Purchase promotion device and purchase promotion method

Abstract

Identify and provide information that reflects the customer's purchasing potential. [Solution] The purchase promotion device comprises a communication device, a storage device, and a processing device. The communication device acquires customer information from an application on a mobile terminal for customers visiting a commercial facility or store. The storage device stores the customer information. Based on customer information regarding the customer's purpose of visit on the day or the customer's behavioral history on the day, the device calculates a purchase activity level, which is an indicator of the customer's temporary willingness to purchase. Based on customer information regarding the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application, the device calculates a potential purchase level, which is an indicator of the customer's consistent willingness to purchase. Based on the purchase activity level and the potential purchase level, the device calculates a purchase probability level, which is an indicator of the probability that the customer will purchase the product.

Description

Technical Field

[0001] This application relates to an apparatus or method for promoting customer purchases in a store.

Background Art

[0002] Patent Document 1 discloses a sales support apparatus. The sales support apparatus is a wearable terminal for store clerks and includes an imaging device and a head-mounted display. The imaging device captures and recognizes the face of a customer. The member information of the customer recognized using the imaging device is displayed on the head-mounted display. The member information includes the customer's past purchase history. As a result, since the customer's purchase history can be confirmed while continuing customer service, products suitable for the customer's preferences can be smoothly proposed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the sales support apparatus of Patent Document 1, it is only possible to confirm the customer's purchase history, and the customer's purchase probability cannot be specified. Therefore, there is a possibility of missing customers with a high purchase probability due to the inability to sufficiently respond to customers with a high purchase probability.

[0005] This application has been made in view of the above circumstances, and its main object is to specify and provide the customer's purchase probability.

Means for Solving the Problems

[0006] The problems to be solved by this application are as described above. Next, the means for solving this problem and its effects will be described.

[0007] According to a first aspect of this application, a purchase promotion device is provided having the following configuration: The purchase promotion device comprises a communication device, a storage device, and a processing device. The communication device acquires customer information from an application on a mobile terminal for customers visiting a commercial facility or store. The storage device stores the customer information. Based on the customer information relating to the customer's purpose of visit on that day or the customer's behavioral history on that day, a purchase activity level, which is an indicator of the customer's temporary willingness to purchase, is calculated. Based on the customer information relating to the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application, a potential purchase level, which is an indicator of the customer's regular willingness to purchase, is calculated. Based on the purchase activity level and the potential purchase level, a purchase probability level, which is an indicator of the probability that the customer will purchase a product, is calculated.

[0008] A second aspect of this application provides a method for promoting purchases, which involves having a computer perform the following processes: 1. Obtain customer information from a mobile terminal application for customers visiting a commercial facility or store. 2. Store the customer information. 3. Calculate a purchase activity level, an indicator of the customer's temporary willingness to purchase, based on the customer information relating to the customer's purpose of visit or their behavioral history for the day. 4. Calculate a potential purchase level, an indicator of the customer's long-term willingness to purchase, based on the customer information relating to the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application. 5. Calculate a purchase probability level, an indicator of the customer's probability of purchasing a product, based on the purchase activity level and the potential purchase level. [Effects of the Invention]

[0009] According to this application, it is possible to identify and provide the customer's purchasing potential. [Brief explanation of the drawing]

[0010] [Figure 1] Block diagram of the management system. [Figure 2] A flowchart for mobile devices. [Figure 3]A diagram showing examples of questions asked upon arrival. [Figure 4] A flowchart illustrating the process for calculating purchase probability. [Figure 5] Purchase activity checklist and potential purchase activity checklist. [Figure 6] A flowchart illustrating the process of creating and updating the first customer map based on purchase potential. [Figure 7] A diagram showing an example of the first customer map. [Figure 8] A flowchart illustrating the process of issuing electronic coupons based on purchase probability. [Figure 9] A flowchart illustrating the process of creating a second customer map by calculating response priority based on purchase probability and other information. [Figure 10] A diagram showing an example of a second customer map. [Modes for carrying out the invention]

[0011] Next, embodiments of this application will be described with reference to the drawings. First, the configuration of the management system 1 will be described with reference to Figure 1.

