CN112085521A - System for managing and serving store members - Google Patents
System for managing and serving store members Download PDFInfo
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- CN112085521A CN112085521A CN202010853538.2A CN202010853538A CN112085521A CN 112085521 A CN112085521 A CN 112085521A CN 202010853538 A CN202010853538 A CN 202010853538A CN 112085521 A CN112085521 A CN 112085521A
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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
- G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
- G06Q30/0226—Incentive systems for frequent usage, e.g. frequent flyer miles programs or point systems
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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
- G06Q30/01—Customer relationship services
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Abstract
The invention relates to the field of physical retail industry, in particular to a system for store member management and service. The method is characterized in that: the system records all records and behavior data consumed by the members in the store, classifies and files all generated data, forms member labels according to classified data characteristics, enables the members to arrive at the store, enables the cameras to capture member face information, enables the AI face analysis box to perform data analysis, enables the cloud server to calculate, pair and store information, enables the terminals to display and send member arrival reminding and labeling information, and enables the stores to achieve accurate service and conversion. The system solves the problems that the stores can not perform characteristic classification management, label identification, member-to-store reminding and timely and automatically present member label information on the members, can help merchants improve the reputation of brands and realize stable and continuous increase of business turnover, and can be widely applied to store member management in the retail industry.
Description
Technical Field
The invention relates to the field of physical retail industry, in particular to a system for store member management and service.
Background
The member label is used for recording and describing objective facts (such as attributes and behaviors) of the member, and describing user images in the form of keywords and words, so that data analysis is performed on the member through modeling.
The AI face recognition technology is a biometric technology that performs identification based on facial feature information of a person. The method comprises the following steps of collecting images or video streams containing human faces by using a camera or a camera, automatically detecting and tracking the human faces in the images, and further carrying out face recognition on the detected human faces.
In general, a physical store may be equipped with a member management system and a conventional security device, and the general member management system can only record consumption records and other related data of members, and can only query historical data, cannot analyze and count related data of the members, and cannot describe characteristics of the members in the form of keywords. Conventional security equipment can only play a role in security, and cannot achieve the purposes of identifying members to shops and pushing tagged data information, so that accurate marketing and personalized services cannot be realized. The invention combines the store member management system, the face recognition and data analysis technology and the equipment, simultaneously realizes the recording, classification and statistics of the related data of the members, summarizes the characteristics of various data in the form of key words, and realizes the voice prompt of welcome phrases of a certain member to the store after the member arrives at the store through the face recognition and data analysis technology and the equipment, and displays the tagged information of the member on the terminal equipment. The system solves the problems that the store management system can not perform characteristic classification management, label identification, member arrival store reminding and timely and automatically present member label information for the members.
Disclosure of Invention
The invention aims to provide a system for store member management and service, and solves the problems that a store management system cannot perform characteristic classification management, label identification, member arrival store reminding and timely and automatic member label information presentation on members.
The technical scheme for solving the technical problems is as follows:
the method is characterized in that: the system records all records and behavior data consumed by the members in the store, files all generated data in a classified mode, forms member labels according to classified data characteristics, enables the members to arrive at the store, enables the cameras to capture member face information, enables the AI face analysis box to conduct data analysis, enables the cloud server to conduct operation, pairing and information storage, enables the terminals to display and send member arrival at the store reminding and labeling information, and can achieve accurate service and conversion in the store.
In the system for store member management and service, in the first step, a member profile is created in the store management system, and the profile information includes: name, member account number, gender, age, phone, native place, photo, micro-signal, registration time, and registered store, etc.
