WO2005111880A1 - 行動解析装置 - Google Patents
行動解析装置 Download PDFInfo
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- WO2005111880A1 WO2005111880A1 PCT/JP2005/008809 JP2005008809W WO2005111880A1 WO 2005111880 A1 WO2005111880 A1 WO 2005111880A1 JP 2005008809 W JP2005008809 W JP 2005008809W WO 2005111880 A1 WO2005111880 A1 WO 2005111880A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
Definitions
- the present invention relates to a behavior analysis device, and more particularly, to a technique for analyzing a behavior of a moving object in a space by detecting a position using a technique such as wireless communication.
- Patent Document 1 Japanese Patent Application Laid-Open No. 2003-223548
- Point-of-sale POS
- Point-of-sale (POS) systems can provide statistics on merchandise sales and purchasers based on data entered into retail cash registers.
- POS data shows ⁇ sellable products '' and ⁇ unsellable products ''
- it is difficult to identify the factors related to customer behavior such as ⁇ why sell '' and ⁇ why not sell '' . Therefore, it was difficult to determine whether a product that could not be sold had a problem with the product itself or simply had a problem with the display method, and it was difficult to take appropriate measures.
- a behavior analysis device provides position information indicating a position of a moving object that changes with time in a predetermined real space and a positioning timing thereof.
- a position acquisition unit that acquires the time information shown in the table, a space acquisition unit that acquires the space information representing the real space in the virtual space, and a mobile unit in the real space based on the position information, the time information, and the space information.
- a path obtaining unit that generates path information indicating a moving path of a moving object in a virtual space, a speed obtaining unit that generates speed information indicating a moving speed of the moving object based on the position information and the time information,
- a pattern storage unit that stores a plurality of action pattern data, each of which defines a different action pattern as a type of action based on the relationship between the movement path and the movement speed, and the route information, speed information, and multiple actions
- a pattern determination unit that determines whether the behavior of the moving object matches the type of the behavior pattern based on the pattern data, and an output processing unit that outputs a determination result.
- the "moving object” is, for example, a customer who has visited a store, a shopping cart or a shopping basket of the customer, a store employee, a visitor or employee in a recreation facility such as a theme park, or a competition space. Indicates a person moving in the space, such as an athlete inside, or an accessory thereof.
- the “behavior pattern data” defines a case where the type of the behavior pattern of the mobile body in the entire predetermined space is defined, and a case where the type of the behavior pattern of the mobile body in each of the plurality of regions included in the predetermined space is defined. Any of the above cases may be used.
- the space acquisition unit acquires, as space information, respective coordinates for specifying the arrangement of a plurality of regions included in the real space in the virtual space, and the route acquisition unit acquires the movement of the moving object in the real space.
- the route information indicating the route by the position in the virtual space is transmitted to the mobile
- the speed acquisition unit generates the average speed of the moving object in all of the plurality of regions, the average speed of the moving object in each of the plurality of regions, and the moving object as speed information.
- the pattern determination unit generates information indicating at least one ⁇ of the instantaneous speed of the moving object, and the pattern determining unit determines the route information and the speed information including information on which of the plurality of areas the moving object has passed, and the plurality of actions. Based on the pattern data, the match of the behavior pattern may be determined!
- the position acquisition unit acquires position information indicating the position of the moving object in a space in a predetermined store as real space and time information thereof, and the space acquisition unit determines the arrangement of a plurality of counters included in the store.
- the respective coordinates for specifying in the virtual space are acquired as space information, and the route obtaining unit obtains the route information indicating the moving route of the moving object in the space in the store by the position in the virtual space, and obtains the route information.
- the speed acquisition unit outputs, as speed information, the average speed of the mobile object in all of the plurality of sales area areas, and the speed of the moving object in each of the plurality of sales area areas.
- the pattern determination unit generates information indicating at least one of the average speed and the instantaneous speed of the moving object, and the pattern determination unit includes route information including information on which of the plurality of counters the moving object has passed.
- the coincidence of behavior patterns on the basis of the degree information and the plurality of behavioral pattern data may be determined. In this case, since the behavior of the customer can be analyzed for each sales floor, accurate useful information that leads to sales promotion can be obtained for each sales floor or product.
- This behavior analysis device is capable of transmitting intensity information indicating the intensity of radio waves transmitted or received by a communication device carried by a mobile object among a plurality of wireless communication devices installed at different positions in a real space.
- the apparatus may further include an intensity obtaining unit that obtains the information via at least one of them, and a position recognizing unit that generates position information and time information indicating the position of the moving object based on the intensity information.
- the “wireless communication device” may be a wireless base station also called a so-called access point. In this case, location information and time information can be acquired using wireless LAN technology, which is widely used as hardware, and the behavior of a mobile body such as a visiting customer can be analyzed at relatively low cost.
- the “communication device held by a mobile object” is mainly assumed to be a wireless LAN terminal, but this may be realized by an IC tag (RFID) with a built-in wireless function! / ⁇ .
- RFID IC tag
- one of the plurality of radio communication devices installed at different positions in a real space and one of the radio communication media carried by a mobile body transmits radio waves.
- a position recognition unit that generates position information indicating the position of the moving object and time information based on the length of time until one receives the radio wave as a response from the other that received the radio wave.
- the “wireless communication device” and the “wireless communication medium carried by the moving object” are also the same as above, and may be a wireless LAN or an IC tag.
- This behavior analysis device is a device in which an IC tag or a wireless communication device carried by a moving object is a device out of a plurality of wireless communication devices or a plurality of IC tags installed at different positions in a real space. And a position recognition unit that generates position information and time information indicating the position of the mobile object based on the location of the mobile object.
- This behavior analysis device specifies an image acquisition unit that acquires an image captured by a predetermined angular force in a real space, and an object that moves between a plurality of images acquired by the image acquisition unit as a moving object.
- a position recognition unit that generates position information and time information of the moving object by recognizing the position of the object in the space in the image.
- imaging as used herein may mean imaging using a CCD sensor or a CMOS sensor, or special imaging using reflected waves when ultrasonic waves, microwaves, infrared rays, electromagnetic waves, etc. are applied to an object. .
- the pattern determination unit may acquire data indicating the purchase content of the mobile customer, and may estimate the factor of the quality of the purchase based on the data indicating the purchase content and the type of the matching behavior pattern.
- data indicating the purchase content of a customer may be acquired using POS data. Since there is a correlation between the degree of sale of the product and the behavior pattern of the customer, it is possible to relatively easily grasp the cause of the good sale or the poor sale by combining the two.
- the pattern determination unit determines the position of the settlement area where the customer stayed for the purchase of the product and the date and time of the purchase of the product based on the route information, and determines the purchase content corresponding to the position of the payment region and the date and time of the purchase of the product. May be obtained, and the obtained data may be associated with the route information.
- the pattern determination unit is configured to determine the type of the route information, the speed information, and the matching action pattern, and the attribute pattern data in which the conditions of the type of the route information, the speed information, and the type of the action pattern are defined for each customer attribute.
- the attribute of a customer who is a moving object may be estimated. In some cases, there is a high correlation between the customer's attributes and the behavioral patterns, and by converting such relationships as attribute pattern data into data, the customer's attributes can be relatively easily adapted to the behavioral patterns. Can be estimated.
- the pattern determining unit acquires the attribute of the customer as the moving object, and stores the determined behavior pattern in the pattern storage unit as attribute pattern data in association with the attribute. By referring to the attribute pattern data stored in the section, the attribute can be determined and the attribute of the customer can be estimated.
- a product information storage unit that stores information that can be provided to a customer regarding a product to be sold in association with a sales floor of the product and a type of behavior pattern, and a mobile unit according to a type of a matching behavior pattern.
- An information distribution unit that transmits information that can be provided to the customer to a communication device held by the customer. Since the current state of the customer and the ability of the customer's behavioral patterns can be estimated, the active distribution of information that matches the position and the state can lead to product sales promotion and sales efficiency. Can be.
- the plurality of action pattern data stored in the pattern storage unit includes a first pattern indicating a case where the customer who is a moving object in the sales area to be determined passes through the sales area as a type of purchasing behavior.
- Time spent in each sales area area for the second pattern which indicates when goods were purchased or purchased after a relatively short stay in the area
- the third pattern which indicates when goods stayed for a long time in one sales area.
- the presence or absence of stop, and the calorie deceleration are defined in advance, and the pattern determination unit determines whether the behavior of the customer as the mobile object is the first pattern, the second pattern, and the third pattern. It may be determined which of the patterns matches.
- the “stop” here may include a case where the vehicle stays to the extent that the vehicle is considered to be substantially stopped or a case where the traffic speed is so low as to be much lower than the average speed.
- acceleration / deceleration for example, the presence / absence of sudden deceleration may be determined. This makes it possible to accurately estimate the purchase behavior of the customer.
- the pattern determining unit calculates the stay time until the moving object enters and leaves each time in each of the plurality of sales area areas, and purchases the goods based on the route information and the data indicating the purchase content.
- Identify the mobile unit that had the problem and the sales floor area of the purchased product specify the staying time of the mobile unit in that sales area as the stay time at the time of product purchase, and specify the time when purchasing the product for each of the multiple sales area areas.
- the average minimum time which specifies the effective minimum time and the maximum time for each day or time zone, and averages the effective minimum time for multiple days or multiple time zones for each sales area. Is calculated and stored in the pattern storage unit as a first threshold value for distinguishing the first pattern from the second pattern in a form corresponding to the sales area.
- the average longest time obtained by averaging the substantial longest times over a plurality of time zones is calculated, and this is stored in the pattern storage unit as a second threshold value for distinguishing the second pattern from the third pattern.
- the behavior pattern of the moving object in the sales area becomes the first pattern. It is determined that they match, and the staying time in the sales area of the mobile unit for which the behavior pattern is to be determined is greater than or equal to the first threshold value associated with the sales area area and less than the second threshold value. In this case, it is determined that the behavior pattern of the moving object in the sales area matches the second pattern, and the staying time in the sales area of the moving object for which the behavior pattern is to be determined is determined. If is greater than or equal to the second threshold value associated with the counter area, the behavior pattern of the moving object with respect to the counter area may be determined to match the third pattern.
- the value falls below the first threshold value does not mean that values near the first threshold value are strictly distinguished.
- the case where the threshold value is equal to the threshold value or the case where the threshold value is within the predetermined range from the first threshold value may also be determined to match the first pattern.