[0012] Management System 1 is a system for managing stores or commercial facilities. A commercial facility is a facility that includes multiple stores, specifically a department store, shopping center, outlet mall, or event facility. The facility is not limited to a single building and may include multiple buildings. Outdoor venues, including temporary tents, also qualify as facilities. As shown in Figure 1, Management System 1 includes a server 10, multiple mobile terminals 20, and multiple store terminals 30. If the management system 1 is managing a single store, then the store terminals 30 provided by Management System 1 will also be single.

[0013] Server 10 may be located within a facility or store, or it may be located on the cloud. Server 10 comprises a communication device 11, a storage device 12, and a processing device 13. Although only one server 10 is shown in Figure 1, the management system 1 may include multiple servers 10.

[0014] The communication device 11 is a wired communication module connected to the internet via a router. The storage device 12 is an HDD, SSD, or flash memory, etc., capable of storing data. The data stored in the storage device 12 includes programs and control data for performing the functions of the management system 1. The processing device 13 is, for example, a CPU, which can perform various processes by executing the programs stored in the storage device 12.

[0015] Mobile terminal 20 is a device owned by a visitor to the facility. Mobile terminal 20 is a smartphone, mobile phone, tablet, notebook PC, or wearable device. Visitors are users who receive various services provided by management system 1. Hereinafter, visitors to the facility who use management system 1 will be referred to as "users". However, when focusing on the purchase of goods, they may be referred to as "customers" instead of "users". Mobile terminal 20 comprises a communication device 21, a storage device 22, a processing device 23, a display 24, and a location detection device 25.

[0016] The communication device 21 is a wireless communication module and is connected to the Internet via a wireless LAN or a mobile communication line. Therefore, the communication device 11 of the server 10 and the communication device 21 of the mobile terminal 20 can communicate with each other. The storage device 22 is an HDD, SSD, flash memory, etc., and can store data. The data stored in the storage device 22 includes programs and control data for realizing the functions of the management system 1. The processing device 23 is, for example, a CPU, and can execute various processes by executing the programs stored in the storage device 22. The display 24 is a liquid crystal display, an organic EL display, etc. The display 24 displays the screens created by the server 10 or the mobile terminal 20. The position detection device 25 is a GNSS module that detects the position of the mobile terminal 20 based on GNSS radio waves. The position of the mobile terminal 20 is, in other words, also the position of the user who owns the corresponding mobile terminal 20. Note that the wireless communication module, which is the communication device 21, may also serve as the position detection device 25. That is, since the wireless communication module can also detect its position based on the intensities of the radio waves transmitted by a plurality of wireless access points, when this technology is used, the position detection device 25 is the wireless communication module. When the position detection device 25 is a GNSS module, the latitude and longitude information is the position information. When the position detection device 25 is a wireless communication module, the information indicating whether it is located in any of the pre-classified areas is the position information.

[0017] An application provided by the management system 1 is installed in the mobile terminal 20. Hereinafter, the application provided by the management system 1 may be simply referred to as an "app". The app can provide information about the facility to the user who visits the facility. In the app, the user is identified and managed using the unique information of the mobile terminal 20 or the ID created by the user.

[0018] The store terminal 30 is a terminal provided in the store. The store terminal 30 is a notebook PC, a tablet terminal, or a smartphone. The store terminal 30 cooperates with the server 10 to implement the management system 1. Note that the store terminal 30 may be used for store operations or may be a dedicated terminal for the management system 1. The store terminal 30 includes a communication device 31, a storage device 32, a processing device 33, and a display 34. Since these components are substantially the same as the components with the same name in the server 10 or the mobile terminal 20, the description thereof is omitted. Also, the server 10, the mobile terminal 20, and the store terminal 30 are a type of computer.

[0019] In this specification, calculating the purchase likelihood of customers using the management system 1 and the method of using the purchase likelihood will be described. Briefly explaining the process of calculating the purchase likelihood of customers, the server 10 acquires customer information, behavior history, and location information from the mobile terminal 20. The customer information and behavior history include information necessary for calculating the purchase likelihood of customers. The location information is used to identify that the corresponding store has been visited or is located in the vicinity of the corresponding store. The store terminal 30 acquires the customer information and behavior history of customers in the store or near the store from the server 10 and calculates the purchase likelihood of the customers. Thereby, customer service and the like can be performed taking into account the level of the purchase likelihood of the customers.