In the second step, the system records all records and behavior data of the member consuming in the store. The method comprises the steps of automatically recording and manually inputting information by a system, wherein the recorded data comprises: member image, consumption data, preference data, activity data, consumption period and frequency data, etc
The detailed recorded member data includes:
(1) member image: uploading a recent front photo of each member;
(2) consumption data: the system comprises a consumption shop, a consumption brand, a consumption type, an amount, a date, a payment mode and a participation mode;
(3) preference data: including preferred styles, colors, categories, etc.;
(4) activity data: including the status of the activities and consumption engaged in and feedback on the activities;
(5) period and frequency of consumption: including year, season, month, week, daily consumption time period and frequency statistics;
in the third step, the system classifies, counts and archives all generated data to form member feature labels, so that the consumption portrait of the member can be very clearly known according to the member label information, and label extraction is mainly performed from the following three aspects:
firstly, living habits:
(1) dividing the member into gender and age groups according to the gender and the age of the member, and extracting a gender label and an age group label;
(2) extracting frequent shopping store information of the members according to the data statistical ranking of the consumption stores of the members;
(3) extracting member consumption time period information and activity information according to member consumption time statistics;
secondly, consumption habit:
(1) extracting a brand grade label frequently purchased by a member according to information statistics of member consumption brands;
(2) extracting whether the member is a label of a frequently participating activity or a group buying and general consuming member according to the data statistics of the participating activity;
thirdly, behavior habit:
(1) extracting payment mode labels commonly used by the members according to statistics of payment modes of the members;
(2) extracting the activities frequently attended by the user, the activity frequency and the feedback information of the activities according to the data statistics of the attended activities;
in the fourth step, after the member arrives at the store, the camera in the store captures the face information of the member, the AI face recognition box performs data analysis, the cloud server performs operation, pairing and information storage, and the information is analyzed through the database information of the cloud server. The method mainly comprises the following three steps:
(1) establishing a database containing a large number of facial images (images of input members and labeled information);
(2) obtaining a target face image to be identified currently (face information captured by a member-to-store camera) through various modes;
(3) comparing and screening (data analysis) the target face image with the existing face images in the database;
in the fifth step, the terminal equipment sends out welcome language voice of a certain member to the store, and meanwhile, the terminal equipment system (the PU end and the mobile end) pops up member label information. When listening to the prompt voice, the store clerk checks the member label data information popped up by the computer or the mobile end store management system, so that the user-friendly service and marketing can be timely and accurately provided for the member, and the transaction rate of the order is improved.
The invention solves the problems that the store management system can not carry out feature classification management, label identification, member arrival reminding and timely and automatic member label information presentation on members, is beneficial to realizing accurate marketing and service on different member clients, avoids invalid disturbance on the member clients, provides better shopping experience for the clients, and improves loyalty and reputation of brands and stores.
Drawings
The invention may be better understood by referring to the following description taken in conjunction with the accompanying drawings.
FIG. 1 is a flow chart of the system of the present invention.
Detailed Description
As shown in fig. 1, the system of the present invention comprises: the system comprises a store management system, a client, an AI face analysis box, a cloud server, a terminal and a server, wherein the store management system is used for creating a member file, the system is used for recording all records and behavior data consumed by a member in a store, classifying and filing all generated data, forming a member label according to classified data characteristics, the member arrives at the store, a camera captures member face information, the AI face analysis box performs data analysis, the cloud server performs operation, pairing and information storage, the terminal displays and sends member arrival at the store reminding and labeling information, and the store realizes accurate service and conversion.
In the first step, a member profile is created in the store management system, and the basic profile information includes: name, member account number, gender, age, phone, native place, photo, micro-signal, registration time, and registered store, etc.
In the second step, the system records all records and behavior data of the member consuming in the store. The method comprises the steps of automatically recording by a system and manually inputting records, wherein the record and behavior data comprise: member image, consumption data, preference data, activity data, consumption period and frequency data, etc
The detailed recorded member data includes:
(1) member image: uploading a recent front photo of each member;
(2) consumption data: the system comprises a consumption shop, a consumption brand, a consumption type, an amount, a date, a payment mode and a participation mode;
(3) preference data: including preferred styles, colors, categories, etc.;
(4) activity data: including the status of the activities and consumption engaged in and feedback on the activities;
(5) period and frequency of consumption: including year, season, month, week, daily consumption time period and frequency statistics;
in the third step, the system classifies, counts and archives all generated data to form member feature labels, so that the consumption portrait of the member can be very clearly known according to the member label information, and label extraction is mainly performed from the following three aspects:
firstly, living habits:
(1) dividing the member into gender and age groups according to the gender and the age of the member, and extracting a gender label and an age group label;
(2) extracting frequent shopping store information of the members according to the data statistical ranking of the consumption stores of the members;
(3) extracting member consumption time period information and activity information according to member consumption time statistics;
secondly, consumption habit:
(1) extracting a brand grade label frequently purchased by a member according to information statistics of member consumption brands;
(2) extracting whether the member is a label of a frequently participating activity or a group buying and general consuming member according to the data statistics of the participating activity;
thirdly, behavior habit:
(1) extracting payment mode labels commonly used by the members according to statistics of payment modes of the members;
(2) extracting the activities frequently attended by the user, the activity frequency and the feedback information of the activities according to the data statistics of the attended activities;
in the fourth step, after the member arrives at the store, the camera installed in the store captures the face information of the member, the AI face recognition box performs data analysis, the cloud server performs operation, pairing and information storage, and the information is analyzed through the database information of the cloud. The method mainly comprises the following three steps:
(1) establishing a database containing a large number of facial images (images of input members and labeled information);
(2) obtaining a target face image to be identified currently (face information captured by a member-to-store camera) through various modes;
(3) comparing and screening (data analysis) the target face image with the existing face images in the database;
in the fifth step, the terminal equipment sends out welcome language voice of a certain member to the store, and meanwhile, the terminal equipment system (the PU end and the mobile end) pops up member label information. When listening to the prompt voice, the store clerk checks the member label data information popped up by the computer or the mobile end store management system, so that the user-friendly service and marketing can be timely and accurately provided for the member, and the transaction rate of the order is improved.