- the criterion for the second pattern "when the value is equal to or more than the first threshold value and falls below the second threshold value” or the criterion for the third pattern, " It does not mean that values close to each threshold value are strictly distinguished.
- the terms “substantial minimum time” and “substantial maximum time” are intended to exclude abnormal values that are extremely short or long. Of the values, for example, the shortest time and the longest time excluding values within the range of 10% may be set as the substantial shortest time and the longest time, respectively.
- multiple days may be specified by, for example, a day of the week !, by a combination of a month and a day of the week, or by a method of dividing a weekday and a holiday.
- Multiple time zones may be specified by, for example, only a time zone, a combination of a day of the week and a time zone, or a combination of a month, a day of the week, and a time zone. It may be specified by a combination of weekday and holiday division and time zone!
- the pattern determination unit expresses, for each sales area, the relationship between the stay time and the number of customers who stayed in that area, among the customers whose stay time is shorter than the first time value, there is no purchase of goods in the sales area.
- the time value at which the ratio of the total of the customers who have made purchases in the sales area area to the total of the customers who made an effort to purchase products in the sales area becomes a specified percentage is specified as the first time value for each day or for each time zone.
- the mobile Behavior patterns If it is determined that the moving pattern matches the second pattern, and the staying time of the moving object for which the behavior pattern is to be determined in the sales area is equal to or greater than the second threshold value associated with the sales area, the sales area is determined. It is determined that the behavior pattern of the mobile May be.
- the no-turn determining unit determines whether the customer, who is a moving body, has at least one of the flow line distance to exit, the entrance time, the stay time, the average speed, and the total number of stops in the entire space in the store.
- the first threshold, the value, and the second threshold are calculated for each segment, stored in the pattern storage unit, and the moving object for which the behavior pattern is determined is determined for each segment. Determines which of the multiple segments corresponds to at least one of the flow line distance from entry to exit, entry time, stay time, average speed, and total number of stops in the entire space in the store.
- the first pattern, the value and the second threshold corresponding to the corresponding segment, and the values of the first pattern, the second pattern, and the third pattern are determined based on the value. Judge whether it matches the gap You can! /
- the pattern determination unit classifies the behavior of the customer as the moving body into a case in which the behavior matches the first pattern and a case in which the behavior coincides with the second pattern and the third pattern. By calculating the reference value, a reference value for estimating the factor of the product purchase presence / absence may be determined.
- the pattern determining unit determines whether the quality of the purchase by the customer as the moving object is determined by the number of times of the product of any one of the first pattern, the second pattern, and the third pattern for each sales area.
- the number of purchases or the purchase amount, or the number of the first pattern, the second pattern, and the third pattern may be calculated. As a result, it is possible to accurately estimate the factor of the customer's purchase quality.
- useful information can be provided by analyzing the behavior of a moving object in a space.
- FIG. 1 is a functional block diagram showing a configuration of a customer behavior analysis system.
- FIG. 2 is a diagram schematically showing a relationship between a classification based on a customer state and the number of purchasers.
- FIG. 3 is a view showing the appearance of a shopping cart.
- FIG. 4 is a diagram schematically showing a sales floor arrangement in a store in a virtual space defined by space information.
- FIG. 5 is a diagram schematically showing a hierarchical sales area.
- FIG. 6 is a diagram schematically illustrating an example of a moving path of a shopping cart in a sales area.
- FIG. 7 is a functional block diagram illustrating a configuration of a customer behavior analysis system according to a second embodiment.
- FIG. 8 is a functional block diagram illustrating a configuration of a customer behavior analysis system according to a third embodiment.
- FIG. 9 is a functional block diagram illustrating a configuration of a customer behavior analysis system according to a fourth embodiment.
- FIG. 10 illustrates an image obtained by photographing a certain sales area from a bird's-eye view.
- FIG. 11 is a diagram schematically showing a shooting state of a counter image in FIG. 10 from the side.
- FIG. 12 is a diagram in which a cylinder model is applied to the sales floor image of FIG.
- FIG. 13 is a diagram schematically showing a technique for detecting the same moving object in overlapping imaging ranges.
- FIG. 14 is a diagram schematically illustrating an example of a shooting range of each camera in a store.
- FIG. 15 is a functional block diagram showing a configuration of a customer behavior analysis system according to a fifth embodiment.
- FIG. 16 is a functional block diagram showing a configuration of a customer behavior analysis system according to a sixth embodiment.
- FIG. 17 is a diagram showing a relationship between stay time and the number of customers in a sales area.
- FIG. 18 is a diagram showing an example of a screen displaying a list of lengths of time for each behavioral state of an employee. Explanation of symbols
- 10 customer behavior analysis system 20 customer behavior analysis device, 22 communication unit, 24 strength acquisition unit, 26 position recognition unit, 28 position information storage unit, 30 position acquisition unit, 32 speed Acquisition unit, 34 route acquisition unit, 36 space acquisition unit, 38 spatial information storage unit, 40 data setting unit, 42 pattern judgment unit, 44 action pattern data storage unit, 46 judgment result storage unit, 48 output processing unit, 50 Information distribution unit, 56 display unit, 58 product information storage unit, 60 shopping cart, 62 liquid crystal display for cart.
- POS point-of-sale
- purchases such as “why sell power” and “why not sell” It is difficult to identify the factors.
- the intention of the customer to go to the sales floor and the circumstances leading to the purchase of the product can be grasped based on statistical data, and the interest and interest of each customer for the products in the sales floor can be objectively estimated. And obtain useful marketing information.
- FIG. 1 is a functional block diagram showing the configuration of the customer behavior analysis system.
- the customer behavior analysis system 10 includes a first access point 12, a second access point 14, and a third access point 16, which are a plurality of wireless LAN base stations, and a customer behavior analysis device 20.
- the “plurality of wireless LAN base stations” are provided with at least three access points for positioning between a mobile unit and each base station using the strength of radio waves.
- three access points including a first access point 12, a second access point 14, and a third access point 16 are illustrated.
- four access points may be used depending on the size of the store or the sales area. More than two access points may be used.
- Each of the first access point 12, the second access point 14, and the third access point 16 communicates with a communication device provided in a shopping cart of a customer via an antenna via a wireless LAN, and also via a LAN 18 via a LAN.
- a communication device provided in a shopping cart of a customer via an antenna via a wireless LAN, and also via a LAN 18 via a LAN.
- the customer behavior analysis device 20 acquires POS data from the POS server 19 via the LAN 18 as data indicating purchase content.
- the POS data includes information on customer purchases.
- the POS server 19 is connected to a plurality of cash registers (not shown), and a product name or a product ID sold from each cash register, a quantity, a sales amount, a sales date and time, and a customer ID. And other information related to customer purchases.
- the customer ID may be, for example, the ID of a member card issued to the customer. In that case, the POS server 19 does not acquire the customer ID from a customer who does not own the member card.
- the customer behavior analysis device 20 includes a communication unit 22, an intensity acquisition unit 24, a position recognition unit 26, a position information storage unit 28, a position acquisition unit 30, a speed acquisition unit 32, a route acquisition unit 34, a space acquisition unit 36, Spatial information storage unit 38, data setting unit 40, pattern determination unit 42, behavior pattern data storage unit 44, determination result storage unit 46, output processing unit 48, information distribution unit 50, operation input unit 52, control unit 54, display unit 56, a product information storage unit 58 is provided.
- the communication unit 22 transmits and receives data to and from the first access point 12, the second access point 14, the third access point 16, and the POS server 19 via the LAN 18.
- the strength obtaining unit 24 receives data indicating the radio wave strength from the first access point 12, the second access point 14, and the third access point 16 via the communication unit 22.
- This radio wave intensity is the intensity of a radio wave transmitted and received between a communication device provided in a shopping cart used by the customer.
- the communication device of each shopping cart transmits data indicating the strength of radio waves transmitted and received between the first access point 12, the second access point 14, and the third access point 16 to the first access point 12, the first access point 12, and the third access point 16. 2 Transmit to at least one of the access point 14 and the third access point 16 and send it to the strength acquisition unit 24 via the first access point 12, the second access point 14 or the third access point 16. Get.
- the position recognition unit 26 determines the strength of the shopping cart based on the difference in the radio wave intensity from the same shopping cart received from the first access point 12, the second access point 14, and the third access point 16 by the strength acquisition unit 24. Recognize location. That is, the position recognizing unit 26 obtains the distance from each access point to the shopping cart based on the radio wave intensity received from each access point, and recognizes a point where the distance intersects as the current position of the shopping cart. The position recognizing unit 26 generates position information, which is the current position of the customer, which changes with time in the store, and time information indicating the timing at which the position information was measured, and stores it in the position information storage unit 28.
- This position information indicates the relative position of the shopping cart with respect to the three access points, and is represented by, for example, (X, y, z) three-dimensional coordinates. Also, it may be represented as (X, y, z, t) together with the time information, or may be represented by two-dimensional coordinates such as (X, y) or (X, y, t).
- the location information of one access point is also set as a manager based on the input information. That is, when installing each access point, the administrator inputs the approximate position via the operation input unit 52, and the position recognition unit 26 corrects the input value based on the radio wave intensity between the access points. Recognize each accurate position and store the position information in the position information storage unit 28.
- the position acquisition unit 30 acquires, from the position information storage unit 28, the position information and the time information of the shopping cart used by the customer who has performed shopping in the store or used by the customer who is shopping. That is, the position information and the time information continuously measured until the customer enters the store, starts using the shopping cart, and finishes using the shopping cart are acquired by the position acquiring unit 30.
- the speed acquisition unit 32 generates speed information indicating the moving speed of the customer based on the position information and the time information. For example, the speed acquisition unit 32 calculates the average speed, the maximum speed, and the average number of stops for all shopping carts, the starting speed for each shopping cart, the average speed until the end of use, the maximum speed, and the number of stops, the average speed for each sales area, Calculate the maximum speed and average number of stops, the average speed per store area for each shopping cart, the maximum speed and the number of stops, and the speed of the shopping cart currently in use.
- the ability to start using the shopping cart throughout the store The flow distance until the end of use, entry time, stay time, average speed or average speed excluding the third pattern, total number of stops, determined to match the first pattern
- Parameters such as a minimum value, a maximum value, an average value, and a threshold value, which will be described later, are calculated for each customer segment, and processing of determining an action pattern and estimating a customer attribute is performed for each customer segment.