[0020] Hereinafter, the details of the method for calculating the purchase likelihood of customers will be described. The flowcharts after FIG. 2 are executed by the processing devices 13, 23, 33 of the server 10, the mobile terminal 20, or the store terminal 30. However, in the following description, it may be described that the server 10 executes the processing, etc., and the description of the processing devices 13, 23, 33 may be omitted.

[0021] First, the processing of the mobile terminal 20 will be explained with reference to Figure 2. When the user taps the app icon, the mobile terminal 20 launches the app (S101). Next, the mobile terminal 20 displays a screen on the display 24 asking whether the user consents to providing information to the store terminal 30, and determines whether the user consents or not (S102). By making this determination, it is possible to prevent customer information from being provided to the store terminal 30 without the user's permission. Note that if a similar confirmation has been made during app installation, the determination in step S102 may be omitted.

[0022] If the determination in step S102 is negative, the mobile terminal 20 terminates processing because it is not possible to calculate the customer's purchase probability. If the determination in step S102 is positive, the mobile terminal 20 receives the visitor question from the server 10 and displays it on the display 24 (S103). If the visitor question is fixed, the question may be stored in the storage device 22 of the mobile terminal 20 and read out at the timing of step S103.

[0023] Figure 3 shows an example of a question asked upon arrival. The question is multiple-choice, not open-ended. This reduces the effort required from the user to answer and simplifies the processing of the answers on the management system 1. However, the question could also be open-ended.

[0024] The visitor questionnaire is administered each time a user visits. Therefore, the visitor questionnaire is not designed to inquire about the user's usual preferences or values, but rather to understand their mood and plans for that day. The answers to the visitor questionnaire are used to calculate the user's purchase probability, as will be explained later.

[0025] Question 1, shown in Figure 3, is the purpose of the visit. Possible answers include purchasing goods, a change of pace, resting, sightseeing, and other. If purchasing goods is selected in Question 1, further questions about the intended purchase may be asked. Question 2 is the planned length of stay. The answer options can be specific durations, as shown in Figure 3, or times, such as "until 2 PM." It is preferable to provide options for planned length of stay that correspond to, for example, the size of the commercial facility or the number of stores. Question 3 is the preference for customer service. The answer options are a choice between those who want to be actively approached by staff, those who do not want to be approached by staff, or a neutral choice in between.

[0026] These questions are just examples; you may omit some questions or add others. You may also ask further questions depending on the options the user selects.

[0027] The mobile terminal 20 sends the answer to the question to the server 10 (S104). The user then uses the app while moving around the commercial facility. For example, the app also functions as a point card for the commercial facility, and the user uses the app when purchasing products. The location detection device 25 also periodically detects the user's location. The mobile terminal 20 sends the location information and purchase history detected in this way to the server 10 (S105). The mobile terminal 20 determines whether the user has left the facility (S106). The mobile terminal 20 determines that the user has left the facility, for example, when the location information shows that the user is outside the facility. The mobile terminal 20 continues to send location information and purchase history to the server 10 until it detects that the user has left. In addition, the stores visited by the user are identified by comparing the location information with the locations of stores within the facility. In this way, the user's activity history is identified.

[0028] Next, the process for calculating purchase probability will be explained with reference to Figures 4 and 5. In this embodiment, the process shown in Figure 4 is performed by the store terminal 30. Alternatively, the server 10 or the mobile terminal 20 may perform the same process and transmit the calculated purchase probability to the store terminal 30.

[0029] The store terminal 30 continuously acquires customer location information within the facility from the server 10. The store terminal 30 may acquire location information for all customers within the facility from the server 10, or it may acquire location information for customers within its own store and in the vicinity of its store from the server 10.

[0030] Based on the customer location information acquired in this manner, the store terminal 30 determines whether or not it has detected a customer inside or near the store (S201). Since calculating purchase probability for customers located far from the store would not be effective, the store extracts customers to be included in the calculation of purchase probability based on their location.

[0031] If the determination in step S201 is positive, the store terminal 30 determines whether the detected customer is a customer who is permitted to be displayed (S202). The store terminal 30 makes the determination in step S202 based on the result of step S102.

[0032] If the determination in step S202 is positive, the store terminal 30 determines whether the customer's purpose for visiting is to purchase a product (S203). The store terminal 30 makes the determination in step S203 based on the answers to the questions asked upon arrival.

