CN111178966A - Latent customer behavior analysis method and system based on face recognition - Google Patents
Latent customer behavior analysis method and system based on face recognition Download PDFInfo
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- 238000004458 analytical method Methods 0.000 title claims abstract description 25
- 238000012163 sequencing technique Methods 0.000 claims abstract description 24
- 230000006399 behavior Effects 0.000 claims description 28
- 238000000034 method Methods 0.000 claims description 13
- 238000000605 extraction Methods 0.000 claims description 11
- 239000000284 extract Substances 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 7
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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
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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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
- G06V40/168—Feature extraction; Face representation
Abstract
The invention provides a potential customer behavior analysis method and system based on face recognition, wherein a store customer is shot through a camera, characteristic information is extracted and face data is generated when a face image is detected, the face image is compared with the existing face data, analysis is performed according to matching results in different situations, if the face image is a potential customer, sequencing information is output, an information template A is sent to a store employee terminal, and if the face image is not a potential customer, an information template B is sent to the store employee terminal; when the matching is unsuccessful, a customer information table is created for the customer, and sequencing information is output and stored, so that recommendation for potential customers is realized, the coverage of recommended groups is improved, the existing member customers are not recommended by analyzing the purchasing records of the member customers, but the behavior of the user is analyzed by recording based on face recognition, an effective recommendation result is obtained, and meanwhile, data support is provided for developing new members of stores and improving the sales efficiency.
Description
Technical Field
The invention relates to a potential customer behavior analysis method and system based on face recognition, and belongs to the technical field of information analysis.
Background
With the increasing maturity of face recognition technology, many fields begin to apply face recognition technology to actual scenes.
At present, in places such as some market brand special cabinets, brand exclusive sales stores, when the passenger flow volume is big the store clerk hardly takes into account each to shop customer, and the customer who is not taken in the reception by the store clerk enters the shop and browses commodity after, does not leave any information and just leaves the store, can lead to partial customer's loss like this, when customer reentry store, if still do not have the store clerk to take in, store customer loss rate can be higher, and customer shopping experience is also not good.
In the existing technical level, a merchant mainly identifies whether a store customer is a member of the merchant by using a face recognition technology, and if the store customer is the member, a member management system of the merchant can push activity or coupon information of the store to a terminal of the customer so as to improve sales of store commodities. However, for potential customers (non-members or customers without purchase records), the prior art is rarely concerned with analyzing potential customer-to-store behavior to assist marketers in developing further marketing campaigns for potential customers.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a potential customer behavior analysis method and system based on face recognition, which help a marketer to record and analyze the store arrival behaviors of non-members or potential customers without purchase records by means of an information technology, provide accurate marketing for the potential customers and improve the shopping experience of the customers.
The technical scheme adopted by the invention for solving the technical problem is as follows: the potential customer behavior analysis method based on face recognition is provided, and comprises the following steps:
(1) shooting store customers through cameras in various areas of a store, and transmitting face images to a face feature extraction unit when the cameras detect the face images;
(2) the face feature extraction unit extracts feature information of the face image, generates face data and sends the face data to the central server;
(3) the central server compares the face data with the existing face data and identifies whether the face information of the customer exists or not; if the face data is matched with the corresponding data, the step (3.1) is carried out, otherwise, the step (3.2) is carried out;
(3.1) judging whether the customer is a potential customer, if the purchase record of the customer does not exist in the central server, outputting the sequencing information of the customer, the identification times and the commodity information to the potential customer through the central server for storage, and simultaneously sending an information template A to a terminal of a shop assistant; if the customer is not a potential customer, the customer is a regular customer, and the central server sends an information template B to the terminal of the clerk;
(3.2) the central server creates a customer information table for the customer, and simultaneously records the times that the customer is identified in each area of the store and the commodity information of the area; and outputting the sequencing information of the customer, the identification times and the commodity information through the central server and storing the sequencing information.
Further, in the step (3.1), the terminal of the store clerk is provided with an information template A and an information template B in advance, and the contents of the information template A and the information template B are set in a self-defined mode according to the fields of the customer information base.
Further, the sorting method of the customer-identification times-commodity information sorting information in the step (3.1) and the step (3.2) is to sort according to the times of customers being identified in one area, and the sorting with the large number of identified times is in the front.