- parameters such as a minimum value, a maximum value, an average value, and a threshold value are calculated for the entire customer, not for each customer segment, and based on the calculated parameters, behavior patterns are determined and customer attributes are determined. Process the estimation Is also good.
- the “average speed” here is also calculated together with the average speed in a period excluding the “freeze” state described later.
- the space acquisition unit 36 acquires space information representing a space in a store by a position in a virtual space.
- space information coordinates indicating the entire area of the store and coordinates for specifying the arrangement of a plurality of sales floors included therein in the virtual space are defined.
- the positions of the first access point 12, the second access point 14, and the third access point 16 are also determined in the spatial information.
- the route acquisition unit 34 generates route information indicating the customer's travel route in the space within the store as a position in the virtual space based on the position information, the time information, and the space information.
- the route acquisition unit 34 generates route information together with information on which of the plurality of sales area areas the customer has passed. As described above, the route information is generated for each sales floor area, and if all the route information is connected in a time series in one shopping cart, all the routes from the start of use to the end of use are recognized.
- the behavior pattern data storage unit 44 stores a plurality of behavior pattern data in which different behavior patterns are defined as types of purchasing behavior based on the relationship between the customer's travel route and travel speed.
- the type of purchasing behavior defined in multiple behavior pattern data is, for example, “passing”, which is the first pattern that passes through the sales area without showing a stop or sudden deceleration and! /
- the second pattern, ⁇ active '' is a second pattern for considering purchases of goods at least for a short time in the sales area, and the third pattern is to stay in one sales area for a long time. There is a "freeze".
- an average staying time, an average traffic speed, presence or absence of a cart stop, and presence or absence of a sudden deceleration are determined in advance for each purchase area for various purchase behaviors.
- a plurality of action pattern data are determined for each sales area, and the pattern determination unit 42 calculates an average staying time and an average traffic speed in each sales area on a regular or irregular basis, and calculates the average.
- the plurality of behavior pattern data stored in the behavior pattern data storage unit 44 is updated based on the value. Since the criteria for distinguishing behavior patterns differ according to the product configuration and arrangement for each sales area, the standards are updated frequently for each sales area to reflect changes in product composition and arrangement in the behavior patterns. .
- the pattern determination unit 42 determines whether the customer behavior is passing, active, The determination result as to which of the freezes is matched is stored in the determination result storage unit 46 in association with the sales area.
- the pattern determination unit 42 stores the combinations or permutations of the sales areas where the customer's behavior matches the passing, the combinations or permutations of the sales areas that actively match, and the combinations or permutations of the sales areas that match the freeze. Store in.
- the pattern determination unit 42 determines whether or not the customer's purchasing behavior matches the type of behavior pattern! /, Based on the route information, speed information, and a plurality of behavior pattern data.
- the no-turn determination unit 42 acquires POS data as data indicating purchase content from the POS server 19 via the communication unit 22, and uses the POS data as a determination material for a customer's purchasing behavior.
- the POS data includes information on the customer's purchase such as the product name or product ID, purchase quantity, purchase price, purchase date and time, customer, and settlement area ID, and information on the customer himself.
- the customer ID is identification information given to identify a customer, for example, registered on a membership card, and the ID is input via a cash register at the time of payment.
- the checkout area ID is identification information assigned to each cash register in advance to distinguish a plurality of cash registers.
- the position coordinates of a plurality of checkout areas where each cash register is installed are defined in spatial information, and each of them is associated with a checkout area ID in advance.
- the pattern determination unit 42 associates the POS data with the route information based on the purchase date and time, the settlement area ID, and the route information. That is, the route information records which settlement area was passed and when, and the POS data is associated with the route information by referring to the purchase date and the settlement area ID included in the POS data.
- the no-turn determining unit 42 also extracts the customer ID from the POS data force, and acquires the attribute of the customer from the POS server 19 based on the customer ID.
- the POS data may include the customer attribute data itself.
- Customer attributes are factors that can distinguish types of customers, such as gender and age group, and are factors that can affect their behavior.
- the pattern determination unit 42 stores the behavior pattern determined to match in the behavior pattern data storage unit 44 in a form corresponding to the type of the attribute of the customer. Then, the pattern determination unit 42 determines the correspondence between the behavior pattern stored in the behavior pattern data storage unit 44 and the attribute. To estimate the attribute of the customer whose attribute is not known.
- the pattern determination unit 42 estimates the purchase behavior of the customer based on information on which of the plurality of sales floors the customer has passed and the type of the matching behavior pattern. Details of the determination method and the estimation method by the pattern determination unit 42 will be described later.
- the judgment result and the estimation result of the pattern judgment unit 42 are stored in the judgment result storage unit 46.
- the output processing unit 48 outputs the determination result stored in the determination result storage unit 46 through the display unit 56 or the communication unit 22. That is, the output processing unit 48 displays the determination result on the screen of the display unit 56, and transmits the determination result to the outside via the communication unit 22.
- the product information storage unit 58 stores information that can be provided to the customer regarding the product to be sold in association with the sales floor of the product and the type of behavior pattern.
- the information distribution unit 50 sends information that can be provided to the customer to the output processing unit 48 according to the type of the customer's behavior pattern determined by the pattern determination unit 42, and the output processing unit 48 transmits the information to the customer's shopping.
- the data is sent to the liquid crystal display and POS server 19 provided in the cart.
- the operation input unit 52 receives an operation by the administrator of the customer behavior analysis system 10, and the control unit 54 controls each unit of the customer behavior analysis device 20 based on the operation.
- a method of determining a behavior pattern and a method of estimating a purchase behavior by the pattern determination unit 42 will be described.
- Two examples are given as a method of determining an action pattern.
- One is (A) the approach to the sales area, and the other is to judge according to the time until exit and the stop or sudden deceleration in the sales area. This method is based on only the stay time from entry to exit to exit.
- the pattern determination unit 42 calculates, for each counter area, the staying time during which the entry into the counter area was strong even before leaving, and the effective minimum value of the day or the time zone is set to XX [seconds].
- YY [seconds] be the effective maximum value for the day or the time zone.
- the effective minimum value for the cart that purchased the product in the sales area the effective minimum value for the cart that stopped or suddenly decelerated in the sales area, the actual sales area
- the administrator selects and selects a practical minimum value or a value set by the system administrator for the cart that purchased the product after stopping or suddenly decelerating.
- the value obtained is XX [seconds] of the day or the time zone.
- the substantial maximum value of the cart that purchased the product in the sales area the substantial maximum value of the cart stopped or suddenly decelerated in the sales area, and the maximum value of the shopping area.
- the administrator selects and selects one of the practical maximum value or the value set by the system administrator.
- the value obtained is YY [seconds] for the day or the time zone.
- the pattern determination unit 42 averages the substantial minimum value XX and the substantial maximum value YY over a plurality of days or a plurality of time zones, respectively, to obtain an average value X [seconds] and an average value Y [seconds].
- These averages X and Y are the thresholds used to distinguish between passing, active, and freezing. Note that XX, YY, X, and ⁇ may be calculated for each day of the week instead of for each day or each time period.
- the pattern judging section 42 determines whether the input to the sales area is strong even before leaving.
- the interval is calculated for each sales floor area, and the actual minimum value of the day or the time zone is XX [seconds], and the actual maximum value of the day or the time zone is YY [seconds].
- the effective minimum value for the cart that purchased the product in the sales area the effective minimum value for the cart that stopped or suddenly decelerated in the sales area, the actual sales area
- the administrator selects and selects a practical minimum value or a value set by the system administrator for the cart that purchased the product after stopping or suddenly decelerating.
- the value obtained is XX [seconds] of the day or the time zone.
- the substantial maximum value of the cart that purchased the product in the sales area the substantial maximum value of the cart stopped or suddenly decelerated in the sales area, and the maximum value of the shopping area.
- the administrator selects and selects one of the practical maximum value or the value set by the system administrator.
- the value obtained is YY [seconds] for the day or the time zone.
- the pattern determination unit 42 averages the substantial minimum value XX and the substantial maximum value YY over a plurality of days or a plurality of time zones, respectively, to obtain an average value X [seconds] and an average value Y [seconds].
- These averages X and Y are the thresholds used to distinguish between passing, active, and freezing.
- the pattern determination unit 42 determines which of (1) to (5) the movement of the shopping cart matches for each sales area. In the case of (1), it is estimated that the customer simply passed through the sales area, and in the case of (2), it is estimated that the merchandise in the sales area was purchased, or at least purchased. In the case of (3), it is presumed that there is strong interest in the product in the sales area, but the product has no visibility or is lost in purchasing. In the case of (4), it is estimated that the user repeatedly freezes and is lost in the purchase. In the case of (5), it is estimated that the more times the noshing is repeated, the more lost or lost the product is. As described above, the pattern determination unit 42 can estimate the purchase behavior of the customer if the type of the behavior pattern is found.
- the pattern determination unit 42 determines the traveling direction, the moving speed, and the presence or absence of a stop for each shopping cart based on the position information and the time information.
- the pattern determination unit 42 can determine whether the vehicle has entered the counter area in the forward direction or the reverse direction based on the traveling direction.
- the pattern determination unit 42 can determine whether or not the customer is sudden, based on the moving speed of the shopping cart.
- the pattern judgment unit 42 determines whether the speed of the shopping cart It is possible to determine whether the customer has the ability to define the product or whether or not he / she is shopping, based on the absence or presence / absence of suspension.
- the pattern determination unit 42 estimates the attribute of the customer based on the behavior pattern or the purchase behavior of the customer. For example, on Saturdays, Sundays, and holidays, a customer who has a relatively long average residence time in each sales area with a slow moving speed is extracted, and the customer is estimated to be “families”. At stores that sell non-food items such as clothing and sundries, customers who pass through many or all of the men's, women's, and children's sales areas are referred to as families. ". As described above, the pattern determination unit 42 may make different determinations depending on the day of the week, the time zone, and the sales floor.
- the pattern determination unit 42 determines whether the number of nosing / freezing times, the ratio, and the time of a moving object exceeding a predetermined abnormal value standard, for example, the number of sales areas that have passed before the closing force or the closing of the store, the number of nosing or freezing.
- a predetermined abnormal value standard for example, the number of sales areas that have passed before the closing force or the closing of the store, the number of nosing or freezing.
