis server 100 to execute the customer analysis process.

  In addition to electronic commerce such as mail order sites and online shopping malls, when there are multiple sales channels such as telephone orders, facsimile orders, sales at actual stores, etc., the data of each sales channel is stored in one system (for example, The purchase history information aggregated in the order management system, the backbone system, etc.) may be transmitted to the customer analysis server 100 to execute the customer analysis process.

  Further, by replacing the purchase history information with the shipment data from the warehouse, the shipment history information generated in the warehouse system is transmitted to the customer analysis server 100 in cooperation with the warehouse system that manages the arrival, shipment, and inventory in the warehouse. Customer analysis processing may be performed.

  In addition, it is linked with accounting software that performs financial accounting processing, a system that manages newspaper subscription contracts that assume monthly product purchase contracts, and a dentist reservation system that is expected to purchase multiple services. The purchase history information generated by each system may be transmitted to the customer analysis server 100 to perform customer analysis processing.

  The hardware configuration of the customer analysis server 100 according to the above-described embodiment includes a CPU (Central Processing Unit), an ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), and other external storage devices, communication The computer is a normal computer including a control device and the like, and the above-described configuration and functions are realized by the CPU reading and operating programs stored in the ROM, RAM, HDD, and the like.

  A program that operates on the customer analysis server 100 is stored on a computer connected to a network N such as the Internet, and is provided by being downloaded via the network N, or a file in an installable or executable format. May be recorded and provided on a computer-readable recording medium such as a CD-ROM, a DVD, a USB memory, or an SD card. The program for realizing the functions and processes described above is provided in the form of one function of API (Application Programming Interface), SaaS (Software as a Service), or ASP (Application Service Provider) service in cloud computing. Also good.

  Note that the present invention is not limited to the above-described embodiments as they are, and does not necessarily have to be physically configured as illustrated. In addition, the present invention is configured to functionally or physically divide, integrate, replace, modify, or delete all or a part of the constituent elements described in the embodiments in arbitrary units according to various loads or usage conditions. Can be configured.

DESCRIPTION OF SYMBOLS N ... Network, 10 ... Customer analysis system, 100 ... Customer analysis server, 101 ... Transmission / reception part, 102 ... Customer identification information generation part, 103 ... Customer purchase information generation part, 104 ... Customer status determination part, 105 ... Customer number calculation part 106 ... I / O unit 110 ... Purchase history information storage unit 120 ... Customer purchase information storage unit 200 ... EC server 201 ... Transmission / reception unit 210 ... Purchase history information storage unit 300 ... Information terminal device

In order to solve the above-described problems, in the present invention, the input of an analysis reference date, which is a reference date for customer analysis, is accepted, and the customer purchase information and the analysis reference date stored in the customer purchase information storage means are used to determine the customer situation. and generates customer purchase information plus customer situation determined, resulting calculates the number of customers each customer situation from the customer purchase information, displayed for each calculated number purchased number of customers each customer situation was, customer status Is a continuation that indicates that the customer has purchased a product or service after purchasing the product or service, a customer who has not purchased the product or service for which the withdrawal judgment period has not elapsed, and has not purchased the product or service. A stay, a product or service that indicates that the customer has not purchased the product or service within the withdrawal decision period after purchasing the product or service. Characterized in that Re is or.

Claims (10)

Customer purchase information storage that stores customer purchase information in which customer identification information that uniquely identifies a customer, a purchase date when the customer purchased a product or service, and a purchase count that is the total purchase count of the customer are associated with each other Means,
A reference date receiving means for receiving an input of an analysis reference date, which is a reference date for customer analysis;
Using the customer purchase information stored in the customer purchase information storage means and the analysis reference date, a customer situation determination means for judging a customer situation;
Customer purchase information generation means for generating the customer purchase information to which the customer status determined by the customer status determination means is added;
Customer number calculation means for calculating the number of customers in each of the customer statuses from the customer purchase information generated by the customer purchase information generation means;
Display means for displaying the number of customers of each of the customer statuses calculated by the number of customers calculating means for each number of purchases;
A customer analysis server comprising: The customer purchase information storage means further stores a purchase type indicating a method of purchasing goods or services in association with the customer identification information, and sets the number of purchases as the number of purchase types.
The customer analysis server according to claim 1, wherein the number of customers calculation unit calculates the number of customers for each purchase type.   3. The customer analysis server according to claim 1, wherein the number of customers calculation unit calculates the number of customers from the customer purchase information whose purchase date is within a predetermined period.   4. The customer analysis server according to claim 1, wherein the number of customers calculation unit calculates the number of customers from the customer purchase information of a customer who has made a first purchase within the predetermined period. 5. .   The customer status includes a continuation indicating that the customer has purchased the product or service after purchasing the product or service, the withdrawal judgment period has not elapsed after the purchase of the product or service, and the product or service has been purchased. A stay indicating that the customer is not a customer, or a customer who has not purchased a product or service within the departure judgment period after purchasing a product or service after purchase. Item 5. The customer analysis server according to any one of Items 1 to 4. A customer identification information generating unit that generates the customer identification information from a combination of information that can identify the customer included in the purchase history information generated by the EC server;
The said customer purchase information generation means produces | generates the said customer purchase information which added the said customer identification information produced | generated by the said customer identification information production | generation means, The Claim 1 characterized by the above-mentioned. Customer analysis server. The customer number calculating means stores the number of customers in association with the customer purchase information counted in the number of customers in a storage unit,
The said display means displays the said customer purchase information matched with the said number of customers memorize | stored in the said memory | storage part, when the instruction | indication of the said number of customers is received. The customer analysis server described in one.   When the display means receives an instruction to display customer transition, the transition of the number of customers and the customer ratio for each customer situation is displayed in time series from the customer purchase information stored in the customer purchase information storage means. The customer analysis server according to any one of claims 1 to 7, characterized in that: Customer purchase information storage that stores customer purchase information in which customer identification information that uniquely identifies a customer, a purchase date when the customer purchased a product or service, and a purchase count that is the total purchase count of the customer are associated with each other A customer analysis method executed by a customer analysis server comprising means,
A reference date receiving step for accepting an input of an analysis reference date, which is a reference date for customer analysis;
A customer status determination step for determining customer status using the customer purchase information stored in the customer purchase information storage means and the analysis reference date;
A customer purchase information generation step for generating the customer purchase information including the customer status determined by the customer status determination step;
A customer number calculating step of calculating the number of customers in each of the customer statuses from the customer purchase information generated by the customer purchase information generating step;
A display step of displaying the number of customers of each of the customer statuses calculated by the customer number calculating means for each number of purchases;
A customer analysis method characterized by including: Customer purchase information storage that stores customer purchase information in which customer identification information that uniquely identifies a customer, a purchase date when the customer purchased a product or service, and a purchase count that is the total purchase count of the customer are associated with each other In the customer analysis server with means,
A reference date receiving step for accepting an input of an analysis reference date, which is a reference date for customer analysis;
A customer status determination step for determining customer status using the customer purchase information stored in the customer purchase information storage means and the analysis reference date;
A customer purchase information generation step for generating the customer purchase information including the customer status determined by the customer status determination step;
A customer number calculating step of calculating the number of customers in each of the customer statuses from the customer purchase information generated by the customer purchase information generating step;
A display step of displaying the number of customers of each of the customer statuses calculated by the customer number calculating means for each number of purchases;
A customer analysis program characterized by having

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