Information processing method

Abstract

The present invention provides a method for improving a technique for inferring a purchase intention of a customer. An information processing device (10) uses one or more sensors provided in a store to detect customer information of customers coming to the store. Then, the information processing device (10) determines the customer attribute information on the basis of the detected customer information. Then, the information processing device (10) estimates, on the basis of the attribute information, the degree of the customer's intention to purchase the product in the store.

Description

Technical Field

[0001] This disclosure relates to a method. Background Technology

[0002] Previously, techniques for inferring customers' purchasing intentions were known. For example, Patent Document 1 discloses an advertising publishing control device that infers purchasing intentions based on the time of acquisition and balance of a customer's voucher.

[0003] Prior art literature Patent documents Patent Document 1: Japanese Patent Application Publication No. 2019-168880 Summary of the Invention The problem that the invention aims to solve In recent years, with the development of machine learning and other technologies, there is a desire to improve the technology for inferring customers' purchasing intentions.

[0004] The purpose of this disclosure, which was made in view of such circumstances, is to improve the technology for inferring customers' purchasing intentions.

[0005] Methods for solving problems One embodiment of this disclosure relates to a method performed by an information processing device, the method comprising the following steps: detecting customer information of customers who have entered the store using one or more sensors installed in the store; determining the attribute information of the customers based on the detected customer information; and inferring the degree of the customers' willingness to purchase goods in the store based on the attribute information.

[0006] Invention Effects According to one embodiment of this disclosure, the technology for inferring a customer's purchase intention can be improved. Attached Figure Description

[0007] Figure 1 A block diagram illustrating the general structure of the information processing apparatus involved in this disclosure.

[0008] Figure 2 A flowchart illustrating the operation of the information processing apparatus involved in this disclosure. Detailed Implementation

[0009] The embodiments of this disclosure will now be described.

[0010] (Summary of the implementation method) Reference Figure 1The structure of the information processing apparatus 10 according to this embodiment will be described below. The information processing apparatus 10 may be, for example, a server device, a computer such as a PC (Personal Computer), or a general-purpose or special-purpose electronic device. The information processing apparatus 10 may provide services used by staff of shops such as car dealerships. The information processing apparatus 10 may be a terminal device used by the shop staff as users of this service, a server belonging to a cloud computing system, or it may be composed of a terminal device and a server.

[0011] First, an overview of this embodiment will be given; detailed information will be described later. The information processing device 10 uses one or more sensors installed in the store to detect customer information of customers entering the store. Next, the information processing device 10 determines the customer's attribute information based on the detected customer information. Then, the information processing device 10 infers the degree of the customer's willingness to purchase the store's goods based on the attribute information.

[0012] Existing technologies require prior knowledge of customer information to infer their purchasing intentions upon entering a store. In contrast, this embodiment infers customer purchasing intentions using information detected by one or more sensors installed in the store. Therefore, purchasing intentions can be inferred even when prior customer information is unavailable. Furthermore, the inferred purchasing intentions are real-time information. Thus, this embodiment improves the technique for inferring purchasing intentions by providing real-time information, even when prior customer information is unavailable. Moreover, by improving the technique for inferring purchasing intentions, the store's processing time for customers with low purchasing intentions can be reduced.

[0013] Next, the structure of the information processing device 10 will be described in detail.

[0014] (Structure of an information processing device) The information processing device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0015] The communication unit 11 includes one or more communication interfaces connected to a network. These communication interfaces may correspond to mobile communication standards such as 4G (4th Generation) or 5G (5th Generation), but are not limited to these. The communication unit 11 receives information used in the operation of the information processing device 10 and transmits information obtained through the operation of the information processing device 10. The communication unit 11 enables the information processing device 10 to send and receive information via the network with other devices, such as one or more sensors installed in a store.

