Service recommendation method and device, electronic equipment and medium
By obtaining user portraits and related information, accurately recommending business contacts and personalized content solves the problem of insufficient attractiveness of existing business recommendation methods and improves business transaction rates.
Patent Information
- Application Number
- CN202510828454.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-19
- Publication Date
- 2025-09-30
AI Technical Summary
Existing business recommendation methods have low appeal to users, resulting in low business transaction rates.
By obtaining the user portrait and related information of the target user, the target display information of the first business page is accurately determined, and corresponding target operations are performed according to the related information, including recommending business contacts or adding links to business contacts, and providing personalized welcome content.
It increases users' interest and attention in business content, enhances the attractiveness of the business, and improves the business transaction rate.
Smart Images
Figure CN120723971A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of financial technology, and in particular to a business recommendation method, device, electronic device and medium. Background Art
[0002] With the rapid development of mobile internet technology, the penetration rate of smart terminal devices has increased significantly. This is particularly true for companies in the financial, insurance, healthcare, and elderly care sectors, which have large customer bases and diverse target audiences. The need for mobile application platforms to provide customer service and precision marketing is becoming increasingly urgent. Accurately recommending relevant services to users is directly related to improving marketing effectiveness and user satisfaction.
[0003] However, currently, companies generally adopt a random push method when recommending services, which makes the recommended services poorly matched with users' actual needs, resulting in the pushed services being less attractive to users, thus affecting the business transaction rate. Summary of the Invention
[0004] The main purpose of the embodiments of the present application is to propose a business recommendation method, device, electronic device and medium, aiming to solve the problem that existing business recommendation methods have low appeal to users, resulting in a low business transaction rate.
[0005] To achieve the above objectives, a first aspect of an embodiment of the present application provides a service recommendation method, the method comprising:
[0006] In response to a target user's access request to a first business page of a target business, obtaining a user profile of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business;
[0007] Determining target display information for the first business page based on the user portrait;
[0008] Displaying the first business page using the target display information;
[0009] Execute a target operation corresponding to the target service according to the association information.
[0010] In some implementations, executing a target operation corresponding to the target service according to the association information includes:
[0011] In a case where the association information indicates that the target user has added a business contact for the target business, determining a second business page for the target business based on the first information; wherein the first information includes at least one of the following: behavioral data of the target user on the first business page; business information related to the business contact in the target business;
[0012] Push the link of the second business page to the target user.
[0013] In some implementations, executing a target operation corresponding to the target service according to the association information includes:
[0014] If the association information indicates that the target user has not added a business contact for the target business, determining a business recommended contact for the target user based on second information; wherein the second information includes at least one of the following: the user portrait; and the target user's behavior data on the first business page;
[0015] Push the add link of the business recommendation contact to the target user.
[0016] In some implementations, after pushing the added link of the business recommendation contact to the target user, the method further includes:
[0017] In response to the target user's request to add the business recommendation contact, adding the target user as a friend;
[0018] Determining target welcome content based on the user profile of the target user;
[0019] The target welcome content is displayed on a page for adding the target user as a friend.
[0020] In some implementations, after adding the target user as a friend in response to the target user's add request, the method further includes:
[0021] The corresponding relationship between the target user and the link of the first business page and the business recommendation contact is recorded in the log system.
[0022] In some implementations, determining target display information of the first business page based on the user portrait includes:
[0023] The target display information of the first business page is determined based on the user portrait and the relevant information of the access request; wherein the relevant information includes at least one of the following: the request time of the access request and the weather corresponding to the request time.
[0024] In some embodiments, before obtaining a user profile of the target user in response to a target user's access request to the first business page of the target business, the method further includes:
[0025] Obtaining the user's personal information and historical behavior data, including the content data the user browses and the time the user stays on a page;
[0026] Based on the user's personal information and historical behavior data, corresponding tags are added to the user according to preset tag adding rules to generate a user profile of the user;
[0027] Constructing a user portrait table using the personal information and the user portrait, wherein the user portrait table includes multiple user portraits and the personal information corresponding to each user portrait;
[0028] The step of obtaining a user profile of the target user in response to a target user's access request to the first business page of the target business includes:
[0029] Obtaining target personal information of the target user;
[0030] A user portrait corresponding to the target personal information is obtained from the user portrait table as the user portrait of the target user.
