JP2006309280A - System for analyzing purchase behavior of customer in store using noncontact ic tag - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system capable of collecting inclusively and automatically a customer characteristic, a purchase behavior of a customer in a store, customer purchase information and the like, and capable of analyzing the pieces of information to grasp a detail of the purchase behavior of the customer. <P>SOLUTION: In this system of analyzing the purchase behavior of the customer, the detail purchase behavior including a moving direction of the customer and a moving speed thereof are grasped by a system with noncontact type IC tags 102 attached to shopping carts 110 and cages, with IC tag readers 103 arranged with an equal interval in a floor in the store, and for measuring reception information from the plurality of IC tag readers and time serial transition of a reception level. Customer characteristic information such as an age and the distinction of sex of the customer is also automatically acquired to be correlated with the IC tag information of the cart and the cage used by the customer. A high level of analysis is thereby possible for grasping the purchase behavior a customer class by a customer class of a target, for display thereof, for grasping an article preference tendency, and for the like. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a technique for acquiring analysis data and managing / utilizing analysis data for analyzing customer purchase behavior in a store.

  Conventionally, as a technique for registering, managing and utilizing customer purchase behavior data in a customer purchase behavior analysis processing device, for example, those described in Patent Literature 1 and Patent Literature 2 below are known.

  The thing of the following patent document 1 attaches an IC tag reader to the cart which a customer uses when purchasing a product, and attaches a plurality of IC tags to a product display shelf in the store, so that the IC tag in the vicinity This is a technology that reads and collects outgoing information with an IC tag reader of the cart, analyzes it with an analysis means, and systematically grasps the purchase behavior of the customer, such as the trajectory followed by the buyer. In addition, immediately after receiving the received data, the data is transmitted to the analysis unit, so that the location of the purchaser at the time of reception is grasped, and the residence time of the purchaser near each IC tag is calculated. Thereby, it is possible to grasp the flow line and the purchaser's movement status.

Moreover, the thing of the following patent document 2 is that the customer carries an IC card and receives the ID of the IC card by a plurality of receiving devices in the store and receiving devices installed at the entrance / exit. This is a technology for grasping information related to purchase behavior such as a travel route in a store of a customer, a staying time in the store, and a purchase history.
JP 2000-357177 A JP 2003-16243 A

  Conventionally, it has been common to manually grasp the purchase behavior of customers. For example, an observer follows the customer who has entered the store, and manually records the customer's travel route, the purchased product, the product that he / she did not purchase, but which he thought he was interested in. So, he grasped the purchase behavior of customers. In addition, surveillance video cameras are arranged at various locations in the store, and the inside of the store is shot and recorded, and after shooting, the person in charge checks the moving route of the customer while watching this recorded video, Analyzing behavior. However, with these methods, it is necessary to make subjective judgments by manually observing the purchasing behavior of each customer individually, which requires a great deal of labor and time, and the judgment is ambiguous. There were drawbacks.

  In order to solve this problem, the techniques described in Patent Document 1 and Patent Document 2, for example, have automated information collection and information analysis. However, with the techniques described in Patent Document 1 and Patent Document 2, it is impossible to grasp the detailed behavior of the customer. For example, when a customer passes through a certain area of the store, the route and time can be grasped, but the speed at which the customer passes while looking at the display shelf on the left and right cannot be grasped. There is a problem.

  Also, in analyzing customer purchasing behavior, it is important to relate to the characteristics of the customer, such as age and gender. However, as in Patent Document 1, the customer only needs to attach the IC tag reader to the cart. I cannot understand the characteristics. In addition, in the method of giving the IC card to the customer himself as in the above-mentioned Patent Document 2, there is a possibility of instilling a sense of resistance that the customer always observes at the same time that there is a leak due to forgetting to carry the IC card. There is a problem.

  Furthermore, in Patent Document 1 and Patent Document 2 described above, the analysis technology focuses on purchasing behavior of a specific customer. For example, a customer who satisfies a specific condition such as the preference of a man in his 30s. No mention is made of the analysis of the set as a whole.