[0033] If the determination in step S203 is positive, the store terminal 30 sets this customer as a potential purchaser (S204). Also, even if the determination in step S203 is negative, if the store terminal 30 determines that the customer's stay time is above a threshold (S205), it sets this customer as a potential purchaser (S204). A potential purchaser is a customer whose likelihood of purchase is estimated to be reasonably high through a simple process. The store terminal 30 calculates the probability of purchase only for potential purchasers. This reduces the frequency of calculating the probability of purchase, thereby reducing the load on the store terminal 30. Steps S201 to S205 are not mandatory processes and may be omitted.

[0034] Next, the store terminal 30 calculates the purchase activity level for prospective customers (S206). Purchase activity level is an indicator of a customer's temporary purchasing intent. Temporary refers primarily to the same day or within a few hours. Purchase activity level is calculated based on customer information that changes daily or hourly. Figure 5 shows a purchase activity level checklist.

[0035] The purchase activity checklist has multiple check items, and the number of items that are met represents the purchase activity level. Whether or not a check item is met is determined based on customer information or behavioral history stored on server 10. Specifically, if the purpose of the visit is to purchase a product, it is naturally assumed that the customer has a high purchase intent. If there is a history of visiting similar stores, it is highly likely that the desired product is available in the store, so it is naturally assumed that the customer has a high purchase intent. If the customer is returning to the store on the same day, it is naturally assumed that the customer has a high purchase intent. If the customer is carrying a shopping bag, it means that they have shopped at other stores, so it is naturally assumed that the customer has a high purchase intent. Whether or not a customer is carrying a shopping bag can be determined by combining the analysis results of images taken by cameras placed in or near the store with the customer's location information. If the visit occurs after eating or drinking, it is possible that the customer has organized their purchasing decisions or their energy levels have increased during the meal, so it is naturally assumed that the customer has a high purchase intent. If the time spent at the store in question exceeds a threshold, it is naturally assumed that the customer has a high purchase intent. This checklist will not necessarily meet all the criteria immediately after a customer arrives at the store, but the customer's actions after their arrival may potentially lead to them meeting all the criteria.

[0036] Next, the store terminal 30 calculates the potential purchase rate for prospective customers (S207). The potential purchase rate is an indicator of a customer's consistent purchasing intent. Consistent means that it does not change from day to day or hour to hour. In other words, it is determined based on information such as the customer's hobbies, preferences, personality, or behavioral patterns. Note that behavioral patterns are different from one-time behavioral history, but are patterned behaviors that a customer repeats many times. For example, visiting the store over several days to check products before purchasing. In addition, customers register information about their hobbies, preferences, personality, or behavioral patterns when registering for the app. Figure 5 shows a potential purchase rate checklist.

[0037] The potential purchase checklist has multiple check items, and the number of items that are met represents the potential purchase rate. Whether or not a check item is met is determined based on customer information stored on server 10. Specifically, if the characteristics of the customer registered in the app match the store's products, the product is more likely to be purchased based on the customer's tastes and preferences. Also, if the frequency or probability of past purchases at similar stores is above a threshold, the product is naturally more likely to be purchased. This information is calculated based on the aggregated results of past behavioral history using the app.

[0038] The contents of the Purchase Activity Checklist and the Potential Purchase Activity Checklist are examples only, and any of the check items may be changed or deleted, or other check items may be added. For example, purchase activity may be determined to be high if the time spent in the same location within the store exceeds a threshold. In this embodiment, the points for each check item are uniform, but the points may be different for each check item, for example, by doubling the points for important items.

[0039] In this embodiment, the purchase activity and potential purchase rate are calculated regardless of the type of product. Alternatively, the purchase activity and potential purchase rate may be calculated for each type of product to calculate the purchase probability. This allows for the calculation of information such as, for example, that the purchase probability of clothing is low, but the purchase probability of shoes is high.

[0040] Next, the store terminal 30 calculates the probability of purchase based on the purchase activity level and the potential purchase level (S208). In this embodiment, the probability of purchase is calculated by adding the purchase activity level and the potential purchase level together. Alternatively, different weights may be assigned to the purchase activity level and the potential purchase level, and then they may be added together.

[0041] Based on the above, the probability of purchase can be calculated. The probability of purchase calculated in this way is highly accurate because it takes into account not only the customer's temporary purchasing intent but also their ongoing purchasing intent.