[0031] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a service recommendation device, the device comprising:
[0032] an acquisition module, configured to, in response to a target user's access request to a first business page of a target business, acquire a user profile of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business;
[0033] a determination module, configured to determine target display information of the first business page according to the user portrait;
[0034] A display module, configured to display the first business page using the target display information;
[0035] An execution module is used to execute a target operation corresponding to the target business according to the association information.
[0036] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the service recommendation method described in the first aspect above.
[0037] To achieve the above objectives, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the service recommendation method described in the first aspect.
[0038] To achieve the above objectives, an embodiment of the present application may provide a computer program product for implementation. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device implements the service recommendation method described in the first aspect above.
[0039] The business recommendation method, device, electronic device and medium proposed in this application obtain the user portrait of the target user and the association information between the target user and the target business in response to the target user's access request to the first business page of the target business, accurately determine the target display information of the first business page through the user portrait, and use the target display information to display the first business page to achieve personalized content display, thereby increasing the user's interest and attention to the business content, recommending corresponding business contacts to the user based on the association information, and executing the target operation corresponding to the target business, thereby increasing the attractiveness of the business to the user and improving the business transaction rate. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] Figure 1 This is a flow chart of a service recommendation method provided by an embodiment of the present application;
[0041] Figure 2 yes Figure 1 Flow chart of step S104 in FIG.
[0042] Figure 3 yes Figure 1 Flow chart of step S104 in FIG.
[0043] Figure 4 This is another flowchart of the service recommendation method provided in an embodiment of the present application;
[0044] Figure 5 This is a schematic diagram of the execution flow of the service recommendation method provided in an embodiment of the present application;
[0045] Figure 6 This is a schematic diagram of the structure of the service recommendation device provided in an embodiment of the present application;
[0046] Figure 7 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0047] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0048] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.
[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.
[0050] First, let’s analyze some of the terms used in this application:
[0051] User Profile: It is a dynamic digital model with a semantic labeling system that is constructed by collecting, cleaning and analyzing multi-dimensional behavioral data and attribute characteristics of users. User profile belongs to the cross-technology category of data science and user behavior analysis. Its core goal is to transform fragmented user information into quantifiable and actionable structured feature representations, and provide decision-making basis for enterprises to implement precision marketing, product optimization and service recommendations. Specifically, the user profile system uses feature engineering methods (including data mining, machine learning and statistical analysis technologies) to establish a multi-level labeling system from four dimensions: basic user attributes (such as age, gender, region), behavioral trajectories (such as clickstream, length of stay), interest preferences (such as content orientation, brand attention) and consumption characteristics (such as purchase frequency, price sensitivity). It also uses collaborative filtering, deep learning embedding representation and other technologies to realize the association and fusion of multi-source heterogeneous data (including log data, social network relationship chains, IoT sensor data, etc.).
[0052] With the rapid development of mobile internet technology and the significant increase in the penetration of smart terminal devices, businesses are increasingly demanding customer service and precision marketing through mobile application platforms. Accurately recommending relevant services to users is directly related to improving a company's marketing effectiveness and user satisfaction.
[0053] However, currently, companies generally adopt a random push method when recommending services, which makes the recommended services poorly matched with users' actual needs, resulting in the pushed services being less attractive to users, thus affecting the business transaction rate.
[0054] Based on this, the embodiments of the present application provide a service recommendation method, device, electronic device and medium, which aim to solve the problem that existing service recommendation methods have low appeal to users, resulting in low service transaction rates.
[0055] The service recommendation method, device, electronic device, and medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the service recommendation method in the embodiments of the present application is described.