  The purpose of the present invention is to collect customer characteristics, in-store customer behavior status, customer purchase information, etc. comprehensively and automatically. It is to provide a system to grasp.

  In order to achieve the above object, the present invention attaches an IC tag to a cart or a basket, and installs an IC tag reader at a predetermined interval on the floor in the store, and reads the ID of the IC tag with the IC tag reader. By analyzing the radio field intensity at that time, the position of the IC tag is obtained, and from the IC tag position information obtained in time series, the route the customer moves, the moving speed of the customer, the direction the customer is facing It is characterized by measuring. In particular, by using customer information reading means, customer characteristic information such as age and gender is automatically collected and stored in association with the corresponding IC tag. In addition, the analysis device re-aggregates and displays the analysis results under certain specific conditions, which area in the store is popular in a certain customer segment, and which products do not lead to purchase It provides advanced analysis functions such as whether you are interested in things, what products are selling well, what time the store visits often, and how much customers are in the special sales corner.

  In addition, by giving stock status to the POS database and automatically updating the number of stocks in the POS database at the time of purchase, it is possible to perform inventory transitions on the analysis server, which allows instructions for additional goods receipt or inventory. It can be used to consider the removal / replacement of the product itself when it is slow.

  According to the present invention, by examining the display status of the customer purchase behavior analysis result obtained by the analysis device, it becomes possible to grasp the purchase behavior of each customer in real time, and the conventional manual purchase behavior can be grasped. In comparison, the labor and cost can be greatly reduced. At the same time, the suspicious behavior of the customer can be monitored, and it can be applied to a crime prevention use.

  In addition, the advanced analysis function of customer purchase behavior obtained by the analysis device makes it possible to grasp the purchase behavior of a certain customer group. For example, the store reexamination plan for product display shelves and the layout plan for special sales corners. It can be used as an objective material for planning to increase sales. In particular, in large supermarkets and discount stores, it is often the case that it is difficult to personally understand the purchasing behavior of each customer, and such a system seems to exert its maximum effect.

  Hereinafter, an embodiment for carrying out the present invention will be specifically described with reference to the drawings.

  FIG. 1 is a schematic diagram showing a configuration of a customer purchase behavior analysis system according to an embodiment of the present invention. In the figure, 101 is a shopping cart, 102 is an IC tag installed in the shopping cart 101, 104 is a floor in the store, 103 is an IC tag reader installed on the floor 104 at equal intervals, 105 is a cashier corner, 106 is A register installed in the cashier corner 105, 107 is an analysis server, 108 is an IC tag information receiving antenna that wirelessly receives information from the IC tag reader 103, 109 is a VPN Internet line, and 110 is an analysis client PC .

  The analysis server 107 includes a customer purchase behavior analysis system 111, a product position DB (database) 112, an analysis DB 113, and a POS DB 114. The product position DB 112 is a DB that links the positional relationship between each product and the product display shelf on which it is displayed. The analysis DB 113 is a DB that stores information from the IC tag reader 103. The POS DB 114 is a DB that stores POS data such as product information, product price, and product inventory status. The analysis system client PC 110 is a PC intended to be used for visually displaying the customer purchase behavior analysis result analyzed by the analysis server 107. The analysis system client PC 110 and the customer purchase behavior analysis system 111 are connected by a VPN Internet line 109, for example. Thereby, the analysis system client PC 110 can be arranged in a remote place. Note that a plurality of IC tag information receiving antennas 108 may be arranged in order to reliably receive from all of the plurality of IC tag readers 103.

  FIG. 2 shows an arrangement example of the IC tag reader 103 on the floor 104. Reference numerals 201 to 207 correspond to the IC tag reader 103 in FIG. The IC tag readers 201 to 207 form a hexagonal honeycomb structure so as to be arranged at equal intervals (1 m) from adjacent IC tag readers. Here, arbitrary IC tag information (102 in FIG. 1) is received by, for example, the nearest IC tag reader 201, and simultaneously received by the adjacent IC tag readers 202 to 207. By simultaneously measuring the radio wave intensity levels of the received information, it is possible to grasp the accurate position information of the cart 101 to which the IC tag 102 is attached at a certain point in time, and also to measure the moving speed and moving direction. .