- a moving object whose ratio of the number of sales floor areas is higher than a predetermined standard may be determined to be a suspicious individual.
- a moving object whose freeze time in a specific sales area is longer than a predetermined abnormal value or a moving object whose freeze frequency is larger than a predetermined abnormal value may be determined to be a suspicious individual.
- the pattern determination unit 42 determines that the moving object is a suspicious individual. For example, moving objects that are very long, such as staying in a store for several hours, or moving objects that have a long line of flow in a store far exceeding normal times, are suspicious individuals. It may be determined that there is.
- a moving object whose average speed is lower than a predetermined abnormal value or a moving object whose average speed is higher than a predetermined abnormal value may be determined to be a suspicious individual.
- the output processing unit 48 may transmit the determination result of the suspicious individual to, for example, a terminal carried by a security guard.
- the pattern determination unit 42 estimates factors of the sales of the product by using the cumulative behavior patterns of the customers and the determination results regarding the purchase behavior. For example, the pattern determination unit 42 can also compare the merchandise sales capabilities of each sales area with a plurality of cutting forces. The ability of customers to take actions in each sales area Aggregate them as “performance indicators” for each sales area and compare them with past aggregations, or compare aggregations between different sales floors.
- the comparison result is stored in the output processing unit 48. For example, sales and purchase times in each sales area are calculated based on the area of the sales area, the number of nosing carts, the number of active carts, the number of freezing carts, the total stay time of carts, and the total number of cart stops. The numbers divided by the number of stops, cart density, etc. are totaled and compared.
- the output processing unit 48 reads the comparison result from the determination result storage unit 46 and displays the result on the display unit 56.
- the no-turn judging unit 42 first calculates (1-1) the number of purchases, (1-2) the purchase amount, (1-3) the number of passing, the number of actives, and the number of freezes until the store closes for each sales area. Purchase probability as a ratio of the number of purchases to each, (1-4) Purchase probability as a ratio of the number of purchases to the number of stoppages, (15) Average speed, (1-6) Stay time, (17) Entering power Calculate the flow line distance to exit, (18) customer attributes, (19) number of stops, (1-10) passing ratio, active ratio, and freeze ratio.
- the “passing ratio” is, for example, a ratio of the number of passing times to the sum of the number of passing times, the number of active times, and the number of freeze times.
- the “active ratio” is, for example, the ratio of the number of active times to the sum of the number of passing times, the number of active times, and the number of freezes
- the “freeze ratio” is, for example, the sum of the number of passing times, the number of active times, and the number of freezes. Is the ratio of the number of freezes to.
- the pattern determination unit 42 totals the information of (11) to (1 10) for each shopping cart for all customers, and classifies or compares the following elements as cuts according to the user's request.
- the elements of the classification are, for example, (1—A) sales area, (1—B) time and day, (1—C) average speed, (1—D) stay time, (1—E) flow line distance, (1—E) —F) Customer attributes, (1—G) number of suspensions, (1—H) purchase price, number of purchases.
- the output processing unit 48 displays a graph in which one of (1 ⁇ A) to (l ⁇ H) is set on the X axis and one of the information of (11) to (1 10) is set on the y axis. Output to section 56 etc. Elements taken on the X and Y axes are selected by the user.
- the pattern determination unit 42 determines (2-1) the number of traffics, that is, the number of customers, (2
- the pattern determination unit 42 classifies or compares each of the information (2-1) to (2-14) for each counter area with the following elements as cuts according to the user's request.
- Classification factors include, for example, (2—A) customer status divided into passing, active, and frozen, (2—B) sales area, (2—C) hours and days, and (2—D) entry. Average speed to exit, (2—E) Stay time from entry to exit, (2—F) Flow distance from entry to sales floor area, (2—G) Customer attributes, (2— H) Number of stops, (2-1) Purchase price, Number of purchases, (2-J) Purchased product.
- the output processing unit 48 is a graph that takes any one of (2—A) to (2—J) on the X axis and any one of the information (2—1) to (2—14) on the y axis. Is output to the display 56 or the like. Elements taken on the X and Y axes are selected by the user.
- FIG. 2 schematically shows the relationship between the classification based on the state of the customer and the number of purchasers.
- the pattern judging unit 42 determines whether the customer often decides to purchase a product immediately for each sales floor area or purchases the product in consideration of the power of construction. Then, the judgment is made based on the number of noshing, the number of active, and the number of freezes. As an example, the number of purchases, nosings, actives, and freezes for each sales area are tabulated for all customers.
- the number of prospective purchasers 130 is the sum of the number of active times and the number of freezes in a certain sales area, and is positioned as at least the number of customers who are interested in and enter the product in that sales area.
- the actual number of buyers 132 is the number of customers who actually purchased products in the sales area calculated based on the POS data.
- the number of customers 136 which is the overlap between the yen of 130 prospective purchasers and the yen of 132 actual purchasers, is the number of customers who actually purchased those customers who were interested and entered the sales area.
- the number of customers 134 is the number of customers who were interested in the sales area and entered, but did not actually make a purchase. If the number of customers is large, the number of customers is out of stock, poor quality, low product power, It can be estimated that negative factors, such as high product prices, exist at the sales floor.
- the number of customers 13 8 is the number of customers who were in a strong passing It can be inferred that there is a positive factor in the sales floor, such as noticing the necessity of products on the spot. In this way, the existence of negative and positive factors can be made apparent for each sales floor area, and measures can be taken to reduce negative factors and increase positive factors according to the results.
- the pattern determination unit 42 may calculate the following performance index. For example, let a be the number of customers 134 who are interested in the sales area but make a purchase, and let b be the number 136 of customers who are interested in the sales area and make a purchase. If c is 138, the number of customers who have made purchases, and 139 is d, the number of customers 139 who have no interest in the sales floor and have made a purchase, b / (a + b) is the number of interested customers (a + b ) Is the rate that led to the purchase. If this rate is high, the quality and price of the product can be highly evaluated.
- c / (b + c) is the percentage of customers (b + c) who originally did not care about the sales floor.If this ratio is high, the in-store advertisement, product placement, campaign, etc. will be highly evaluated. be able to.
- c / (c + d) is the percentage of customers (c + d) who are interested in the sales floor and who have made a purchase. If this percentage is high, the in-store advertisement and product arrangement can be highly evaluated.
- a / (a + d) is the percentage of customers who did not purchase at the store, but were originally interested in the store, and if this ratio is high, the potential customer needs of the store are Can be highly evaluated.
- the pattern determination unit 42 estimates the cause of a poorly sold product. For example, the no-turn judging unit 42 estimates that there is a problem with the shelf layout and the arrangement method when the number of times of passing is relatively large in the sales area where the poorly sold products are displayed, and outputs information indicating the problem to the judgment result. And stored in the determination result storage unit 46 as For example, if the number of purchases is relatively small compared to the number of times of activation or the number of freezes, the pattern determination unit 42 estimates that there is a problem with the product lineup, product power, or product price, and determines information indicating that as a determination result. The result is stored in the result storage unit 46.
- the factor of the quality of purchase may be determined based on the number of stoppages of the shopping cart in each sales area. Stopping the shopping cart includes not only the actual purchase of the product but also the actual purchase that was not purchased but at least until the purchase was considered, so useful data as marketing information was obtained. Can be
- the pattern determination unit 42 performs a special sale campaign performed on a specific product or a specific sales area. You can also analyze the effect of the flyer. Although the quality of sales itself is known from POS data, it is difficult to determine the factors of sales quality from POS data. According to the present embodiment, it is possible to estimate the factor of the sales quality based on the behavior pattern of the customer. For example, before and after the campaign flyer, the pattern judging unit 42 finds that the number of visitors to the sales floor advertised in the campaign flyer and the number of interested customers (a + b) do not increase so much, If the value does not increase so much, it can be concluded that the effect of the campaign flyer was too powerful.
- the pattern determination unit 42 determines the campaign / flyer based on the number of times of passing, the number of times of active, and the number of times of freezing in the sales area of the product advertised as a special sale item or a flyer, and the number of purchases and the purchase amount for each number of times. The effect and its factor can be determined.
- the pattern determination unit 42 monitors the behavior of the shopping power of the customer who is currently shopping, in real time.
- Each performance index is displayed on the display unit 56 by the output processing unit 48.
- the administrator can grasp the performance index for each sales area in real time while looking at the screen of the display unit 56, find a sales area with poor performance, and respond immediately. For example, if the average value of the number of “active” carts in a sales area is the same as normal, but the display unit 56 shows that sales growth is worse than normal, the products in that sales area are not fresh. Or the product price is high.
- the information distribution unit 50 sends to the output processing unit 48 information for introducing products displayed in the sales area according to the sales area where the shopping cart is currently located.
- the output processing unit 48 transmits the information received from the information distribution unit 50 to the shopping cart via the wireless LAN, and transmits the information to the POS server 19 via the LAN 18.
- the information distribution unit 50 obtains product information corresponding to the type of the customer's behavior pattern from the product information storage unit 58 and sends it to the output processing unit 48. For example, information about a frozen customer or information about a passing customer may be sent, or information about a lost customer may be sent to a lost customer. Data of a store guide map may be sent as information.
- the pattern determination unit 42 refers to the POS data and the purchase history of the customer, and determines the type of the customer's route information, speed information, and behavior pattern.
- the information distribution unit 50 may determine a correspondence between the information content and the purchase content, and determine the information content and the providing method based on the determination.
- the no-turn determination unit 42 obtains the customer ID and purchase content of the customer staying in the checkout area, and associates the purchase ID with the customer route information to the determination result storage unit 46. Store as history.
- the pattern judgment unit 42 After being stored in the judgment result storage unit 46, when the same customer comes to the store again, the pattern judgment unit 42 reads out the purchase history of the customer from the judgment result storage unit 46 based on the customer ID, and performs the behavior of the customer. To analyze.
- the customer ID may be obtained, for example, by reading it from the member card into the shopping cart at the start of shopping, or by reading it from the member card in the payment area at the time of payment.
- the information distribution unit 50 may send the information to the cash register in the checkout area and print it on the customer's receipt, or, if the customer's e-mail address is already registered, e-mail It may be delivered by e-mail.
- the information to be printed on the receipt and the information to be distributed by e-mail are exemplified below.
- the pattern determination unit 42 determines that the frequency of visiting a particular sales area suddenly decreases for a customer who visits relatively frequently, the product in that sales area is purchased at another store! It can be inferred.