[0042] Next, we will explain examples of how to utilize purchase potential. First, we will explain the first customer map with reference to Figures 6 and 7. The first customer map is a map in which icons created according to the purchase potential of each customer are superimposed on a map of stores.

[0043] Specifically, the store terminal 30 extracts customers based on their likelihood of purchase (S301). The extraction method may involve extracting a predetermined number of customers in order of their likelihood of purchase, or extracting all customers whose likelihood of purchase exceeds a threshold. Alternatively, the process in step S301 may be omitted.

[0044] Next, the store terminal 30 displays a first customer map on the display 34, showing the purchase probability of the extracted customers (S302). The customer's location can be obtained via the server 10 as described above. The store map is also created in advance and stored in the storage device 32. Then, the customer icons are placed on the store map according to the customer's location. As a result, the first customer map shown in Figure 7 is created. In this embodiment, icons are set according to the level of purchase probability so that the level of purchase probability can be grasped at a glance.

[0045] By viewing the first customer map, you can quickly identify the locations of customers with a high probability of making a purchase. This allows you to, for example, prioritize serving these high-probability customers to encourage them to buy.

[0046] Using a first customer map to indicate purchase potential is just one example. Alternatively, a customer list can be used. This customer list includes the customer's purchase potential and location in a list format. The customer's location might be indicated as, for example, Area 5. For stores with low customer traffic, simply providing the area number using the customer list is sufficient to identify the relevant customer.

[0047] As mentioned above, purchase activity changes depending on the customer's behavior within the store. Therefore, the store terminal 30 obtains the customer's behavior history within the store via the server 10 (S303). As a result, when the customer meets the check items for purchase activity, their purchase activity increases, and consequently, their likelihood of making a purchase also increases.

[0048] Next, the store terminal 30 updates the first customer map using the updated purchase probability (S304). This allows the store staff to be provided with purchase probability that reflects the latest information. Note that updating the first customer map is not mandatory, so steps S303 and S304 may be omitted.

[0049] Next, with reference to Figure 8, we will explain the issuance of electronic coupons using purchase potential.

[0050] First, the store terminal 30 extracts customers based on their likelihood of purchase (S401). Step S401 is the same process as step S301. Next, the store terminal 30 issues electronic coupons to the extracted customers based on their likelihood of purchase (S402) and sends the issued electronic coupons to the customers' mobile terminals 20 (S403). When the mobile terminal 20 receives the electronic coupon, it notifies the user using the app's notification function.

[0051] Electronic coupons include not only discounts on products, but also increased points for product purchases, and the provision of novelty items for product purchases. Electronic coupons based on purchase likelihood mean, for example, that the higher the purchase likelihood, the higher the discount rate of the electronic coupon issued. Alternatively, for customers with a high purchase likelihood, an electronic coupon type may be issued that provides a discount if the purchase amount exceeds a certain amount, with the aim of encouraging additional purchases. As mentioned above, if the purchase likelihood is calculated for each type of product, electronic coupons for products with a high purchase likelihood may be issued preferentially.

[0052] Furthermore, the content of electronic coupons may be determined based on the customer's in-store behavior history. For example, if a customer spends a long time in a particular product section, an electronic coupon for that product may be issued. Also, if a customer spends a long time in the store, a time-limited electronic coupon may be issued.

[0053] Subsequently, the store terminal 30 acquires and records the usage history of the electronic coupon (S404). By accumulating and analyzing the usage history of the electronic coupon, it is possible to infer the conditions for issuing valid electronic coupons and the content of the electronic coupons.

[0054] Next, the second customer map will be explained with reference to Figures 9 and 10. The second customer map is a map that overlays information indicating the priority of response calculated according to the customer's purchase probability, etc., and the store staff who should respond, onto a map of the store.

[0055] First, the store terminal 30 identifies customer characteristics based on the answers to questions asked during app registration and visit, as well as the customer's activity history for the day (S501). Customer characteristics include information about the customer's hobbies, preferences, personality, behavioral patterns, mood on the day, the customer's available time on the day, or the aforementioned purchase probability.

[0056] Next, the store terminal 30 reads out the store employees working that day and their characteristics (S502). Store employee characteristics include, for example, the employee's gender, age, and customer service policy. Customer service policy may be, for example, actively engaging with customers or not initiating conversations with customers. Alternatively, customer service policies may be classified as listening type, advisory type, friend-type, etc. The store employees working that day are entered, for example, when the store terminal 30 is activated during preparation for opening the store. Store employee characteristics are information associated with the store employees. Store employee characteristics may be created in advance and stored in the storage device 32, or they may be entered during preparation for opening the store.