  FIG. 3A is a conceptual diagram of a customer purchase behavior grasp map in the store. A cart 301 is placed in the cart storage 303. The customer enters from the entrance / exit 308, picks up the cart 301, and starts shopping. 301 'shows the cart which the customer is using for shopping. The cart 301 ′ is provided with an IC tag 310. When a customer takes the cart 301 ′ and starts shopping, the customer information reading camera system 302 takes a picture of the customer, and acquires customer information of the customer (age, gender, family / single family, etc.) from the image. To the analysis server 107. A rectangle indicated by 304 (and a similar rectangle in the sales floor) indicates a merchandise display shelf. A hatched rectangle (and a similar rectangle in the sales floor) 305 indicates an IC tag reader installed on the floor. The customer of the cart 301 ′ arbitrarily moves in the sales floor to make a purchase. At that time, the IC tag 310 ID is sequentially received by the IC tag reader 305 near the cart 301 ′ and analyzed. The purchase behavior line 311 of the customer can be acquired. 306 is a cash register corner, 307 is a cash register, and 309 is an emergency exit.

  FIG. 3-2 shows an example of an analysis image displayed on the analysis system client PC 110. As shown in the figure, when a specific condition is specified, regarding a set of customers that match that condition, there are product shelves that those customers seem to be interested in, areas where the time required to pass (residence time) was large, etc. It can be displayed. Here, the analysis image is shown when the condition is specified that the sex of the customer is male, the age is 30s, and the time zone is 16: 00-20: 00. Reference numerals 321 and 322 denote areas where it took a long time for a customer satisfying this condition to pass. Accordingly, it can be determined that the merchandise display shelves 323 to 326 are placed with merchandise that is of interest to customers who satisfy the above conditions. On the other hand, reference numerals 327 and 328 denote areas where a customer who satisfies the above conditions took less time to pass. Thereby, it can be determined that the product shelves 329 to 334 are product shelves that were not interested. In addition to this, it is also possible to specify and display the location of the product where the purchase amount is actually large, in cooperation with the POS DB 114 and the product position DB 112.

  Next, the configuration of each file will be described.

  FIG. 4 shows an example of data contents of the IC tag 102 installed in the cart 101 of FIG. The IC tag 102 stores an IC tag ID 401 that is an identifier for uniquely identifying each IC tag. The IC tag ID 401 is used for the analysis server 107 to associate with customer characteristic information, purchased product information, and the like of the customer in order to specify a customer who makes a purchase with the cart.

  FIG. 5 shows an example of data contents of each IC tag reading device 103 (201 to 207 in FIG. 2) arranged on the floor 104. The reading device ID 501 is an identifier that uniquely identifies each IC tag reading device, and is set in advance. The received IC tag ID 502 and the received radio wave intensity 503 are areas for storing the read IC tag ID and the received radio wave intensity when any IC tag 102 is read by the IC tag reader. Having the received IC tag ID 502 and the reception level 503 enables the analysis server 107 to accurately measure the position of the IC tag. In addition, by updating and acquiring these data in time series, it is possible to measure the moving speed and moving direction of the IC tag.

  FIG. 6 shows an example of the file structure of the POS DB 114. The POS DB 114 stores information such as a product ID 601, a product name 602, a price 603, a purchase value 604, a supplier code 605, and a stock quantity 606 regarding each product. The association between the product ID 601 and the IC tag ID 401 is automatically performed on the analysis server 107 side when the IC tag ID 401 is received by a specific IC tag reader 103, as will be described later. Is not necessary. The price 603 is the selling price of the product. When a special price sale or the like is performed, it is possible to set a special price flag by updating this price information. The stock quantity 606 indicates the remaining number of products existing in the store, and the analysis server 107 measures the reduction of the product to give an additional storage instruction or consider replacement of the next product. It is a feature that can be used in some cases.

  FIG. 7 shows an example of the file structure of the analysis DB 113. The analysis DB 113 includes two DBs.