The invention solves the problems that the store management system can not carry out characteristic classification management, label identification, member arrival store reminding and timely and automatic member label information presentation on members.
The above-mentioned description only shows the embodiments of the present invention, and the description is more specific and detailed, but it should not be understood as the limitation of the scope of the invention, and it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the spirit of the invention, and these are all within the scope of the invention, therefore, the scope of the invention should be determined by the appended claims.
Claims (6)
1. A system for store member management and services. The method is characterized in that: the system records all records and behavior data consumed by the members in the store, classifies and files all generated data, forms member labels according to classified data characteristics, enables the members to arrive at the store, enables the cameras to capture member face information, enables the AI face analysis box to conduct data analysis, enables the cloud server to conduct operation, pairing and information storage, enables the terminals to display and send member arrival store reminding and labeling information, and enables the stores to achieve accurate service and conversion.
2. A system for store member management and services according to claim 1, characterized in that: creating a member profile in a store management system, the profile information including: name, member account number, gender, age, phone, native place, photo, micro-signal, registration time, and registered store, etc.
3. A system for store member management and services according to claim 1, characterized in that:
the system records all records and behavior data of member consumption in the store. The system comprises automatic recording and manual input information, and the recorded data comprises: member images, consumption data, preference data, activity data, consumption period and frequency data, and the like.
(1) Member image: uploading a recent front photo of each member;
(2) consumption data: including the store of consumption, the brand of consumption, the category of consumption, the amount, the date, the payment mode and the participation mode;
(3) preference data: including preferred styles, colors, categories, etc.;
(4) activity data: including the status of the activities and consumption engaged in and feedback on the activities;
(5) period and frequency of consumption: including year, season, month, week, daily consumption time period and frequency statistics.
4. A system for store member management and services according to claims 2 and 3, characterized in that: and the system classifies, counts and archives all generated data to form a member characteristic label. The consumption portrait of the member can be clearly known according to the member label information. Tag extraction is mainly performed from the following three aspects:
firstly, living habits:
(1) dividing the member into gender and age groups according to the gender and the age of the member, and extracting a gender label and an age group label;
(2) extracting information of frequent shopping stores of the members according to the data statistical ranking of the consumption stores of the members;
(3) extracting member consumption time period information and activity information according to member consumption time statistics;
secondly, consumption habit:
(1) extracting a brand grade label frequently purchased by a member according to information statistics of member consumption brands;
(2) extracting whether the member is a label of a frequently participating activity or a group buying and general consuming member according to the data statistics of the participating activity;
thirdly, behavior habit:
(1) extracting payment mode labels commonly used by the members according to statistics of payment modes of the members;
(2) and extracting the activities frequently participated by the user, the activity frequency and the feedback information of the activities according to the data statistics of the participated activities.
5. A system for store member management and services according to claim 4, wherein: after the member arrives at the store, the face information of the member is captured by a camera in the store, the AI face recognition box performs data analysis, and the cloud server performs operation, pairing and information storage and analyzes the information through the database information of the cloud. The method mainly comprises the following three steps:
(1) establishing a database containing a large number of facial images (images of input members and labeled information);
(2) obtaining a target face image to be identified currently (face information captured by a member-to-store camera) through various modes;
(3) the target face image is compared and screened (data analysis) against existing face images in the database.
6. A system for store member management and services according to claim 5, characterized in that: the terminal equipment sends out welcome speech of a certain member to the store, and meanwhile, the terminal equipment system (the PU end and the mobile end) pops up member label information. And when listening to the prompt voice, the store clerk checks the member label data information popped up by the computer or the mobile end store management system.
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| CN202010853538.2A CN112085521A (en) | 2020-08-19 | 2020-08-19 | System for managing and serving store members |
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| CN202010853538.2A CN112085521A (en) | 2020-08-19 | 2020-08-19 | System for managing and serving store members |
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| CN113283933A (en) * | 2021-05-26 | 2021-08-20 | 深圳市博优思创科技发展有限公司 | Member management method and system based on multidimensional information |
| CN113408756A (en) * | 2021-06-18 | 2021-09-17 | 杭州闪援车管家汽车服务有限公司 | Pipe inspection system for automobile washing maintenance |
| CN115563185A (en) * | 2022-10-11 | 2023-01-03 | 广东智科信息技术发展有限公司 | One-card system for user information statistics |
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