[0057] Next, the store terminal 30 matches customers with staff based on customer characteristics and staff characteristics, starting with customers with the highest likelihood of purchasing (S503). The matching of customer characteristics and staff characteristics includes matching the customer's customer service preference (answers to customer service preferences in questions asked upon arrival) with the staff's customer service policy. For example, by matching customers who want to be approached with staff who are proactive in engaging with them, it is possible to provide customer-tailored service. Also, since customer characteristics include age and gender, by matching customers with the same gender or similar age with staff, it is possible to provide customer-tailored service. Furthermore, by matching customers in order of their likelihood of purchasing, staff can be assigned to customers with a high likelihood of purchasing, making it easier to promote customer purchases.

[0058] Next, the store terminal 30 calculates customer priority based on customer characteristics and matching results (S504). Response priority is the priority given to which a store employee should attend to the customer. Based on customer characteristics, for example, if a customer's hobbies, preferences, and personality match those of the store, the response priority will be higher. Also, if a customer is willing to be approached, the response priority will be higher. Furthermore, if a customer is likely to make a purchase, the response priority will be higher. Additionally, if a customer has ample time available, the response priority will be higher. Furthermore, customers who are matched with a store employee based on the matching results will also receive a higher response priority. For example, points may be assigned to each of the above items, and the response priority may be determined based on the total score.

[0059] Next, the store terminal 30 displays a second customer map on the display 34, indicating the priority of service (S505). As shown in Figure 10, the second customer map is superimposed on the store map with icons assigned to customers according to their priority. The second customer map also shows the matching results between customers and store staff. By looking at the second customer map, store staff can quickly identify which customers should be given priority, and in particular, which store staff should attend to which customers.

[0060] Furthermore, while the method for calculating response priority includes various items as described above, it is not necessary to include all of them, and they can be omitted as appropriate. Also, store staff can switch which items are used to calculate response priority. For example, response priority can be calculated based solely on matching results, or based solely on the customer's time availability and purchase probability. Response priority may also be calculated using items not mentioned above.

[0061] (Feature 1) The purchase promotion device of this embodiment comprises a communication device 31, a storage device 32, and a processing device 33. The communication device 31 acquires customer information from an application on a mobile terminal 20 for customers visiting a commercial facility or store. The storage device 32 stores the customer information. Based on customer information relating to the customer's purpose of visit on the day or the customer's behavioral history on the day, the device calculates a purchase activity level, which is an indicator of the customer's temporary willingness to purchase. Based on customer information relating to the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application, the device calculates a potential purchase level, which is an indicator of the customer's regular willingness to purchase. Based on the purchase activity level and the potential purchase level, the device calculates a purchase probability level, which is an indicator of the probability that the customer will purchase the product.

[0062] This allows for the calculation of purchase probability based on a customer's temporary and ongoing purchase intent. The purchase probability calculated in this way is more accurate than values ​​based solely on ongoing purchase intent, making it useful as information for promoting purchases.

[0063] (Feature 2) In the purchase promotion device of this embodiment, the processing device 33 calculates the purchase activity level based on the customer's answers to questions presented to the customer via the application and the customer's daily behavior history obtained via the application.

[0064] This allows for the calculation of a highly accurate purchase motivation level.

[0065] (Feature 3) In the purchase promotion device of this embodiment, the communication device 31 acquires the customer's location as customer information, which is detected by the location detection device 25 built into the customer's mobile terminal 20. The processing device 33 displays information that associates the customer's location with the likelihood of purchase on the display 34 of a store terminal 30 installed in the store or held by a store employee.

[0066] This allows for customer service that leverages purchasing potential.

[0067] (Feature 4) In the purchase promotion device of this embodiment, the processing device 33 displays a first customer map on the display 34, which includes a map of the store and customer icons indicating the customer's location on the map. The processing device 33 determines whether or not to display the customer icons, or the display manner, based on the likelihood of purchase.

[0068] This allows store employees to quickly grasp a customer's purchasing potential.

[0069] (Feature 5) In the purchase promotion device of this embodiment, the processing device 33 extracts customers based on their likelihood of purchase and displays only the extracted customers on the display 34.