[0056] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.
[0057] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.
[0058] The business recommendation method provided in the embodiment of the present application relates to the field of financial technology. The business recommendation method provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the business recommendation method, etc., but is not limited to the above forms.
[0059] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.
[0060] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.
[0061] Figure 1 This is a flowchart of the service recommendation method provided in the embodiment of the present application. Figure 1 The service recommendation method provided in the embodiment of the present application may include but is not limited to steps S101 to S104.
[0062] Step S101: In response to a target user's access request to a first business page of a target business, obtain a user portrait of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business.
[0063] In this step, when the target user terminal initiates an access request to the first business page of the target business, the user portrait of the target user and the association information between the target user and the target business can be obtained from the cloud database based on the unique identifier of the target user. The user portrait of the target user can also be obtained from the local cache based on the unique identifier of the target user, which is not limited here, and the association information can be used to determine whether the target user has added contacts for the target business. Among them, the user's unique identifier can be the user's identity information, the user's account information, or the user's network IP, which is not limited here.
[0064] The target business can be financial insurance business, medical and health consulting business, elderly care service-related business, physical sales business, or marketing business, without limitation here.
[0065] User portraits include but are not limited to the user's basic information, interests, historical behaviors, and consumption records. In this embodiment, user portraits can be pre-built according to the target business needs and stored in a cloud database so that the user portrait of the target user can be quickly obtained when the user accesses the user portrait.
[0066] For example, a financial insurance company owns a fintech application called "xx Bank", which can provide trading and investment services for stocks, funds, and wealth management products. When user A opens the fintech application and clicks on the stock page of technology company A that the user is following, the target business is the stock trading and information page of technology company A, and the stock page of technology company A is the first business page; when receiving user A's access request to the first business page, the user portrait of user A is obtained, including user A's basic information, financial behavior characteristics (such as investment preferences, risk tolerance, asset size, etc.), interest preferences (such as high-tech, medical health, financial insurance, etc.), and whether the user has business contacts for adding the target business.
[0067] Step S102: Determine target display information of the first business page based on the user portrait.
[0068] In this step, the target display information includes at least one of the display content and display style of the first business page, and the target display information of the first business page is determined according to the user portrait.
[0069] For example, the user profile of user A includes basic information (male, 35 years old, married), financial behavior characteristics (investment preference is technology and medical health, risk tolerance is medium to high, and asset size is medium), and interest preferences (artificial intelligence, medical health). Based on the user profile of user A, the target display information can be determined to be new health insurance products, the latest business developments in the field of financial technology, etc.
[0070] Step S103: Display the first business page using the target display information.
[0071] In this step, the target display information includes any one of the target display style and the target display content. The layout of the first business page can be designed according to the target display style, the display style of the first business page can be determined according to the target display style, the display elements of the first business page can be determined according to the target display style, and the target display content can also be displayed on the first business page.
[0072] For example, when the server of the fintech application receives an access request from user A, the front end of the fintech application starts to render the page. While following the design specifications of the application, the overall layout of the page is adjusted based on the portrait of user A in terms of display content priority and display method.
[0073] Furthermore, the company's core transaction information could be prominently displayed at the top of the page, with a small risk label, such as "Medium Volatility," placed next to or below the price information. A "Related News" or "In-Depth Analysis" section could be created in the middle of the page or in the sidebar. Prioritize the company's latest announcement summaries or headlines related to its progress in fintech, artificial intelligence, and healthcare, such as "[Company Announcement] The company announced a strategic partnership with an AI giant."
[0074] Step S104: Execute a target operation corresponding to the target business according to the association information.
[0075] In this step, if the association information indicates that the target user has added a business contact of the target business, the business contact of the target business will recommend related businesses and related products to the target user; if the association information indicates that the target user has not added a business contact of the target business, a link to add the business contact of the target business will be recommended to the target user.