[0016] The storage unit 12 includes one or more memories. These memories may be, for example, semiconductor memories, magnetic memories, or optical memories, but are not limited to these. Each memory included in the storage unit 12 may function as a main storage device, an auxiliary storage device, or a cache memory. The storage unit 12 stores any information used in the operation of the information processing device 10. Furthermore, the storage unit 12 may also store system programs, application programs, and embedded software. For example, the information stored in the storage unit 12 may be updated using information obtained from a network via the communication unit 11.

[0017] The control unit 13 includes at least one processor, at least one programmable circuit such as an FPGA (field-programmable gate array), at least one special-purpose circuit such as an ASIC (application-specific integrated circuit), or any combination thereof. The processor is a general-purpose processor such as a CPU (central processing unit) or a GPU (graphics processing unit), or a special-purpose processor dedicated to specific processing. The control unit 13 controls various parts of the information processing device 10 while simultaneously performing processing related to the operation of the information processing device 10.

[0018] (The operation flow of the information processing device) Reference Figure 2 The operation of the information processing apparatus 10 according to this embodiment will be explained.

[0019] S100: The control unit 13 of the information processing device 10 uses one or more sensors installed in the store to detect customer information of customers who come to the store.

[0020] "One or more sensors" includes, for example, surveillance cameras capable of capturing images inside the store and microphones capable of recording conversations within the store, but may also include, but is not limited to, any sensor capable of detecting customer information within the store. Furthermore, one or more sensors may not be installed in the store, but rather be devices held by store staff. For example, one or more sensors may include cameras and / or microphones on terminal devices used by staff, or microphones worn by staff, but are not limited to these devices.

[0021] "Customer information" can include, for example, customer movement within the store, such as the path customers take and the time they spend looking at products, which can be detected by surveillance cameras, or it can include conversations within the store, which can be detected by microphones.

[0022] S101: The control unit 13 judges the attribute information of the customer based on the detected customer information.

[0023] "Attribute information" can also be information related to any attribute that can be inferred from a customer's in-store behavior and conversation. For example, while attributes may include a customer's age group, family composition, clothing, budget, purpose of visit, and interest in products, they may also include, but are not limited to, any information that can infer the degree of a customer's purchase intention.

[0024] For example, if one or more sensors include a microphone, the control unit 13 can also determine attribute information by performing natural language processing and keyword detection processing on the conversational voices within the store. Specifically, the control unit 13 can also infer the customer's age group, family structure, budget, purpose of visit, etc., by performing natural language processing and keyword detection processing on the conversational voices.

[0025] For example, if one or more sensors include a surveillance camera, the control unit 13 can also perform image recognition processing on the camera images captured by the surveillance camera to determine attribute information. Specifically, the control unit 13 can also perform image recognition processing to infer information such as a customer's clothing and in-store activities.

[0026] S102: Controller 13 infers the customer's level of purchase intention for the store based on attribute information.

[0027] For example, control unit 13 may store statistical values ​​of the purchase intention level of customers for each age group in storage unit 12, and use the statistical value corresponding to the inferred age group of the customer as the degree of the customer's purchase intention for inference. Furthermore, control unit 13 may infer, for example, that the higher the inferred customer's budget, the stronger their purchase intention. Additionally, control unit 13 may infer, for example, that the more specific the inferred customer's purpose for visiting the store, such as researching purchases before March, the higher their purchase intention. Furthermore, control unit 13 may infer, for example, that the more formal the inferred customer's clothing, the stronger their purchase intention. Moreover, control unit 13 may infer, for example, that the longer and more frequently the customer lingers near the product display area, the stronger their purchase intention for that product.

[0028] Although the "degree of customer's willingness to buy" can be expressed in order of purchase willingness from high to low as "high", "medium" and "low", or it can be expressed as an integer in any range from 5 to 1, or as a letter such as S, A, B, C and D, it can also be expressed in any way that is not limited to these methods.

[0029] In addition, for example, the control unit 13 can use AI to analyze the attribute information of customers with a high degree of purchase intention, store the analysis results in the storage unit 12, and infer the degree of purchase intention of the customer based on the analysis results.