[0070] This allows for the organization of information when there are many customers inside or near the store.

[0071] (Feature 6) In the purchase promotion device of this embodiment, the processing device 33 extracts customers based on their likelihood of purchase and issues electronic coupons to the extracted customers. The communication device 31 transmits the electronic coupons issued by the processing device 33 to the customer's mobile terminal 20.

[0072] This can provide a trigger for customers who are highly likely to make a purchase to actually make one.

[0073] (Feature 7) In the purchase promotion device of this embodiment, the processing device 33 issues an electronic coupon whose content is determined based on the customer's likelihood of purchase.

[0074] This allows for the issuance of electronic coupons tailored to purchase likelihood.

[0075] (Feature 8) In the purchase promotion device of this embodiment, the communication device 31 acquires the customer's store movement history as customer information based on the customer's location information detected by the location detection device 25 built into the customer's mobile terminal 20. The processing device 33 issues an electronic coupon whose content is determined based on the customer's store movement history.

[0076] This allows for the issuance of coupons based on customer behavior.

[0077] (Feature 9) In the purchase promotion device of this embodiment, the processing device 33 calculates the priority order for serving customers who visit the store based on customer characteristics related to the customer's hobbies, preferences, personality, or behavioral patterns based on customer information, and the likelihood of purchase. The priority order is displayed on the display 34 of a store terminal 30 installed in the store or held by a store employee.

[0078] This allows the employee to understand the priority of customer service.

[0079] (Feature 10) In the purchase promotion device of this embodiment, the processing device 33 extracts customers based on their likelihood of purchase, and matches the extracted customers with store employees based on customer characteristics related to the customer's hobbies, preferences, personality, or behavioral patterns based on customer information, and store employee characteristics indicating the characteristics of store employees that have been registered in advance.

[0080] This allows for matching customers with the most suitable staff members. In particular, it matches customers who are highly likely to make a purchase, thus increasing the chances of a sale.

[0081] (Feature 11) In the purchase promotion device of this embodiment, the processing device 33 matches customers with store employees based on customer characteristics, specifically the customer service preference score which indicates preferences regarding customer service, and store employee characteristics, specifically the customer service policy.

[0082] This allows, for example, a store employee who is willing to talk to a customer can be matched with the type of employee who is willing to talk to the customer.

[0083] (Feature 12) In the purchase promotion device of this embodiment, the processing device 33 calculates the priority of service for customers who visit the store based on customer characteristics related to the customer's hobbies, preferences, personality, or behavioral patterns based on customer information, purchase probability, and matching results. The priority of service is displayed on the display 34 of a store terminal 30 installed in the store or held by a store employee.

[0084] You can quickly grasp the priority of customer service requests.

[0085] The above-mentioned features 1 to 12 can be combined, for example, as follows to realize a purchase promotion device. The same applies to the purchase promotion method. [Configuration 1] A purchase promotion device having Feature 1. [Configuration 2] A purchase promotion device having feature 2 in addition to configuration 1. [Configuration 3] A purchase promotion device having the features of configuration 1 or 2, in addition to feature 3. [Configuration 4] A purchase promotion device having one of Configurations 1 to 3, plus Feature 4. [Configuration 5] A purchase promotion device having one of Configurations 1 to 4, plus feature 5. [Configuration 6] A purchase promotion device having one of Configurations 1 to 5, plus feature 6. [Configuration 7] A purchase promotion device having one of Configurations 1 to 6, plus feature 7. [Configuration 8] A purchase promotion device having one of Configurations 1 to 7, plus feature 8. [Configuration 9] A purchase promotion device having one of Configurations 1 to 8, plus feature 9.