[0076] In this implementation, by responding to the target user's access request to the first business page of the target business, the user portrait of the target user and the association information between the target user and the target business are obtained, the target display information of the first business page is accurately determined through the user portrait, and the first business page is displayed in a target display style to achieve personalized content display, thereby increasing the user's interest and attention to the business content, recommending corresponding business contacts to the user based on the association information, and executing the target operation corresponding to the target business, thereby increasing the attractiveness of the business to users and improving the business transaction rate.
[0077] In some embodiments, as Figure 2As shown, in step S104 , the target operation corresponding to the target business is executed according to the association information, which may include but is not limited to steps S1041 to S1042 .
[0078] Step S1041: When the association information indicates that the target user has added a business contact for the target business, determine a second business page for the target business based on first information; wherein the first information includes at least one of the following: behavior data of the target user on the first business page; business information related to the business contact in the target business;
[0079] Step S1042: Push the link of the second business page to the target user.
[0080] In this implementation, when the association information indicates that the target user has added a business contact for the target business, the second business page of the target business is determined based on the target user's behavioral data on the first business page and / or the business information related to the business contact in the target business. The second business page of the target business can be a related product page or marketing activity page determined based on the target user's behavioral data on the first business page, or it can be a business personnel chat interface determined based on the business information related to the business contact in the target business, and the business personnel pushes related product activity information in the chat box.
[0081] In this implementation, the first information includes at least one of the target user's behavioral data on the first business page and business information related to the business contact in the target business, wherein the target user's behavioral data on the first business page includes browsing time, number of clicks, product types of interest, etc. on the first page, and the business information related to the business contact in the target business includes the contact's professional field, service evaluation, success cases, etc.
[0082] For example, based on the behavioral data of user B on the health insurance page and / or the information of business contacts related to health insurance, a second business interface specifically introducing the advantages and service features of health insurance is determined, and the link to the second business interface is pushed to user B via SMS, email, or in-app message.
[0083] In this embodiment, by analyzing the target user's behavioral data on the first business page, the user's interests and needs can be grasped more accurately, so as to improve the pertinence and effectiveness of business page push, enhance marketing effects, attract user clicks, and thus increase business transaction rates.
[0084] In some embodiments, as Figure 3As shown, in step S104, the target operation corresponding to the target business is executed according to the association information, which may include but is not limited to steps S1043 to S1044.
[0085] Step S1043: If the association information indicates that the target user has not added a business contact for the target business, determine a business recommended contact for the target user based on second information; wherein the second information includes at least one of the following: the user portrait; and the target user's behavior data on the first business page.
[0086] Step S1044: Push the add link of the business recommendation contact to the target user.
[0087] In this implementation, when the associated information indicates that the target user has not added the business contact of the target business, the business contact of the target user is determined based on the user portrait and / or based on the behavioral data of the target user on the first page, and the addition link of the above-mentioned business contact can be pushed to the target user through the target communication application, wherein the target communication application can be a text message, instant messaging application, etc., and the addition link of the business contact can be a QR code, a web link, or a contact method, which is not limited here.
[0088] In this implementation, the second information includes at least one item of the target user's user portrait and behavioral data of the first business page, wherein the user portrait includes age, gender, occupation, income level, business needs, etc., and the target user's behavioral data on the first business page includes browsing time, number of clicks, product types of interest, etc. on the first page.
[0089] In other implementations, a salesperson database can be established based on the salesperson's professional field, customer evaluation, business transaction volume, etc. in the enterprise to facilitate rapid matching with target users.
[0090] For example, an insurance company offers a variety of insurance product introductions on its official website (the first business page). User C, while browsing the critical illness insurance page, shows a high level of interest (as evidenced by the amount of time User C spends browsing the page and the coverage they click on), but has not added any business contacts. User C's user profile shows him as a middle-aged male with a stable income and a focus on health protection. Based on this information, salesperson A, who specializes in critical illness insurance, has excellent performance, and receives positive customer reviews, is selected from the business contact database. Salesperson A is identified as a recommended business contact for User C, and an add link is generated for Salesperson A. Based on User C's preferences, a text message is sent to User C containing the add link and a brief introduction to Salesperson A.