[0030] While this disclosure has been described with reference to the accompanying drawings and embodiments, it should be noted that various modifications and alterations can be made based on this disclosure by those skilled in the art. Therefore, it should be understood that such modifications and alterations are included within the scope of this disclosure. For example, the functions included in each structural component or step can be reconfigured in a logically consistent manner, and multiple structural components or steps can be combined into one or divided.

[0031] For example, in the embodiments described above, the structure and operation of the information processing device 10 can also be distributed among multiple computers capable of communicating with each other. For example, if the information processing device 10 is composed of a terminal device and a server, it can also be configured such that the terminal device performs some operations, and the server performs operations that are not performed by the terminal device.

[0032] Furthermore, for example, in the embodiment described above, the control unit 13 may also display information indicating the degree of the customer's inferred purchase intention. Specifically, the control unit 13 may also display the degree of the customer's purchase intention inferred in S102 on the display of the terminal device used by the user.

[0033] Furthermore, as in the embodiment described above, the control unit 13 may also perform the actions of S100 to S102 at fixed intervals, and notify the user if the customer's level of purchase intention changes. While notifying the user may be implemented, for example, by displaying content indicating the above meaning on the display of the user's terminal device using a message, any method not limited to this can be employed. Alternatively, the control unit 13 may not notify the user, but instead display the customer's level of purchase intention on the terminal device's display, for example, by showing a chart or graph.

[0034] Furthermore, the "fixed time" can include any time such as 10 minutes or 1 hour. The fixed time can also be changed. In addition, the control unit 13 can also implement the actions of S100 to S102 in real time.

[0035] Furthermore, an embodiment could also be implemented to enable a general-purpose computer to function as the information processing apparatus 10 described in the above-described embodiments. Specifically, a program describing processing content for implementing the functions of the information processing apparatus 10 described in the above-described embodiments is stored in the memory of a general-purpose computer, and the program is read and executed by a processor. Therefore, this disclosure can also be implemented as a program executable by a processor, or as a non-transitory computer-readable medium in which the program is stored.

[0036] Furthermore, in the embodiments described above, the control unit 13 can also control the dialogue AI that outputs text or voice responses to user input into the terminal device as a store employee, based on the inferred level of the customer's purchase intention. For example, the control unit 13 can also control the dialogue AI to output a response that takes into account the inferred level of purchase intention by inputting the inferred level of purchase intention into the dialogue AI in addition to the text or voice-based question input by the user. According to the structure described above, by referring to the response, the user can conduct appropriate business negotiations or recommendations based on the customer's purchase intention.

[0037] Symbol Explanation 10. Information processing device; 11 Ministry of Communications; 12. Storage Unit; 13. Control Department.

Claims

1. A method, which is a method executed by an information processing apparatus, and includes processing of: detecting customer information of a customer who comes to a store, using one or more sensors provided in the store; judging attribute information of the customer, based on the detected customer information; and inferring a degree of a purchase willingness of the customer for a product of the store, based on the attribute information.

2. The method according to claim 1, wherein, the method further includes processing of: displaying information indicating the inferred degree of the purchase willingness of the customer.

3. The method according to claim 1, wherein, the one or more sensors include a microphone capable of detecting a conversation voice in the store, the customer information includes the conversation voice, the method further includes processing of: implementing natural language processing and keyword detection processing with respect to the conversation voice, the information processing apparatus judges the attribute information based on a result of the natural language processing and the keyword detection processing.

4. The method according to claim 1, wherein, the one or more sensors include a monitoring camera capable of taking an image in the store, the customer information includes a camera image taken by the monitoring camera, the method further includes processing of: implementing image recognition processing with respect to the camera image, the information processing apparatus judges the attribute information based on a result of the image recognition processing.

5. A method, wherein, an information processing apparatus implements the method according to claim 1 every fixed time, the method further includes processing of: notifying a user in a case where the degree of the purchase willingness of the customer has changed.

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