- the information distribution unit 50 distributes discount coupon data relating to the product in the sales area or sales promotion advertisement data relating to the product in the sales area to the customer.
- the pattern determination unit 42 determines that a customer who has stayed in the same sales area for a relatively long time, that is, a customer who has been active or frozen, has ultimately failed to purchase products in that sales area, the pattern determination unit 42 determines that It can be inferred that he or she was convinced of the product or its price. In this case, the information distributing unit 50 provides the customer with the data of the discount coupon related to the product in the sales area or the data of the sales promotion advertisement regarding the product in the sales area. If the pattern determination unit 42 determines that the number of purchased items is small despite the relatively long flow line distance or the relatively long in-store stay time, the information distribution unit 50 sends a discount coupon Data or store products Provide overall promotional advertising data to their customers.
- the information distribution unit 50 determines whether the product in that sales area is available. To provide the customer with discount coupon data or promotional advertising data on products in that sales area. If the pattern determination unit 42 determines that the customer is a customer because the flow line distance is short because the day has been short since the issuance of the membership card, the information distribution unit 50 provides the customer with discount coupon data on merchandise at the entire store. Or provide promotional advertising data for the entire store product. A sales promotion campaign is being held! Customers who are active or frozen at the special sales floor are presumed to be interested in the campaign theme. For such a customer, the information distributing unit 50 provides data of a discount coupon related to a product targeted for a similar campaign or data of a sales promotion advertisement related to the product.
- the information distributing unit 50 transmits, as information to be distributed by e-mail, for example, sales promotion of another product or a related product to a customer who has purchased a campaign target product during a specific sales promotion campaign. You may provide information about the campaign.
- the information distribution unit 50 immediately transmits sales promotion information on the product in the sales area. May be provided, or sales promotion information on products in the sales area may be provided to customers who pass through the same sales area at least a predetermined number of times.
- the promotional information sent to the customer may be information about the merchandise on the sales floor that the customer has not passed or the merchandise on the sales floor that the customer has passed.
- FIG. 3 shows the appearance of a shopping cart.
- the shopping cart 60 is provided with a cart liquid crystal display device 62.
- the cart liquid crystal display device 62 has a built-in wireless LAN communication function, and wirelessly communicates with the first access point 12, the second access point 14 and the third access point 16 in the store via the cart antenna 64.
- the cart liquid crystal display device 62 acquires the intensity of radio waves transmitted and received between the first access point 12, the second access point 14, and the third access point 16.
- the cart liquid crystal display device 62 has a liquid crystal display unit, and displays information on the product received from the customer behavior analysis device 20 on the liquid crystal display unit.
- FIG. 4 schematically shows a sales floor arrangement in a store in a virtual space defined in the space information.
- the store has a sales area for products classified as “vegetables”, “fruits”, “meat”, “fresh fish”, “confectionery”, “dry”, “retort”, seasonings, "dairy products", and “beverages”.
- the areas that customers can pass through are the entrance area 70, the first sales area 72 to the eleventh sales area 92, the first settlement area 94 to the sixth settlement area 104, and the exit area 106.
- the coordinates are defined in the spatial information.
- the entrance area 70 is an area through which the customer starts shopping at this store, and a shopping cart is prepared in this area in advance and serves as a movement start point.
- the first sales area 72 and the second sales area 74 are areas adjacent to the entrance area 70, and the first sales area 72 is associated with the “vegetable” sales area, and the second sales area 74 and the fourth sales area 78 Is associated with the “Fruit” sales floor.
- the third sales area 76 is associated with the “meat” sales area, and the fifth sales area 80 and the sixth sales area 82 are associated with the “confectionery / dry” sales area.
- the ninth sales area 88 is associated with the “fresh fish” sales area, and the seventh sales area 84 and the eighth sales area 86 are associated with the “retort 'seasoning” sales area.
- the tenth sales area 90 is associated with the “dairy” sales area, and the eleventh sales area 92 is associated with the “drinks” sales area.
- the first settlement area 94, the second settlement area 96, the third settlement area 98, the fourth settlement area 100, the fifth settlement area 102, and the sixth settlement area 104 are the first cash register, the second cash register, and the second cash register, respectively.
- the route information about the shopping cart that has passed through the first checkout area 94 is associated with the POS data recorded by the first cash register at that time.
- the exit area 106 is an area where the customer passes when ending shopping at this store, and is an end point of the movement of the shopping cart. Note that in both the entrance area 70 and the exit area 106, the store is regarded as entering when the external force passes inside the store in the heading direction, and exits when the vehicle passes from inside the store to the outside. Is considered.
- FIG. 5 schematically shows a hierarchical sales area.
- the sales floor areas are hierarchized! / ⁇
- one sales floor area is subdivided into multiple sub sales floor areas, and the relationship between sales floor areas is hierarchical.
- the sales floor area 120 is a clothing sales floor and is divided into multiple brands
- the sales floor area 120 which is the “clothing sales floor”
- “D Brand” It is divided into a number of sub-store areas 122, 124, 126, 128.
- the pattern determination unit 42 also aggregates the behavior patterns for a plurality of sub-sale areas 122, 124, 126, and 128, which are not only for aggregation of the behavior patterns for the sales area 120, so that the degree of customer preference and interest can be further improved. It can be estimated in detail.
- the relationship between the sales area areas may be hierarchized as in the example of FIG.
- the judgment result of the action pattern in the upper layer section is obtained not only by the judgment result of the action pattern in each sales floor area, a more diversified judgment result such as an overall result and a partial result can be obtained.
- An estimation result can be obtained.
- FIG. 6 schematically shows an example of a moving path of a shopping cart in a sales area.
- the sales area 110 is a horizontally long quadrilateral area, and the shopping cart enters the sales area 110 on the left side, goes back and forth inside the sales area 110 several times, and once out of the sales area 110 from the right side. Get out. Thereafter, a moving path is shown in which the sales area 110 is reentered from the right side of the sales area 110, and after a while, the right side force also goes out of the sales area 110.
- the correct traveling direction may be determined by virtue of the arrangement, and the route information generated by the route obtaining unit 34 indicates whether the shopping cart has entered in the forward direction. Whether the vehicle has entered from the opposite direction is recorded in correspondence with the sales area. In addition, enter the store area without passing active or freezing once in the sales area that passes before reaching a certain sales area, and after becoming active or freezing in that sales area, never enter the sales area through which it passes. If the player goes to the checkout area without being active or frozen, the result of the determination by the no-turn determination unit 42 is recorded as “directly” the shopping cart goes to the counter area.
- the pattern determination unit 42 records, for each shopping cart, position information and time information representing customer behavior from entering a store to leaving the store as a position attribute table.
- the entry date and time, the entry course [forward course, reverse course, direct], the settlement method [Yes, No], the exit course [forward course, reverse course], the checkout cash register number are parameters for the whole.
- the traffic line distance which is the total distance traveled until the store exits, is recorded.
- the average speed as a parameter related to speed, the average speed during the period excluding the freeze state, the maximum speed, and the number of cart stops as parameters related to whether or not to stop,
- the average cart stop time and the maximum cart stop time are recorded.
- the pattern determination unit 42 determines that the movement of the shopping cart is stopped when the movement of the shopping cart is within the predetermined radius range. For example, when the movement range from a certain positioning point is continuously within the range of a predetermined radius, the pattern determination unit 42 regards this as “stopped”. In addition, for example, when the position of the positioning point measured before one second before also stays within the range of the predetermined radius for a predetermined time or more, the pattern determination unit 42 stops this by ⁇ Stop! You can consider it! "
- the number of times of noshing, the average time of passing, the shortest time of passing, the longest time of passing, and the number of passing counter areas are further recorded as parameters relating to noshing.
- the position attribute table further records the number of active times, the average active time, the shortest active time, the longest active time, and the number of active sales area areas as active parameters.
- the position attribute table further records the number of freezes, the average freeze time, the shortest freeze time, the longest freeze time, and the number of freeze sales areas as freeze-related parameters.
- the no-turn determination unit 42 records the history of actions in the counter area where the car has passed as a cart action history table for each shopping cart.
- the cart action history table contains the sales area name, entry and exit date, exit date and time, state name (passing, active, freeze), flow distance from entry to sales floor, average speed, maximum speed, number of stops, average stop time, The longest stop time, the number of purchased products, and the total purchase price are recorded. If a shopping cart passes through the same sales area multiple times, a record of individual cart behavior history is generated each time the shopping cart passes.
- the no-turn determination unit 42 records the state in each counter area as a counter area position attribute table for each counter area and for each time zone.
- the sales area location attribute table shows the number of passing states in one sales area and time zone, the average time in the missing state, the shortest time in the passing state, the longest time in the passing state, and the passing state. The average number of stops in the state, the average purchase amount in the passing state, and the average number of purchases in the passing state are recorded.
- the sales area location attribute table contains the number of active states in one sales area and time zone, the average time of active states, the shortest time of active states, the longest time of active states, the average number of stops in active states, and the active states.
- Average purchase amount average number of active purchases, number of freezes, average time of freeze, minimum time of freeze, maximum time of freeze, average number of stops in freeze, average purchase in freeze, freeze
- the average number of purchases for the condition is also recorded.
- the entrance capacity for all customers who passed through the sales area the average distance of the flow line to the sales area, the minimum distance of the flow line, and the maximum distance to the sales area, and all customers who purchased products in the sales area
- Average line-to-line distance to exit, minimum line-to-line distance, and maximum line-to-line distance average line-to-line distance from entry to exit for all customers who stopped in that sales area, line of movement
- the minimum distance and the maximum flow line distance are also recorded.
- the sales area location attribute table includes an average traffic time, a shortest traffic time, and a longest traffic time of a customer who has purchased a product in the sales area, an average traffic time and a shortest traffic time of a customer stopped in the sales area. , The longest transit time, the average transit time when a product was purchased while stopped in the sales area, the shortest transit time, and the longest transit time.
- the XX, YY of the day or time zone and the X, Y applicable to the day or time zone are also recorded.
- the pattern determination unit 42 can estimate the following items by matching the purchase history based on the POS data with the behavior pattern of the customer.
- the pattern determination unit 42 calculates the number of purchases per stop for each sales area from the formula (number of purchases Z number of stops). It is considered that there is a strong correlation between the stoppage of the shopping cart and the purchase of the product, so if the number of purchases per stop is relatively small, it can be estimated that there is a problem with the product lineup and product power.