[0091] In this embodiment, by analyzing user behavior and portraits, accurate matching of user needs and business contacts is achieved, which improves the professionalism and service quality of business contacts, makes the business recommendations received by users more in line with their needs, and improves user satisfaction.
[0092] like Figure 4 As shown, the embodiment of the present application further provides a service recommendation method, which may include but is not limited to steps S201 to S208.
[0093] Step S201: In response to a target user's access request to the first business page of a target business, obtain a user portrait of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business.
[0094] The implementation of step S201 is the same as that of step S101. For details, please refer to the description of step S101 and will not be repeated here.
[0095] Step S202: Determine target display information of the first business page based on the user portrait.
[0096] The implementation method of step S202 is the same as that of step S102. For details, please refer to the record in step S102 and will not be repeated here.
[0097] Step S203: Display the first business page using the target display information.
[0098] The implementation of step S203 is the same as that of step S103. For details, please refer to the record in step S103 and will not be repeated here.
[0099] Step S204: When the association information indicates that the target user has not added a business contact for the target business, determine the business recommended contact for the target user based on the second information; wherein the second information includes at least one of the following: the user portrait; the behavior data of the target user on the first business page.
[0100] The implementation method of step S204 is the same as that of step S1043. For details, please refer to the record in step S1043 and will not be repeated here.
[0101] Step S205: Push the add link of the business recommendation contact to the target user.
[0102] The implementation method of step S201 is the same as that of step S1044. For details, please refer to the record in step S1044 and will not be repeated here.
[0103] Step S206: In response to the target user's request to add the business recommendation contact, add the target user as a friend.
[0104] In this step, when receiving an add request from the target user to add a business recommendation contact as a friend by clicking an add link or scanning a QR code, the target user is added to the friend list of the business recommendation contact.
[0105] Step S207: Determine target welcome content based on the user portrait of the target user.
[0106] In this step, the user portrait may include but is not limited to the user's basic information, interests and hobbies, and business needs. Based on the user portrait of the target user, the welcome content that best suits the target user is selected or generated from the preset welcome content template. The welcome content can be a welcome message, a welcome emoticon package, or a welcome picture, which is not limited here.
[0107] For example, for users who are interested in health insurance, welcome content including an introduction to the advantages of health insurance may be generated.
[0108] Step S208: Display the target welcome content on the page for adding the target user as a friend.
[0109] In this step, the generated target welcome content is sent to the user.
[0110] For example, based on the behavioral data and user portrait of user D, salesperson B who specializes in critical illness insurance business is recommended as her business recommendation contact. User D clicks the add link to add business recommendation contact B as a friend. Based on the user portrait of user D, a welcome content about the importance of critical illness insurance and the professional background of business recommendation contact B is determined. After user D adds business recommendation contact B as a friend, the above-determined welcome content is displayed in the friend chat interface between user D and business recommendation contact B.
[0111] In this embodiment, users feel valued and cared for through personalized welcome content, which improves user experience and satisfaction. In addition, accurate welcome content can easily stimulate users' willingness to further communicate with business recommendation contacts, promote user interaction, and increase business transaction rates.
[0112] The embodiment of the present application further provides a service recommendation method, which may include but is not limited to steps S301 to S309.
[0113] Step S301: In response to a target user's access request to the first business page of a target business, obtain a user portrait of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business.
[0114] The implementation of step S301 is the same as that of step S101. For details, please refer to the description of step S101 and will not be repeated here.
[0115] Step S302: Determine target display information of the first business page based on the user portrait.
[0116] The implementation method of step S302 is the same as that of step S102. For details, please refer to the record in step S102 and will not be repeated here.
[0117] Step S303: Display the first business page using the target display information.
[0118] The implementation of step S303 is the same as that of step S103. For details, please refer to the record in step S103 and will not be repeated here.