  The first DB shown in FIG. 7A stores an IC tag ID 701, a reading device ID1 702 to a reading device IDn 703, and a time 704. Note that there are five storage areas between reading device ID1 702 and reading device IDn 703, reading device ID2 to reading device ID6. This DB stores which reading device ID the IC tag ID received at a radio wave intensity level equal to or higher than a predetermined reference value is received by the reading device. The ID of the reader that received the IC tag ID 701 with the highest radio field intensity at that time is stored in the reader ID1 (corresponding to 201 in FIG. 2, and the cart of the IC tag is currently located at this position. IDs of the six surrounding reading devices are stored in reading device ID2 to reading device ID7 (202 to 207 in FIG. 2). Time 704 is the time when the IC tag ID is received. The reception of the IC tag ID by each reading device in the floor is repeatedly performed at a predetermined time interval, and the data shown in FIG. 5 is obtained for the IC tag ID received at a radio wave intensity equal to or higher than a predetermined reference value. Since the information is transmitted from each reading device to the analysis server 107, the analysis server 107 analyzes the transmitted information, and at that time, the reading device ID where the cart of the IC tag ID 701 is located is adjacent to the reading device ID. The reader ID is specified, and the information is stored in this DB with time.

  The second DB shown in FIG. 7B stores an IC tag ID 701, product ID 1 705 to product ID n 706, customer sex 707, customer age 708, and alert flag 709. This DB stores the ID of the product actually purchased by the customer who uses the cart specified by the IC tag ID 701 in the product ID 1 705 to the product ID n 706, and also includes the customer sex 707 and the customer characteristic information of the customer. The age 708 is stored. An area for storing the product ID is provided between the product ID 1 705 and the product ID n 706 according to the number of purchased products. Customer information is not limited to gender and age. The alert flag 709 is normally 0 (off), and is a flag that is automatically updated to 1 (on) when the end of the in-store behavior of the customer is detected as being fraudulent. Such an alert system is linked to other reporting systems. When the alert flag 709 is turned on, an alert is issued, for example, by sounding a patrol / buzzer in the store.

  By having the IC tag ID, the reading device ID, and the product ID by the DB of FIG. 7 described above, the information separately transmitted to the analysis server 107 is associated in the analysis DB 113.

  FIG. 8 shows an example of the file structure of the product position DB 112. The product position DB 112 stores a product ID 801, a display shelf ID 802, and a stage 803. The purpose of this DB is to identify which product is located on which display shelf in the store by associating a specific product ID with a display shelf ID. The product can be specified on the map.

  Next, characteristic operations and processing of the system of this embodiment will be described.

  FIG. 9 shows a block diagram of processing performed in this system in a series of flow from the start of shopping by the customer until payment is made and the customer returns. Although some human actions are included, human actions and this system will be described separately below.

  In FIG. 9, first, a customer enters the store through the entrance / exit 308 (step 901). Next, the customer takes the cart 301 for shopping (step 902). In the present embodiment, an example in which an IC tag is installed in a cart has been described as an example. However, a cart used for shopping may be used instead of a cart. Steps 901 and 902 are human actions.

  Next, when the customer passes through a location of the customer information reading camera system 302 installed at a point entering the store from the cart yard 303, the customer information reading camera system 302 is photographed and obtained. The customer's age, sex, and other characteristics are automatically determined from the obtained image data and acquired as customer information data (step 903). The acquired customer information data is transmitted to the analysis server 107 (step 904). Steps 903 and 904 are operations of this system. Although the customer information reading camera system is not shown in FIG. 1, a customer information reading camera system 302 is provided in the vicinity of the entrance through which shopping is started as described in FIG. It is connected to the analysis server 107 by wired or wireless communication means.