- the pattern determination unit 42 calculates the number of purchases per pass (passing, active, freeze) of the shopping cart for each sales area. If the number of purchases per pass is relatively small, factors such as improper product placement, low attractiveness of products, inappropriate placement of sales floors, and inappropriate placement of advertisements are estimated. . ) (3) The pattern determination unit 42 calculates the number of purchases and the purchase amount per shopping cart that has been “passed” for each sales floor area. If the number of purchases and the amount of purchase are large, it can be estimated that attractive products are easily arranged in hand.
- the pattern determination unit 42 calculates the number of purchases and the purchase price per shopping cart set to “active” for each sales area. If the number of purchases or the purchase price is low, factors such as improper product placement, low product appeal, and high product prices can be estimated.
- the pattern determination unit 42 calculates the number of purchases and the purchase amount per shopping cart that has been “frozen” for each sales floor area. If the number of purchases or the purchase price is low, it is highly probable that despite the high demand, the product sales were missed due to improper product placement or out of stock.
- the pattern determination unit 42 calculates the number of purchases and the purchase amount per shopping cart that has been “re-frozen” for each sales floor area. If the number of purchases or the purchase price is low, it is presumed that problems such as improper product placement or out of stock have occurred.
- the pattern determination unit 42 calculates the number of shopping carts that have left the store without purchasing anything in “active” despite being “direct”. In this case, it is estimated that the product was out of stock.
- the pattern determination unit 42 calculates the number of shopping carts that are “direct” and have left the store without purchasing anything despite having “frozen”. In this case, it is estimated that the product lineup was insufficient.
- the pattern determination unit 42 calculates the number of shopping carts that have moved out of the store without purchasing anything after moving in the “forward direction”. In this case, problems such as product assortment, product quality, and product placement throughout the store are estimated.
- the pattern judging section 42 once enters a ⁇ freeze '' in a certain sales area, and then enters the same sales area again to become ⁇ active '' or ⁇ freeze ''. It is presumed that the customer returned the goods or made a purchase decision.
- the pattern determination unit 42 estimates the attributes and status of the customer based on the customer's behavior pattern and purchase behavior. Specifically, (1) day of the week and time zone [weekdays, holidays, 11:00 to 17:00, Etc.), (2) Entering course [Forward course, reverse course, direct], (3) Checkout [Yes, No], (4) Closing course [Forward course, reverse course], (5) Store stay time [High, Middle, Low], (6) Average speed or average speed during periods excluding freeze state [High, Middle, Low], (7) Cart stop frequency [High, Middle, Low], (8) Cart stop Average time [High, Middle, Low], (9) Passing frequency, (10) Active frequency [High, Middle, Low], (11) Freeze frequency [High, Middle, Low], (12) Refreezing probability [High, Middle, Low], (1 3) Re-passing probability [High, Middle, Low], (14) Active or frozen sales area combination or permutation [Food, confectionery, meat, fresh fish, vegetables, Does at least six of dairy products, dry matter, and seasonings be included?), (15) Total flow distance from
- the pattern determination unit 42 estimates the attribute of the customer as described below with reference to the attribute pattern data.
- the (2) entry course and the (4) exit course are determined in advance as to whether or not the expected entry and exit courses have passed.
- the re-freezing probability is calculated by (number of freezes) Z (number of sales floor areas that have been frozen).
- the re-passing probability is calculated by (number of times of passing) Z (the number of sales floor areas that have been passed).
- the pattern determination unit 42 estimates that the customer's attribute is “shopping with family on holidays”. Note that “High” and “Middl ej“ Low ”correspond to, for example, a case where the distribution of customers is divided into three equal parts.
- one-way operation is performed between a mobile customer and a plurality of wireless LAN base stations. Measures the time from transmitting a radio wave to receiving the return radio wave from the other, and performs positioning based on the difference in the length of time measured at each base station. This is different from the first embodiment in which the position of the moving object is detected using the difference in the radio wave intensity at each base station.
- the description will focus on the differences from the first embodiment, and the description of the common points will be omitted.
- FIG. 7 is a functional block diagram illustrating the configuration of the customer behavior analysis system according to the second embodiment.
- the customer behavior analysis system 10 is different from the customer behavior analysis system 10 according to the first embodiment including the intensity acquisition unit 24 in that the customer behavior analysis system 10 includes a time value acquisition unit 140.
- a plurality of wireless LAN base stations within a wireless communication range of a communication device provided in a shopping cart for example, a first access point 12, a second access point 14, and a third access point 16 transmit radio signals. Force Measures the time until the wireless signal as a reply is also received by the communication device, and transmits the time value to the customer behavior analysis system 10.
- the wireless communication system used in this embodiment may be UWB (Ultra Wide Band).
- the time value acquisition unit 140 acquires the time value of the time required for transmission and reception with the shopping cart for each base station.
- the position recognition unit 26 also calculates the distance between each base station and the shopping cart as well as the time value, calculates the position of the shopping cart based on the distance of at least three base stations, and generates position information. Then, time information indicating the time at which the position was calculated is generated.
- the position detection method may be a TOA (Time of Arrival) method or a TDOA (Time Difference of Arrival) method.
- the position information and the time information are stored in the position information storage unit 28.
- the position information and the time information of the shopping cart can be detected in the same manner as in the first embodiment, and the same analysis as in the first embodiment can be performed based on the information. Note that it is also possible to detect which shopping cart is used by detecting the ID of the wireless LAN communication device provided in the shopping cart of the customer.
- an IC tag is embedded in a shopping cart, a shopping basket, a member card, a mobile phone, a mobile terminal, or the like carried by a customer, and a plurality of reader / writers are used as wireless communication devices capable of wirelessly communicating with the IC tag. Is used.
- the position of the customer is detected by information indicating with which reader / writer the IC tag has wirelessly communicated. For example, a number of reader / writers are installed in stores, each with its own communication area, and held by customers.
- the customer's position is determined by detecting which reader / writer's communication area the IC tag is passing through. This is different from the first embodiment in which the position of the moving object is detected using the difference in the radio wave intensity at each base station.
- a description will be given focusing on differences from the first embodiment.
- FIG. 8 is a functional block diagram illustrating the configuration of the customer behavior analysis system according to the third embodiment.
- the first reader / writer 142, the second reader / writer 144, and the third reader / writer 146 transmit to the customer behavior analysis system 10 reception information indicating that a customer carrying an IC tag has passed in their respective communication areas. I do.
- the reception information acquisition unit 148 acquires reception information from the first reader / writer 142, the second reader / writer 144, and the third reader / writer 146.
- the position recognition unit 26 generates position information indicating the position of the customer holding the IC tag according to whether any of the reader / writer powers has received the reception information, generates time information indicating the timing, and sends the information to the position information storage unit 28. Store.
- the location information and the time information of the customer can be detected. It is also possible to detect which shopping cart or the like is used by detecting the ID of the IC tag embedded in the personal belongings such as the shopping cart of the customer.
- the customer behavior analysis system 10 in the present embodiment is connected to a first camera 152, a second camera 154, and a third camera 156, and includes a reception information acquisition unit 148.
- a plurality of areas included in a target space are continuously photographed by a plurality of cameras at a predetermined angle such as a bird's-eye view, and a color changing force in a plurality of obtained continuous images is a moving object. Is detected, and the position of the object is recognized. This is different from the first embodiment in which the position of the moving object is detected using the difference in the radio wave intensity at each base station.
- the following description focuses on differences from the first embodiment, and a description of common points is omitted.
- FIG. 9 is a functional block diagram illustrating the configuration of the customer behavior analysis system according to the fourth embodiment.
- At least one camera is installed at each sales floor area in the store so that it can capture a predetermined angle force such as overhead view.
- Each of the first camera 152, the second camera 154, and the third camera 156 is an example of a camera that can also take a bird's-eye view.
- the first camera 152, the second camera 154, and the third camera 156 continuously photograph the sales area, which is the photographing area, from a bird's-eye view.
- the A plurality of continuous images taken by the first camera 152, the second camera 154, and the third camera 156 are transmitted to the customer behavior analysis system 10 as needed.
- the image acquisition unit 150 acquires continuous images from the first camera 152, the second camera 154, and the third camera 156.
- the position recognition unit 26 detects a moving object from a continuous image, recognizes the position of the moving object to generate position information, generates time information indicating the time, and sends each to the position information storage unit 28. Store. According to the above method, the location information and the time information of the customer can be detected in the same manner as in the first embodiment, and the same analysis as in the first embodiment can be performed based on the information.
- FIG. 10 exemplifies an image obtained by photographing a certain sales area from above. If the sales floor image 180 in this figure is captured in a plane, the image of the customer, which is a mobile object, will appear diagonally unless it is directly below the camera. As a result, a customer directly under the camera does not see any parts other than the head and shoulders, whereas a customer obliquely sees not only the head and shoulders but also the whole body. The appearance is completely different depending on the customer's location, and the head is closer to the camera than the feet, which are too close to the camera, making it difficult to accurately grasp the customer's location.
- a rectangular frame 183 in which the moving body 182 is inscribed is set on the sales floor image 180, and the frame center point 184 of the rectangular frame 183 is set as the position of the moving body 182. I reckon.
- the actual position of the moving body 182 should be originally the foot position 186, and the frame center point 184 is shifted from the foot position 186.
- FIG. 11 schematically shows the shooting situation of the counter image 180 in FIG. 10 from the side.
- a camera 204 is installed on the ceiling 200, and the camera 204 photographs the direction of the floor 202.
- the moving object 182 walking on the floor 202 moves from the image center point 188 toward the edge, and when the camera 204 takes an image of the moving object 182, the photographing angle of the moving object 182 is Assuming that the floor 202 is the sales floor image 180, the moving object 182 is projected obliquely to the area 206. Therefore, the moving body 182 also has a wider force than its vertical force, and the center of the width is farther from the actual position of the moving body 182. In addition, since the part closer to the camera 204 is larger, the head of the customer, which is the moving body 182, is larger than the foot.
- FIG. 12 is a diagram in which a cylinder model is applied to the sales floor image of FIG.
- the moving object 182 shown in the sales floor image 180 in Fig. 10 has been replaced with a cylindrical body 192.
- the position recognition unit 26 sets a cylindrical axis 194 that is a straight line connecting the image center point 188 and the frame center point 184 of the rectangular frame 183, and sets a cylindrical body 192 having the cylindrical axis 194 as an axis.