[0119] Step S304: When the association information indicates that the target user has not added a business contact for the target business, determine the business recommended contact for the target user based on the second information; wherein the second information includes at least one of the following: the user portrait; the behavior data of the target user on the first business page.
[0120] The implementation method of step S304 is the same as that of step S1043. For details, please refer to the record in step S1043 and will not be repeated here.
[0121] Step S305: Push the add link of the business recommendation contact to the target user.
[0122] The implementation method of step S301 is the same as that of step S1044. For details, please refer to the record in step S1044 and will not be repeated here.
[0123] Step S306: In response to the target user's request to add the business recommendation contact, add the target user as a friend.
[0124] The implementation of step S301 is the same as that of step S206. For details, please refer to the record in step S206 and will not be repeated here.
[0125] Step S307: Determine target welcome content based on the user portrait of the target user.
[0126] The implementation of step S307 is the same as that of step S207. For details, please refer to the record in step S207 and will not be repeated here.
[0127] Step S308: Display the target welcome content on the page for adding the target user as a friend.
[0128] The implementation method of step S308 is the same as that of step S208. For details, please refer to the record in step S208 and will not be repeated here.
[0129] Step S309: Record the corresponding relationship between the target user and the link to the first business page, and the business recommendation contact in a log system.
[0130] In this step, the link information of the target user visiting the first business page and the relevant information of the business recommendation contact recommended for the target user are collected, and the correspondence between the target user and the link information of the first business page and the relevant information of the business recommendation contact is stored in the log system.
[0131] Specifically, a log record can be generated and stored in the log system. The log record may include: the unique identifier of the target user (the target user's personal information, account information, etc.), the link to the first business page, the identifier of the business recommendation contact (the work number, name, etc. of the business recommendation contact), the record timestamp, and the time when the record was generated.
[0132] For example, after user F browses an insurance company's auto insurance product page, business contact C is recommended to him based on his user profile and behavior data. Mr. Wang then adds Manager Li as a friend. The log system will record user F's user ID, the auto insurance product page link visited by user F, the ID or name of the recommended business contact C, and the timestamp of the record generation.
[0133] In this embodiment, by recording the correspondence between users and business pages and business contacts, comprehensive tracking of user behavior and business recommendation processes is achieved, which facilitates subsequent customer service and marketing analysis, and also facilitates rapid tracing of responsibilities through the log system to ensure transparency and fairness of the service.
[0134] In some embodiments, as Figure 2 As shown, determining the target display information of the first business page according to the user portrait in step S102 may include but is not limited to step S1021.
[0135] Step S1021: determine the target display information of the first business page based on the user portrait and the relevant information of the access request; wherein the relevant information includes at least one of the following: the request time of the access request and the weather corresponding to the request time.
[0136] In this implementation, the target display information of the first business page can be determined based on the request time of the access request, the weather corresponding to the request time, and the user portrait. The daily time can be divided into multiple time periods according to actual business needs, and the current time period can be determined according to the time of the access request, such as morning, afternoon, evening, etc.
[0137] In other implementations, the target display information of the first business page may be determined based on the date corresponding to the access request time, the holiday corresponding to the date, the weather corresponding to the request time, and the user portrait.
[0138] For example, let's say a 22-year-old Sichuan user named E likes cats and scans the QR code during the Spring Festival. Based on the above information, we can match her with a young customer who also likes cats and present her with a festive Spring Festival picture featuring cats and Sichuan local characteristics.
[0139] In this embodiment, more personalized services are provided based on user portraits and access request information to meet the needs and moods of users under specific time and weather conditions, so as to improve user satisfaction and thus increase business transaction rates.
[0140] The embodiment of the present application further provides a service recommendation method, which may include but is not limited to steps S401 to S408.