  After entering the store, the customer moves inside the store for shopping (step 905). This is a human action. In this system, a plurality of IC tag readers 103 (201 to 207 in FIG. 2, 201-207 in FIG. 2, and FIG. 3) are installed on the store floor 104 at regular intervals at certain time intervals. 305), and the received data (data in FIG. 5) is transmitted to the analysis server 107 in real time (step 906). The analysis server 107 generates and stores data to be stored in the analysis DB described with reference to FIG. 7A using the received data (step 906). Next, it is determined whether the customer has arrived at the cash register corner 306 (step 907). This determination is to determine whether the customer's cart has been detected by the IC tag reader installed on the floor portion of the cash register corner 306. If the customer has not yet arrived at the cash register corner 306, the customer's unauthorized behavior is detected. Steps 906, 907, and 909 are the operations of this system. The loop of steps 905, 906, 907, and 909 is performed endlessly as long as the customer continues shopping in the store. Step 909 is a process for detecting fraudulent behavior based on pre-specified conditions, for example, when the cart stays at a certain point for a certain period of time or when the cart goes out of the entrance / exit without exiting the cash register. It is. If an unauthorized action is detected, the analysis server 107 issues alert information (step 910). This alert information is reported immediately, and an alarm is issued in conjunction with other systems such as lighting of emergency lights in the store. When it is detected that the customer has arrived at the cash register corner 306 by receiving the IC tag from the specific IC tag reader (step 907), the purchase information by the cash register is transmitted as POS data to the analysis server 107 (step 909). The analysis server 107 stores information on the product purchased by the customer in the analysis DB of FIG. At this point, a series of customer purchasing behavior ends.

  FIG. 10 is a flowchart of the process of automatically transmitting customer information data to the analysis server 107 (step 904 in FIG. 9). In the figure, first, a customer information reading camera system 302 automatically detects the passing of a customer (step 1001), and an IC tag ID read by an IC tag reading device installed in the vicinity at that time is analyzed server 107. (Step 1002). As a result, the analysis server 107 can associate a specific IC tag ID with information that is subsequently read by the customer information reading camera system 302. Next, the customer information reading camera system 302 automatically determines the age and sex of the customer from the captured image data of the customer, and transmits the determination result to the analysis server 107 as customer information data (step 1003). It should be noted that the internal specifications of the customer information reading camera system 302 are assumed to use known techniques, and detailed description thereof is omitted. The analysis server 107 creates an entry in the analysis DB in FIG. 7B using the transmitted IC tag ID as the IC tag ID 701. The product ID 705 and 706 fields are left blank. Further, the received customer information data is set in the customer sex 707 and customer age 708 corresponding to the IC tag ID 701 (step 1004).

  FIG. 11 is a flowchart of subroutine processing (step 906 in FIG. 9) when the analysis server 107 measures the moving direction / moving speed and position of the customer (IC tag). In the figure, first, reception information and reception radio wave levels (that is, data of FIG. 5) from all IC tag readers in the store at a certain time point are received in real time by the analysis server 107 (step 1101). At this time, if the radio wave intensity level is lower than a preset reference value, the level is not detected as 0, thereby reducing the necessary storage capacity required for the analysis server 107. Next, the reader ID (201 in FIG. 2) that received the highest radio wave intensity level is specified for a specific IC tag ID from the received data (step 1102). Further, for the specific IC tag ID, the radio wave intensity levels are received from the six reading devices (202 to 207 in FIG. 2) adjacent to the reading device, and the radio wave intensity levels from the obtained seven reading device IDs are obtained. The exact location of the IC tag at that time is measured (step 1103). The seven reading device IDs obtained in steps 1102 and 1103 are stored in the column of reading device ID1 702 to reading device ID7 703 corresponding to the IC tag ID 701 in FIG. Store it in. Next, by comparing the position information and the reception level of the reader ID stored in the analysis server 107 one unit time ago (more than one unit may be traced back) with the measurement result in step 1103 above, The moving speed and moving direction of the IC tag are measured (step 1104). Then, the time counter is advanced by one unit time (step 1105), the process returns to step 1101, and the above processing is repeated. This repetitive process is repeated until the IC tag arrives at the register position in the main flow of FIG. 9 or until alert information is detected.

  Since it is generally considered that a plurality of carts are shopping on the floor, a plurality of IC tag IDs are usually received in step 1101. Accordingly, each processing in steps 1102 to 1104 is performed for each of the IC tag IDs. Thereby, the position, moving direction, and moving speed of each IC tag (customer) existing in the floor can be acquired.