- the bottom surface 196 of the cylindrical body 192 is set to, for example, 50 cm as a radius in the real world. Since the appearance and size of the cylindrical body 192 change depending on the distance, in the sales floor image 180, the bottom surface 196 is calculated as an ellipse having a major axis radius equivalent to 50 cm. An arbitrary value can be set for the radius of the ellipse.
- the bottom surface 196 is set such that the center point 190 of the bottom surface is located on the cylindrical axis 194 and the circumferential line of the bottom surface 196 contacts the rectangular frame 183.
- the upper surface 198 of the cylinder 192 is drawn as an ellipse whose center point is located on the cylinder axis 194 and whose circumferential line abuts the rectangular frame 183.
- the head of the moving body 182 is larger than that of the feet, and therefore, as shown in FIG. 12, the cylindrical body 192 is set so that the upper surface 198 is larger than the bottom surface 196.
- the bottom center point 190 is regarded as the position of the foot of the moving body 182. Accordingly, even when the moving object is photographed obliquely, the position recognition unit 26 can acquire more accurate position information.
- the force to detect the position of the foot is explained, especially the process of detecting the position of the foot without correcting the image. May be.
- the counter image 180 may be corrected so that the bottom surface 196 changes from an ellipse to a perfect circle. Since the aberration correction method is known, the description thereof will be omitted.
- the position recognition unit 26 assigns an ID to the detected moving object, and recognizes position information and a position detection time in association with the ID. As long as the position recognizing unit 26 continuously recognizes the same moving object from the image in the same sales area, it continues to assign the same ID to the moving object.
- the position information initially recognized is the position coordinates of the frame center point 184 of the rectangular frame 183 shown in FIG. 10, and the coordinates are only relative coordinates in the sales floor image 180.
- a straight line connecting the image center point 188 and the frame center point 184 is assumed to be a cylinder axis 194.
- a cylindrical body 1 having a bottom surface 196 corresponding to a radius of 50 cm on the cylindrical axis 194 corresponding to a radius of 50 cm from the frame center point 184 to the image center point 188 side, and having an upper surface 198 abutting on the opposite side to the square frame 183.
- the relative coordinates of the bottom center point 190 of the bottom surface 196 are taken as the position of the moving object. Detect as information.
- the position recognition unit 26 detects a moving object in the image for each camera. Since different IDs are assigned to the cameras even for the same moving object, the position recognition unit 26 determines the correspondence between the IDs for the same moving object based on the arrangement of the images from the cameras. Thereby, the position recognition unit 26 recognizes the flow line of each mobile in the store.
- the shooting ranges partially overlap between adjacent cameras, there is a possibility that a moving object that has entered the overlapping area is simultaneously displayed in two images.
- the number of IDs that also generate overlapping area powers is a multiple of two. Divide all IDs shown in the overlapping area into pairs, calculate the distance between moving objects in the pair, and sum the distances of each pair. Then, the distance of each pair is summed in the same manner by changing the combination of the pairs. Assuming all possible combinations of such pairs, the sum of the distances is the smallest V, and the combination is the optimal combination, and the mobile units of each pair are determined to be the same mobile unit.
- FIG. 13 schematically shows a method for detecting the same moving object in overlapping imaging ranges.
- the first image 262 and the second image 264 each have an overlapping area 260 because the shooting ranges partially overlap.
- one moving object is shown in an area other than the overlapping area 260 of the first image 262, whereas four moving objects 252 to 258 force S are shown in the overlapping area 260.
- the overlapping region 260 is a portion where the shooting ranges of the two images overlap, the number of moving objects appearing in this region is a multiple of two. Therefore, the second mobile unit 252, the third mobile unit 254, the fourth mobile unit 256, and the fifth mobile unit 258 appearing in the overlap area 260 are actually recognized as two mobile units, each of which is doubled. It's just too much.
- the position recognizing unit 26 divides the moving object appearing in the overlapping area 260 into a plurality of pairs, and determines the method of dividing the pair having the smallest value when calculating the sum of the distances for each pair. judge.
- these moving bodies are arranged at substantially equal intervals in the order of the second moving body 252, the third moving body 254, the fourth moving body 256, and the fifth moving body 258. Therefore, when the pair is divided into a pair of the second mobile unit 252 and the third mobile unit 254 and a pair of the fourth mobile unit 256 and the fifth mobile unit 258, the total value of the distances becomes minimum.
- the moving objects appearing in the same image are all separate moving objects, so it is already grasped clearly. In this case, the second mobile unit 252 and the fourth mobile unit 256 are not paired, and the third mobile unit 254 and the fifth mobile unit 258 are not paired.
- the position recognizing unit 26 determines whether the position force of the first mobile unit 250 is any of the speed and the moving direction to the positions of the second to fifth mobile units 252 to 258, and the position of the first mobile unit 250. The difference between the speed and the moving direction up to is calculated, and the method of dividing the pair having the smallest total value when the total value of the differences is calculated for a plurality of pairs is further determined. In addition, the position recognition unit 26 calculates the total value of values obtained by arbitrarily combining some of the parameters such as the distance between the moving objects, the speed of the moving object, and the moving direction, and calculates the total value of the values. You may decide how to split the pair.
- FIG. 14 schematically shows an example of a shooting range of each camera in a store.
- the first shooting range 320 and the second shooting range 322 are shooting ranges corresponding to the first image 262 and the second image 264 in FIG.
- the first imaging range 320 and the second imaging range 322 have a positional relationship aligned with each other, and their respective coordinate axes are parallel.
- the second shooting range 322 and the third shooting range 324 are not parallel to each other in coordinate axes.
- the third shooting range 324 is inclined obliquely with respect to the second shooting range 322.
- the position recognition unit 26 converts the coordinates in the image of each imaging range into absolute coordinates, which are the spatial coordinates of the entire store, so that the in-store Position can be recognized.
- the customer behavior analysis system 10 is connected to the first ultrasonic acquisition device 270, the second ultrasonic acquisition device 272, and the third ultrasonic acquisition device 274, and includes a reception information acquisition unit 148.
- the first ultrasonic acquisition device 270, the second ultrasonic acquisition device 272, and the third ultrasonic acquisition device 274 acquire the ultrasonic waves to which the moving force is also transmitted in a plurality of areas included in the target space, and obtain the ultrasonic waves.
- the position of the moving object is detected from the reception angle of the moving object. It is assumed that each mobile unit has an ultrasonic transmitter.
- the mobile object is a shopping cart of a customer in a store, and the shopping cart includes an ultrasonic transmitter.
- the customer behavior analysis system 10 according to the present embodiment is different from the customer behavior analysis system 10 according to the first embodiment in which the position of a mobile body is detected using a difference in radio field intensity between base stations.
- the following description focuses on the differences from the first embodiment, and omits the common points.
- FIG. 15 is a functional block diagram illustrating the configuration of the customer behavior analysis system according to the fifth embodiment.
- At least one ultrasonic acquisition device will be installed at a high location such as a ceiling in each of the multiple sales areas in the store.
- the first ultrasonic acquisition device 270, the second ultrasonic acquisition device 272, and the third ultrasonic acquisition device 274 in the figure are examples of ultrasonic acquisition devices installed on the ceiling, respectively. Are received continuously.
- the first ultrasound acquisition device 270, the second ultrasound acquisition device 272, and the third ultrasound acquisition device 274 transmit the reception angle of the received ultrasound to the reception information acquisition unit 148.
- the position recognizing unit 26 detects the moving object from the reception angle of the ultrasonic wave, recognizes the position of the moving object to generate position information, and generates time information indicating the time to generate the position information. It is stored in the position information storage unit 28. Since a method for detecting the ultrasonic wave receiving angle and a method for detecting the position of the moving object based on the ultrasonic wave receiving angle are known, description thereof will be omitted.
- a geomagnetic sensor and an acceleration sensor are mounted on a shopping cart of a customer, which is a mobile body, and the flow line of the force near the entrance of the store can be recognized by tracking the geomagnetic sensor and the acceleration sensor.
- the direction information, which is the detection result of the traveling direction by the geomagnetic sensor, and the acceleration information, which is the detection result of the acceleration by the acceleration sensor, are transmitted to the customer behavior analysis system 10 by the wireless communication device mounted on the shopping cart.
- the customer behavior analysis system 10 uses the direction information and acceleration information received from the shopping cart. Recognize the customer traffic flow based on the store entrance power.
- the customer behavior analysis system 10 does not need to constantly receive direction information and acceleration information from the shopping cart.Entrance force when the shopping cart reaches the checkout area All direction information and acceleration information indicating the flow line to the checkout area Are received together. Therefore, at least one base station in the store that receives information from the shopping cart by wireless communication is sufficient. As described above, since the customer behavior analysis system 10 in the present embodiment detects information on the position with the sensor on the mobile unit side, the position of the mobile unit is detected using the difference in the radio wave intensity at each base station. This is different from the customer behavior analysis system 10 of Example 1. Hereinafter, differences from the first embodiment will be mainly described, and description of common points will be omitted.
- Correction points may be provided at a plurality of locations in a store.
- An IC tag is installed at each correction point.
- the position recognizing unit 26 rewrites the position information of the moving object at that time with a predetermined value indicating the position of the correction point.
- FIG. 16 is a functional block diagram illustrating the configuration of the customer behavior analysis system according to the sixth embodiment.
- At least one base station will be installed in the store.
- the access point 280 in the figure is an example of a base station installed in a store, receives direction information and acceleration information from the sales area or the settlement area, and transmits them to the reception information acquisition unit 148.
- the position recognizing unit 26 Based on the direction information and the acceleration information, the position recognizing unit 26 recognizes the flow line of the moving object based on the position of the store entrance, which is the detection start point, to generate position information, and generates time information indicating the time. Are generated and stored in the position information storage unit 28.
- the position recognition unit 26 may further store the direction information and the acceleration information received from the reception information acquisition unit 148 in the position information storage unit 28.
- the speed acquisition unit 32 may calculate the speed of the moving object by integrating the acceleration information stored in the position information storage unit 28.
- FIG. 17 shows the relationship between the stay time and the number of customers in the sales area. Sales floor shown in this figure The relationship between the length of stay in the area and the number of customers is only an example, but it is assumed that the relationship generally looks like this figure.