The invention also provides a potential customer behavior analysis system based on the method, which comprises the following steps:
the camera is used for capturing a face image;
the face feature extraction unit is used for extracting feature information in the face image;
the central server is used for analyzing and processing the potential customer behaviors of the face image;
and the shop assistant terminal is used for receiving the information pushed by the central server.
Further, the central server specifically includes:
the face database is used for storing face data;
the customer information base is used for storing a customer information table and a customer face information table;
and the customer behavior analysis module is used for outputting the sequencing information of the customer-identification times-commodity information.
Further, the central server further includes:
and the customer information management module is used for creating a customer information table.
One or more technical schemes provided by the invention at least have the following technical effects or advantages:
firstly, shooting a customer in a shop through a camera, extracting characteristic information and generating face data when a face image is detected, then comparing the face data with the existing face data, analyzing the face data according to matching results in different situations, further judging whether the customer is a potential customer or not when the matching is successful, if so, outputting ordering information of the customer, identification times and commodity information, and simultaneously sending an information template A to a shop assistant terminal, and if not, sending an information template B to the shop assistant terminal; when the matching is unsuccessful, a customer information table is created for the customer, and sequencing information is output and stored, so that recommendation for potential customers is realized, the coverage of recommended groups is improved, the record analysis and analysis are performed on the behaviors of the user based on face recognition instead of merely performing the literary analysis recommendation of purchase records for existing member customers, an effective recommendation result is obtained, and meanwhile, data support is provided for developing new members of stores and improving the sales efficiency.
Drawings
Fig. 1 is a flowchart of a potential customer behavior analysis method based on face recognition provided by the invention.
Fig. 2 is a block diagram of a potential customer behavior analysis system based on face recognition provided by the invention.
Detailed Description
The invention is further illustrated by the following figures and examples.
The invention provides the method and the system for analyzing the behavior of the potential customer based on the face recognition, solves the technical problem that the analysis of the potential customer is not in place in the prior art, realizes the purpose of helping a marketing person to record and analyze the behavior of a non-member or a potential customer who does not have a purchase record in the shop by means of an information technology, provides accurate marketing for the potential customer, and improves the shopping experience of the customer.
In order to solve the above problems, the technical solution in the embodiments of the present invention has the following general idea:
firstly, shooting a customer at a shop through a camera, extracting characteristic information when a face image is detected and generating face data, then comparing the face data with the existing face data, analyzing the face data according to matching results in different situations, further judging whether the customer is a potential customer or not when the matching is successful, if so, outputting sequencing information of the customer, identification times and commodity information, and simultaneously sending an information template A to a shop assistant terminal, and if not, sending an information template B to the shop assistant terminal; when the matching is unsuccessful, a customer information table is created for the customer, and sequencing information is output and stored, so that recommendation for potential customers is realized, the coverage of recommended groups is improved, the record analysis and analysis are performed on the behaviors of the user based on face recognition instead of merely performing the literary analysis recommendation of purchase records for existing member customers, an effective recommendation result is obtained, and meanwhile, data support is provided for developing new members of stores and improving the sales efficiency.
For better understanding of the above technical solutions, the following detailed descriptions are provided in conjunction with the drawings and the detailed description of the embodiments.
Referring to fig. 1 and fig. 2, a method for analyzing potential customer behavior based on face recognition according to an embodiment of the present invention includes the following steps:
(1) shooting store customers through cameras in various areas of a store, and transmitting face images to a face feature extraction unit when the cameras detect the face images;
(2) the face feature extraction unit extracts feature information of the face image, generates face data and sends the face data to the central server;
(3) the central server compares the face data with the existing face data and identifies whether the face information of the customer exists or not; if the face data is matched with the corresponding data, the step (3.1) is carried out, otherwise, the step (3.2) is carried out;
(3.1) judging whether the customer is a potential customer, if the purchase record of the customer does not exist in the central server, outputting the sequencing information of the customer, the identification times and the commodity information to the potential customer through the central server for storage, and simultaneously sending an information template A to a terminal of a shop assistant; if the customer is not a potential customer, the customer is a regular customer, and the central server sends an information template B to the terminal of the clerk;
(3.2) the central server creates a customer information table for the customer, and simultaneously records the times that the customer is identified in each area of the store and the commodity information of the area; and outputting the sequencing information of the customer, the identification times and the commodity information through the central server and storing the sequencing information.