  In step 1104, the movement direction and movement speed of the customer are obtained. The movement direction and movement speed of each customer obtained here are stored in a DB (not shown) in the analysis server 107. Note that the direction and speed of movement of the customer may be obtained later when analyzing the customer purchase behavior. Therefore, step 1104 is not executed in FIG. 11, and the process shown in FIG. The moving direction and moving speed may be obtained from the data in the analysis DB. In the analysis DB of FIG. 7A, the reading device ID1 nearest to the position of the IC tag and the surrounding six reading devices ID2 to ID7 are stored every predetermined unit time. The moving direction and moving speed can be calculated from In this case, if the radio wave intensity received by these reading devices as well as the reading devices ID1 to ID7 is accumulated, a finer position can be calculated.

  Next, an example of analyzing customer purchase behavior and displaying the analysis result in the analysis server 107 in response to a request from the analysis system client PC 110 will be described.

  FIG. 12 is a flowchart of processing for designating a specific customer segment, analyzing the purchase behavior, and displaying the result on the screen. First, an analysis condition is specified from the analysis system client PC 110, and an analysis based on the condition is requested to the analysis server 107 (step 1201). Here, it is assumed that a man in his 30s specifies the condition of usage time 16-20.

  FIG. 14 shows an example of an analysis condition designation screen on the client PC 110 used in step 1201. The gender, age, and analysis period of the analysis target can be specified. By specifying these conditions and turning on (clicking) the analysis start button, the request of step 1201 is issued.

  Upon receiving the request, the analysis server 107 extracts data that meets the specified conditions from the analysis DB 113 (FIG. 7), and analyzes and obtains a behavior pattern of a specific customer segment (step 1202). Here, examples of the behavior pattern include a product shelf that has been interested as described with reference to FIG. 3B, an area that has taken a long time (passage time), and the like. Furthermore, in addition to these, in conjunction with the POS DB 114 and the product position DB 112, it is possible to analyze and acquire the specification of the location of the product where the purchase amount is actually large. The above calculation result (analysis result) is transmitted from the analysis server 107 to the analysis client PC 110 through the VPN Internet circuit 109 (step 1203). The analysis client PC 110 displays the analysis result in a color-coded manner on the screen (step 1204), so that the analysis result can be grasped visually. An example of the display screen has a form as shown in FIG.

  FIG. 13 is a flowchart showing a processing procedure when planning / planning rearrangement of in-store product arrangement based on the analysis result of customer purchase behavior as an application example of the analysis result shown in FIG. Steps 1301 and 1302 are the same processes as steps 1201 to 1204 in FIG. 12, and are the processes for displaying the behavior pattern of the designated customer segment.

  Thereafter, it is determined whether or not there is a product with high sales on the in-store flow line through which the customer layer frequently passes (step 1303). This process superimposes all in-store flow lines of customers belonging to the customer segment, extracts a location where a predetermined number or more customers pass, and whether there is a product with high sales at that location (product location and sales This is a process for determining (with reference to high information). If there is a product with high sales, in order to guide customers to the entire store, a message is displayed instructing that the product with high sales be relocated to the store space where the customer segment does not pass ( Step 1304). The in-store space where the customer layer does not pass so much can be obtained by superimposing all the in-store flow lines of the customers belonging to the customer layer and extracting a place where only a predetermined number or less of customers pass. By rearranging according to the message, it is possible to increase the sales of the entire store.

  If there is no product with high sales on the in-store flow line that the customer layer frequently passes in step 1303, the special sales area for the specific customer layer or an interest is placed on the in-store flow line that the customer layer frequently passes. It is determined whether there is a display shelf for the product. If there is no message, the message tells the customer to place the special sales corner or display shelf that was interested but not connected by purchase on the in-store flow line that the customer group frequently passes. Is displayed (step 1306). By performing such rearrangement, it is also possible to increase sales of a specific product layer in a store that targets the specific customer layer.