[0141] Step S401: Obtain the user's personal information and historical behavior data, wherein the behavior data includes the content data browsed by the user and the user's page dwell time;
[0142] In this step, the user's personal information includes the user's basic information, as well as account information, network IP and other information that can serve as the user's unique identifier. Historical behavior data includes all content that the user has browsed on the platform, such as pages, articles, products, etc., and the user's stay time on each page or content.
[0143] Step S402: Based on the user's personal information and the historical behavior data, a corresponding tag is added to the user according to a preset tag adding rule to generate a user profile of the user;
[0144] In this step, the collected personal information and historical behavior data are pre-processed by cleaning, deduplication, formatting, and other pre-processing operations, and label adding rules are preset according to actual business needs. Based on the pre-processed data and the preset label adding rules, a corresponding label set is generated for each user to form a user portrait.
[0145] For example, the user's interest in a certain field is determined based on the type of content the user browses and the length of time the user stays there, and corresponding tags are added.
[0146] Step S403: construct a user portrait table based on the personal information and the user portrait, wherein the user portrait table includes multiple user portraits and the personal information corresponding to each user portrait;
[0147] In this step, a user portrait table containing multiple user portraits is constructed. Each user portrait entry contains the user's basic information and one or more tags.
[0148] Step S404: Obtain the target personal information of the target user;
[0149] In this step, an access request from a target user to a first business page of a target business is received, and personal information of the target user, such as the user's ID, account number, etc., is extracted from the access request or obtained through user identity identification.
[0150] Step S405: Obtain a user portrait corresponding to the target personal information from the user portrait table as the user portrait of the target user.
[0151] In this step, based on the target personal information, the corresponding user portrait entry is searched in the user portrait table. If a match is found, the user portrait is used as the user portrait of the target user.
[0152] Step S406: Determine target display information for the first business page based on the user portrait;
[0153] The implementation method of step S406 is the same as that of step S102. For details, please refer to the record in step S102 and will not be repeated here.
[0154] Step S407: displaying the first business page using the target display information;
[0155] The implementation of step S407 is the same as that of step S103. For details, please refer to the record in step S103 and will not be repeated here.
[0156] Step S408: Execute a target operation corresponding to the target business according to the association information.
[0157] The implementation method of step S408 is the same as that of step S104. For details, please refer to the record in step S104 and will not be repeated here.
[0158] For example, user G often browses health insurance-related content and stays there for a long time. According to the rules, tags such as "focus on health" and "health insurance preference" are added to user G, and a corresponding user portrait is generated; when user G visits the first business page of the insurance company (such as the homepage), the system finds the corresponding user portrait in the user portrait table through his personal information (such as user ID); based on user G's user portrait, relevant health insurance products are recommended to him, and personalized health insurance information and discount information are displayed.
[0159] In this embodiment, accurate user portraits are used to provide personalized services that meet user needs and interests, and improve the efficiency and effectiveness of marketing activities.
[0160] like Figure 5 As shown, it is a schematic diagram of the execution flow of the business recommendation method provided by this application. The activity scenario page (i.e., the first business page) is pre-configured and delivered through text messages, posters, instant messaging programs, etc. When the target user clicks on the first business page (i.e., an access request is sent to the first business page), the target user's information is collected to determine whether the target user has added a business contact. If the target user has added a business contact, the corresponding activity page or product introduction (i.e., the second business page) is recommended to the target domain user. If the target user has not added a business contact, the corresponding business recommendation contact is assigned to the target user based on the target user's user portrait and other relevant information, and the contact link of the business recommendation contact is pushed to the target user. After the target user adds the business recommendation contact, personalized welcome content is pushed to the target user, and the target user is guided to browse related activity products (the second business page).
[0161] Figure 6 This is a schematic diagram of the structure of the business recommendation device provided in the embodiment of the present application. Figure 6 The embodiment of the present application further provides a service recommendation device 800, which can implement the above service recommendation method. The service recommendation device 800 includes:
[0162] An acquisition module 801 is configured to, in response to a target user's access request to a first business page of a target business, acquire a user profile of the target user and association information between the target user and the target business; wherein the association information indicates whether the target user has added a business contact for the target business;
[0163] A determination module 802 is configured to determine target display information of the first business page based on the user portrait;
[0164] A display module 803 is configured to display the first business page using the target display information;
[0165] The execution module 804 is configured to execute a target operation corresponding to the target service according to the association information.