Further, in the step (3.1), the terminal of the store clerk is provided with an information template A and an information template B in advance, and the contents of the information template A and the information template B are set in a self-defined mode according to the fields of the customer information base.
Further, the sorting method of the customer-identification times-commodity information sorting information in the step (3.1) and the step (3.2) is to sort according to the times of customers being identified in one area, and the sorting with the large number of identified times is in the front.
Specific examples are provided below.
The first embodiment is as follows:
(1) the method comprises the steps that a camera is installed in advance, and an area shot by the camera is bound with types of commodities placed in the area at the background; setting an information template received by a shop assistant terminal, wherein the template content can be customized according to fields in a customer information base, and an information template A and an information template B are made for potential customers and non-potential customers;
(2) when a customer enters a store, shooting the customer at the store through cameras in various areas of the store, when the cameras detect face images, transmitting the face images to a face feature extraction unit, and extracting feature information of the face images by the face feature extraction unit, generating face data and sending the face data to a central server;
(3) the central server compares the received face characteristics through a face library, and if the face information exists, the central server sends a customer ID corresponding to the face information to a customer management module; if the face information does not exist, a customer ID is newly established for the face and is sent to a customer information management module and a customer behavior analysis module;
(3.1) after the customer information management module receives the existing customer ID and traverses, if the customer identity is a potential customer, a message template A is sent to a shop assistant terminal; if the customer identity is a regular customer, sending a message template B to a shop assistant terminal;
(3.2) after the customer information management module receives the new customer ID, creating a customer information table for the customer; the customer behavior analysis module generates a sequencing table through the received image information, and the sequencing rule is as follows: the sequencing list obtains the commodity information sequencing information of the customer through accumulated calculation of times (the time interval of camera shooting is fixed and can be defined) of camera shooting and identification when the customer browses commodities in different areas.
According to the above steps, it is assumed that there are ten types of products, A, B, C, D, E, F, G, H, I, J, in one store of a certain merchant. The ten types of commodities are placed in different areas, and 1 camera is placed in each area and used for capturing and recognizing face images. After the camera is installed, the camera is bound with the commodity type of the area in the background, for example, the camera 1 is bound with the commodity type A, and the camera 2 is bound with the commodity type B … … to set the time interval of the camera for acquiring the face image to be ten seconds.
Customers are classified into three types: a, b, and c, assuming that a is a new customer (no record of purchases and first time of store), assuming that b is a potential customer (no record of purchases and not first time of store), and assuming that c is an old customer (record of purchases).
1. The first enters a store. A camera at the door acquires a face image of the person A, and if the face information is not found, an information table of the person is created in a customer information base; when a person browses commodities in a store and the face data is shot by cameras in all areas, recording the data in a customer information table, and obtaining the following table according to a sorting rule:
| sort order | Type of goods | Number of times of accumulation | Accumulated time length |
| 1 | A | 25 | 250s |
| 2 | B | 13 | 130s |
| 3 | C | 10 | 100s |
| 4 | D | 3 | 30s |
TABLE 1 ordering information of customers-identification times-merchandise information of customer A
2.B, entering a store. And a camera at the door acquires a face image of the person B, finds a sorting table (similar to the above table) accumulated last time or in the near term in the system, generates a template message and sends the template message to a mobile terminal of a shop assistant in a store. The template message may be self-configured within the system, examples of which are as follows:
customer ID: 20190523
Customer face picture
Number of customer visits: 3
And recommending the commodity types: 1, A; 2.B
Such as: b, accumulating the effective residence time of 250s at the A-type commodities, and predicting the purchase intention; the effective stay time 130s is accumulated at the type B commodities, and the commodities are interested and can be recommended.
3. The third enters a store. And a camera at the door acquires a human face image of the third party, and the system returns a purchase record of the third party to send to the mobile terminal of the store clerk in the store. The template message may be self-configured within the system, examples of which are as follows:
customer ID: 20190102
Customer face picture
Customer purchase record: commodity J1 of commodity type J, purchase time: 2019-05-23.