- the horizontal axis shows the customer's stay time in a certain sales area
- the vertical axis shows the number of customers.
- the number of staying customers 160 indicates the number of customers for each staying time in a certain sales area in one day
- the number of purchasing customers 162 indicates the number of customers who actually purchased products in that sales area among the number of customers for each staying time. Show.
- the total number of customers is longer for customers who stay relatively short and less for customers who stay longer.
- the shorter the staying time the smaller the number of customers.
- the number of customers increases as the staying time increases, and the number of customers starts to decrease as the staying time increases.
- the area of the first range 164 indicates the sum total of the number of customers who have not purchased products in the sales area area among the customers whose stay time is shorter than the first time value XX [seconds].
- the area of the second range 166 indicates the total number of customers who have purchased products in the sales area area among the customers whose stay time is shorter than the first time value XX.
- the area of the third range 168 indicates the total number of customers who stayed longer than the second time value YY [seconds] who did not purchase products in the sales area.
- the area of the fourth range 170 indicates the sum of the number of customers who have purchased products in the sales area among the customers who have stayed longer than the second time value YY.
- the first time value XX is a value such that the area ratio between the first range 164 and the second range 166 becomes a predetermined ratio.
- the first time value XX is a value such that the ratio of customers who have made a strong purchase of goods and customers who have made a purchase among the customers whose stay time is shorter than that value is a predetermined ratio.
- the area ratio between the first range 164 and the second range 166 is, for example, 10: 1, and is set to an optimal value based on experiments and verification.
- the second time value YY is a value such that the area ratio between the third range 168 and the fourth range 170 becomes a predetermined ratio.
- the second time value YY is a value such that the ratio of customers who have purchased products and customers who have purchased products among the customers who stay longer than that value is a predetermined ratio.
- the area ratio between the third range 168 and the fourth range 170 is, for example, 1: 1 and is set to an optimal value based on experimental verification.
- the customer behavior analysis system 10 is common to the other embodiments in that any one of the position detection methods according to the first to sixth embodiments is adopted as a basic configuration. Is different from other examples in that it analyzes the behavior of employees other than customers at facilities such as
- each employee carries a wireless communication device or an IC tag and communicates with a base station or a reader / writer on the customer behavior analysis system 10 side.
- the position is recognized.
- the position detection method of the fourth embodiment is employed, the position of the employee is recognized through an image taken by a camera.
- the position of the employee is recognized through transmission and reception of ultrasonic waves.
- the position detection method of the sixth embodiment the position of the employee is recognized through the detection results of the geomagnetic sensor and the acceleration sensor.
- differences from the first to sixth embodiments will be mainly described, and description of common points will be omitted.
- the no-turn determining unit 42 can calculate the following parameter values based on the route information and display them on the screen. For example, the pattern determination unit 42 determines, for each employee, the entry time, exit time, the line flow distance to exit, the number of stops from entry to exit, and the entry power Calculate the stop time. The no-turn determination unit 42 can also calculate the stay time, the number of stops, and the stop time for each sales floor area for each employee. The values of these parameters are displayed on the screen through the operation of the administrator.
- the pattern determination unit 42 determines the status of the employee as “Waiting”, “Outside the store”, “Approach from the customer”, “From the employee”, based on the relationship between the employee and the customer, such as the position, distance, speed, and orientation. Judgment is made among the following: “approach”, “negotiation”, “payment”, and “move out of sales area”.
- the Noturn determination unit 42 calculates the time of the determined state for each employee, every month, every day of the week, every day, and every time period. “Waiting” refers to a state where the user remains in the sales area in charge.
- “Outside the sales floor” refers to the state where the customer is out of the sales floor area in charge, excluding the “customer power approach”, “approach from employee”, “negotiations” and “payment”. “Approaching customer power” refers to a situation in which a customer approaches a predetermined approaching distance, for example, within 60 cm, of an employee who is “waiting” or “outside the store”, and that distance continues for a predetermined time. “Approach from employee” refers to a situation where an employee “waiting” or “outside the sales floor” approaches a predetermined approaching distance, such as within 60 cm from the customer, and the approaching distance continues for a predetermined time.
- the pattern determination unit 42 compares the calculated value based on the motion vector of the customer or the employee, based on which of the two approaches. It may be determined from the following. For example, let V be the employee vector and V be the customer vector.
- V cos 0 is greater than V cos 0
- V cos 0 tV cos ⁇ may be equal
- the direction value is a positive value. If the approach between the employee and the customer continues even after the predetermined time has elapsed, the pattern determination unit 42 determines that the state has shifted to the “negotiation” state, and if not, the “wait” or “out of sales area”. Is determined to have been made. After transitioning to the "negotiation” state, if at least one of the employee and customer moves to the checkout area, and the POS data power also recognizes that the checkout was made at that time, then the "negotiation" Is completed and it is determined to be in the state of “payment”.
- the pattern determining unit 42 determines that the “negotiation” has been completed when the employee and the customer who have been in the “negotiation” state have been separated by a predetermined distance or more and the state has elapsed for a predetermined time, and the “wait” or “wait” It is determined that the state has shifted to "out of the store". Therefore, the employee who is in the "negotiation” state does not shift to the "payment", "waiting", or "outside the sales area” state.
- the pattern determination unit 42 determines that the “payment” has been completed if the distance between the customer and the employee is longer than a predetermined distance and the state continues for a predetermined time.
- the no-turn determination unit 42 determines the number of times, the shortest time, and the longest time for each employee's behavioral status such as ⁇ waiting, '' ⁇ approach from customer, '' ⁇ approach from employee, '' ⁇ negotiation, '' and ⁇ payment. '' , The average time, and the time ratio of each state in the total working hours are calculated.
- the pattern determination unit 42 calculates a contract probability for the number of negotiations for each employee.
- the number of negotiations is recognized from the route information of the employee and the relationship between the employee and the customer, such as the position, distance, speed, and orientation.
- the number of closed deals is the employee or customer's route information and the POS data of the customer with whom the negotiation was conducted. Recognize power.
- the no-turn determination unit 42 determines the length of stay in each sales area for each customer by (1) when employees are absent, (2) when all employees are in service, and (3) when employees are not in service. When there is more than one person, calculate each of the three patterns. Each of (1) to (3) is summed up with active or frozen customers passing through the sales area. The no-turn determination unit 42 determines, for each sales area, all of the stay time in that sales area. Calculate the total number of customers who have fallen into force or (2) and the total length of their stay as the number of employees who can not respond in the sales area. This value is used as one indicator of sales opportunity loss. As a result, it is possible to grasp the situation where the employee is absent or waiting for a customer in the sales floor area.
- the customer behavior analysis system 10 can also be applied to management of the entire store.
- the no-turn determination unit 42 includes, for example, the number of visitors, the average stay time from entry to exit, the sales, the average speed excluding the average speed or freeze, the average flow line distance, the average number of stops, the passing ratio, the active ratio, Freeze ratio, customer density in checkout area, longest wait time in checkout area, average wait time in checkout area, purchase probability and average purchase amount in active, purchase probability and average purchase amount in passing, purchase probability in freeze and Parameters such as the average purchase price can also be calculated for each store. Parameters such as a minimum value, an average value, and a maximum value of the ratio of the number of customers and the number of employees per unit area may be calculated for each store.
- FIG. 18 shows an example of a screen displaying a list of the length of time for each of the employee's behavioral states.
- the screen 400 displays the status of each employee, such as “Waiting”, “Outside the sales floor”, “Approach from the customer”, “Approach from the employee”, “Business negotiation”, “Checkout”, and “Move out of the sales area”.
- the length of time spent is indicated by the length of the bar graph.
- the output processing unit 48 can also display the length of time in each of these states, for example, for each employee.
- the output processing unit 48 displays the time at which the employee stayed in each sales area on a monthly, weekly, daily, day, and time zone basis. Display on 56.
- the output processing unit 48 displays, on the display unit 56, a table in which, for example, the stay time for each sales area is set on the horizontal axis and the type of sales area is set on the vertical axis, based on the operation of the administrator.
- a shopping cart used by a customer as a “mobile object” has been mainly exemplified.
- the “moving object” in the modified example may be a shopping basket used by a customer, a communication device such as a mobile phone or a mobile terminal owned by the customer or an employee, or an IC card. Or a medium with a communication function such as a ticket with an IC chip.
- a IC tag such as an IC card or an IC chip
- the IC tag may be an active IC tag having a built-in power supply or a noisy IC tag supplied with an external power supply.
- a system for calculating the position and speed of a mobile object in a space in a store in order to analyze the behavior of the employee or employee has been exemplified.
- the system may be configured as a system that analyzes the behavior of a visitor moving in a space within an entertainment facility such as a shopping district, an amusement park, a theme park, or a zoo.
- the system may be configured as a system for analyzing the movement of players in a sports facility such as a baseball field, a soccer field, and a rugby field.
- an IC tag is embedded in a shopping cart, a shopping basket, a membership card, a mobile phone, a mobile terminal, or the like carried by a customer, and a number of reader / writers are installed in a store.
- the configuration for communication has been described.
- a reader / writer is built in the shopping cart, shopping basket, mobile phone, etc. carried by the customer, a number of IC tags are installed in the store, and these communicate with each other to detect the position of the customer.
- the configuration may be as follows.
- the imaging by the camera described in the fourth embodiment may be a special imaging using sensors such as an ultrasonic wave, a microwave, an infrared ray, and an electromagnetic wave, in addition to the imaging using a CCD sensor or a CMOS sensor.
- the method of detecting the position by the angle of the radio wave in the communication between the transmitter and the receiver of the ultrasonic wave has been described, but the time required for transmitting and receiving the ultrasonic wave between the moving object and the receiver is reduced.
- a configuration for detecting the position of the moving object in response thereto may be employed.
- useful information can be provided by analyzing the behavior of a moving object in a space.
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Abstract
Description
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US11688157B2 (en) | 2020-04-23 | 2023-06-27 | International Business Machines Corporation | Shopper analysis using an acceleration sensor and imaging |
JP6873448B1 (ja) * | 2020-07-29 | 2021-05-19 | 株式会社セオン | Ec化装置 |
JP2022025257A (ja) * | 2020-07-29 | 2022-02-10 | 株式会社セオン | Ec化装置 |
JP7336613B1 (ja) * | 2023-02-28 | 2023-08-31 | Tis株式会社 | 情報処理システム、情報処理方法、及びプログラム |
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