System schematic diagram of one embodiment of the present invention Layout of IC tag reader when the floor is viewed from above Conceptual diagram of customer purchase behavior grasp map Conceptual image of analysis image Diagram showing an example of the contents of an IC tag The figure which shows the contents example of IC tag reading device Figure showing example contents of POS database Figure showing an example of the contents of an analysis database The figure which shows the contents example of the commodity position database Flowchart diagram showing the flow from when the customer starts shopping until payment is completed Flowchart diagram of processing for automatically sending customer information data to the analysis server Flowchart diagram of processing to automatically measure the customer's movement direction and speed by reading the IC tag information of the cart with the IC tag reader Flowchart diagram of processing for displaying analysis results of customer purchase behavior on analysis server and analysis system client Flowchart diagram of processing for planning and planning rearrangement of in-store product placement based on analysis results of customer purchasing behavior Figure showing an example of analysis condition specification screen on an analysis client PC

Explanation of symbols

  DESCRIPTION OF SYMBOLS 101 ... Shopping cart, 102 ... IC tag, 103 ... IC tag reader, 104 ... Floor, 105 ... Cashier, 106 ... Register, 107 ... Analysis server, 108 ... IC tag information receiving antenna, 109 ... VPN Internet line, 110 ... Analysis system client PC, 111 ... customer purchase behavior analysis system, 112 ... commodity position DB, 113 ... analysis DB, 114 ... POS DB, 201-207 ... IC tag reader, 301, 301 '... cart, 302 ... customer information read Camera system device, 303 ... Cart place, 304 ... Product display shelf, 305 ... IC tag reader, 306 ... Register corner, 307 ... Register, 308 ... Entrance / exit, 309 ... Emergency exit, 310 ... IC tag

Claims (4)

A customer purchase behavior analysis system for analyzing customer purchase behavior in a store,
A non-contact type IC tag that stores an IC tag ID, which is an identifier for identifying the IC tag, attached to a cart or a basket used when a customer makes a purchase in a store,
When a customer starts shopping using the cart or basket, the IC tag ID of the IC tag attached to the cart or basket used by the customer is read, and customer characteristic information indicating the characteristics of the customer is automatically read. Customer information reading means to acquire automatically,
Means for storing the customer characteristic information acquired by the customer information reading means in correspondence with the IC tag ID of the IC tag attached to the cart or the basket used by the customer;
A plurality of IC tag reading means arranged at regular intervals on the floor in the store;
When the customer makes a purchase using the cart or car, the IC tag ID of the IC tag attached to the cart or car is read by the plurality of IC tag reading means, and the received radio wave intensity level is acquired. Analyzing the ID of the IC tag reading means closest to the IC tag by analyzing and storing the read IC tag ID, the ID of the IC tag reading means and the time at that time, at a predetermined time interval Means to repeatedly execute in
Means for detecting that the customer has entered a cash register corner for shopping;
A customer purchase behavior analysis system comprising: means for storing the information of the product purchased by the customer in association with an IC tag ID of an IC tag attached to a cart or a basket used by the customer. The customer purchase behavior analysis system according to claim 1, further comprising:
Analyzing the IC tag ID and IC tag reading means ID and time information stored at the predetermined time interval, and obtaining a position, moving direction, and moving speed for each time interval in the customer's store Customer purchase behavior analysis system characterized by comprising. The customer purchase behavior analysis system according to claim 2, further comprising:
From the information on the position, moving direction and moving speed obtained for each customer and information on the product purchased by the customer, information on the customer that satisfies the specified condition is extracted, and the staying time is predetermined for the customer of the customer group Analyze the store area where there were more products than the value, the display shelves with products whose purchase amount was more than the specified value, and the display shelves with products that were interested but did not lead to purchase, etc. and analyzed the results A customer purchase behavior analysis system characterized by comprising means for visually displaying on top. The customer purchase behavior analysis system according to claim 1, further comprising:
A customer purchase behavior analysis system comprising means for generating alarm information when position information of an IC tag recognized as suspicious behavior is detected before detecting that the customer has entered a cash register corner.

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