After a plurality of clients of different types enter a certain area at the same time, face image information is acquired at regular time and sent to a client behavior analysis module, and the face image information is separately recorded and dynamically updated in respective tables.
Referring to fig. 2, a system for analyzing potential customer behavior according to an embodiment of the present invention includes:
the camera is used for capturing a face image;
the face feature extraction unit is used for extracting feature information in the face image;
the central server is used for analyzing and processing the potential customer behaviors of the face image;
and the shop assistant terminal is used for receiving the information pushed by the central server.
In this embodiment, the central server specifically includes:
the face database is used for storing face data;
the customer information base is used for storing a customer information table and a customer face information table;
the customer behavior analysis module is used for outputting sequencing information of customers, identification times and commodity information;
and the customer information management module is used for creating a customer information table.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (7)
1.A potential customer behavior analysis method based on face recognition is characterized by comprising the following steps:
(1) shooting store customers through cameras in various areas of a store, and transmitting face images to a face feature extraction unit when the cameras detect the face images;
(2) the face feature extraction unit extracts feature information of the face image, generates face data and sends the face data to the central server;
(3) the central server compares the face data with the existing face data and identifies whether the face information of the customer exists or not; if the face data is matched with the corresponding data, the step (3.1) is carried out, otherwise, the step (3.2) is carried out;
(3.1) judging whether the customer is a potential customer, if the purchase record of the customer does not exist in the central server, outputting the sequencing information of the customer, the identification times and the commodity information to the potential customer through the central server for storage, and simultaneously sending an information template A to a terminal of a shop assistant; if the customer is not a potential customer, the customer is a regular customer, and the central server sends an information template B to the terminal of the clerk;
(3.2) the central server creates a customer information table for the customer, and simultaneously records the times that the customer is identified in each area of the store and the commodity information of the area; and outputting the sequencing information of the customer, the identification times and the commodity information through the central server and storing the sequencing information.
2. The method of claim 1, wherein: in the step (3.1), the terminal of the store clerk is preset with an information template A and an information template B, and the contents of the information template A and the information template B are set by self according to the fields of the customer information base.
3. The method of claim 1 or 2, wherein: in the step (3.1), the information template A comprises face information of the potential customer and interested commodity information; the information template B includes a record of the last purchases by the old customer.
4. The method of claim 1, wherein: the sequencing method of the sequencing information of the customer, the identification times and the commodity information in the step (3.1) and the step (3.2) is to sequence according to the times of the customer being identified in one area, and the sequencing with the large number of identified times is in the front.
5. A system for analyzing behavior of a potential customer based on the method of claim 1, comprising:
the camera is used for capturing a face image;
the face feature extraction unit is used for extracting feature information in the face image;
the central server is used for analyzing and processing the potential customer behaviors of the face image;
and the shop assistant terminal is used for receiving the information pushed by the central server.
6. The system for analyzing the behavior of potential customers of claim 5, wherein: the central server specifically includes:
the face database is used for storing face data;
the customer information base is used for storing a customer information table and a customer face information table;
and the customer behavior analysis module is used for outputting the sequencing information of the customer-identification times-commodity information.
7. The system for analyzing potential customer behavior of claim 6, wherein: the center server further includes:
and the customer information management module is used for creating a customer information table.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111784454A (en) * | 2020-06-30 | 2020-10-16 | 广东奥园奥买家电子商务有限公司 | Method and device for accurately recommending commodities for customers |
| CN112150193A (en) * | 2020-09-14 | 2020-12-29 | 卖点国际展示(深圳)有限公司 | Guest group analysis method, system and storage medium |
| CN112651793A (en) * | 2021-02-09 | 2021-04-13 | 广东天正计算机服务有限公司 | Intelligent retail system based on face recognition |
| CN112835954A (en) * | 2021-01-26 | 2021-05-25 | 浙江大华技术股份有限公司 | Method, device and equipment for determining target service object |
| CN112883775A (en) * | 2020-12-31 | 2021-06-01 | 深圳云天励飞技术股份有限公司 | Shop sales data analysis method and device, electronic equipment and storage medium |
| CN113487356A (en) * | 2021-07-08 | 2021-10-08 | 上海叮铃铃信息技术有限公司 | Customer management method and system based on face recognition |
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Application publication date: 20200519 |