[0086] The functions of the elements disclosed herein can be performed using circuits or processing circuits, including general-purpose processors, dedicated processors, integrated circuits, ASICs (Application Specific Integrated Circuits), conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. A processor is considered a processing circuit or circuit because it includes transistors and other circuits. In this disclosure, a circuit, unit, or means is hardware that performs the enumerated functions, or hardware programmed to perform the enumerated functions. The hardware may be hardware disclosed herein, or other known hardware that is programmed or configured to perform the enumerated functions. If the hardware is a processor, which is considered a type of circuit, then the circuit, means, or unit is a combination of hardware and software, and the software is used to configure the hardware and / or the processor. [Explanation of Symbols]

[0087] 1 Management System 10 servers 20 Mobile devices 30 Store terminals (purchase promotion devices)

Claims

1. A communication device that acquires customer information from a mobile device application used by customers visiting a commercial facility or store, A storage device for storing the aforementioned customer information, Processing device and Equipped with, The aforementioned processing apparatus is Based on the customer information relating to the customer's purpose of visit on that day or their behavioral history on that day, the purchase activity level, which is an indicator of the customer's temporary willingness to purchase, is calculated. Based on the customer information regarding the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application, the potential purchase rate, which is an indicator of the customer's regular purchasing intent, is calculated. A purchase promotion device that calculates purchase probability, which is an indicator of the probability that a customer will purchase a product, based on the purchase activity level and the potential purchase level.

2. A method for supporting communication according to claim 1, The processing device is a purchase promotion device that calculates the purchase activity level based on the customer's answers to questions presented to the customer via the application and the customer's daily behavioral history obtained via the application.

3. A purchase promotion device according to claim 1, The communication device acquires the customer's location, as customer information, which is detected by a location detection device built into the customer's mobile terminal. The processing device is a purchase promotion device that displays information relating the customer's location to the likelihood of purchase on the display of a terminal installed in the store or held by a store employee.

4. A purchase promotion device according to claim 3, The processing device displays a first customer map on the display, which includes a map of the store and customer icons indicating the location of customers on the map. The processing apparatus is a purchase promotion device that determines whether or not to display the customer icon, or the display pattern thereof, based on the likelihood of purchase.

5. A purchase promotion device according to claim 3, The processing device is a purchase promotion device that extracts customers based on their likelihood of purchase and displays only the extracted customers on the display.

6. A purchase promotion device according to claim 1, The processing device extracts customers based on their likelihood of purchase, and issues electronic coupons to the extracted customers. The communication device is a purchase promotion device that transmits the electronic coupon issued by the processing device to the customer's mobile terminal.

7. A purchase promotion device according to claim 6, The processing device is a purchase promotion device that issues the electronic coupon whose content is determined based on the customer's likelihood of purchase.

8. A purchase promotion device according to claim 7, The communication device acquires the customer's movement history to the store as customer information, based on location information detected by a location detection device built into the customer's mobile terminal. The processing device is a purchase promotion device that issues the electronic coupon whose content is determined based on the customer's visit history to the store.

9. A purchase promotion device according to claim 1, The aforementioned processing apparatus is The processing device calculates the priority order for serving the customer who visited the store, based on the customer characteristics relating to the customer's hobbies, preferences, personality, or behavioral patterns based on the customer information, and the likelihood of purchase. A purchase promotion device that displays the aforementioned priority order on the display of a terminal installed in the store or held by a store employee.

10. A purchase promotion device according to claim 1, The processing device extracts customers based on their likelihood of purchase, and matches the extracted customers with store employees based on customer characteristics relating to the customers' hobbies, preferences, personality, or behavioral patterns based on the customer information, and store employee characteristics indicating the characteristics of store employees that have been registered in advance.

11. A purchase promotion device according to claim 10, The processing device is a purchase promotion device that matches the customer with the store clerk based on the customer preference score, which indicates the customer's preference regarding customer service among the customer characteristics, and the customer service policy among the store clerk characteristics.

12. A purchase promotion device according to claim 11, The processing device calculates the priority order for serving the customer who visited the store based on the customer characteristics relating to the customer's hobbies, preferences, personality, or behavioral patterns based on the customer information, the purchase probability, and the matching results. A purchase promotion device that displays the aforementioned priority order on the display of a terminal installed in the store or held by a store employee.

13. Customer information is obtained from mobile device applications used by customers visiting commercial facilities or stores. The aforementioned customer information is stored, Based on the customer information relating to the customer's purpose of visit on that day or their behavioral history on that day, the purchase activity level, which is an indicator of the customer's temporary willingness to purchase, is calculated. Based on the customer information regarding the customer's hobbies, preferences, personality, or behavioral patterns registered by the customer using the application, the potential purchase rate, which is an indicator of the customer's regular purchasing intent, is calculated. A purchase promotion method comprising having a computer perform a process to calculate purchase probability, which is an indicator of the probability that a customer will purchase a product, based on the purchase activity level and the potential purchase level.

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