[0166] In some implementations, the execution module 804 includes:
[0167] a first determining submodule configured to determine, when the association information indicates that the target user has added a business contact for the target business, a second business page for the target business based on the first information; wherein the first information includes at least one of the following: behavioral data of the target user on the first business page; business information related to the business contact in the target business;
[0168] The first push submodule is used to push the link of the second business page to the target user.
[0169] In some implementations, the execution module 804 includes:
[0170] a second determination submodule configured to determine a recommended business contact for the target user based on second information if the association information indicates that the target user has not added a business contact for the target business; wherein the second information includes at least one of the following: the user portrait; and behavioral data of the target user on the first business page;
[0171] The second determining submodule is configured to push the adding link of the business recommendation contact to the target user.
[0172] In some implementations, the execution module 804 further includes:
[0173] A first adding submodule, configured to add the target user as a friend in response to the target user's request to add the business recommendation contact;
[0174] A third determination submodule is configured to determine target welcome content based on the user profile of the target user;
[0175] The first display submodule is configured to display the target welcome content on a page for adding the target user as a friend.
[0176] In some implementations, the execution module 804 further includes:
[0177] The first recording submodule is used to record the link between the target user and the first business page and the corresponding relationship between the business recommendation contact in the log system.
[0178] In some implementations, the determining module 802 further includes:
[0179] The fourth determination submodule is used to determine the target display information of the first business page based on the user portrait and the relevant information of the access request; wherein, the relevant information includes at least one of the following: the request time of the access request and the weather corresponding to the request time.
[0180] In some implementations, the service recommendation device 800 further includes:
[0181] A history acquisition module is used to obtain the user's personal information and historical behavior data, including the content data browsed by the user and the time the user stays on the page;
[0182] A portrait generation module is used to add corresponding tags to the user based on the user's personal information and the historical behavior data according to preset tag adding rules to generate a user portrait of the user;
[0183] A portrait table construction module is used to construct a user portrait table based on the personal information and the user portrait, wherein the user portrait table includes multiple user portraits and the personal information corresponding to each user portrait;
[0184] The acquisition module 801 further includes:
[0185] A first acquisition submodule is used to acquire target personal information of the target user;
[0186] The second acquisition submodule is used to obtain the user portrait corresponding to the target personal information from the user portrait table as the user portrait of the target user.
[0187] The specific implementation of the service recommendation device 800 is substantially the same as the specific embodiment of the above service recommendation method, and will not be described in detail here.
[0188] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the aforementioned service recommendation method when executing the computer program. The electronic device can be any intelligent terminal, including a desktop computer, a tablet computer, a mobile phone, and an in-vehicle computer.
[0189] See also Figure 7 , Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. The electronic device includes:
[0190] The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.
[0191] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute the service recommendation method of the embodiments of this application.
[0192] Input / output interface 903, used to implement information input and output;
[0193] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);
[0194] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );
[0195] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .
[0196] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned service recommendation method is implemented.
[0197] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0198] In addition, the embodiments of the present application may be implemented by providing a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device implements the service recommendation method in the above embodiment.
[0199] The business recommendation method, device, electronic device and medium provided in the embodiments of the present application obtain a user portrait of the target user and the association information between the target user and the target business in response to the target user's access request to the first business page of the target business, accurately determine the target display information of the first business page through the user portrait, and use the target display information to display the first business page to achieve personalized content display, thereby increasing the user's interest and attention to the business content, recommending corresponding business contacts to the user based on the association information, and executing the target operation corresponding to the target business, thereby increasing the attractiveness of the business to the user and improving the business transaction rate.
[0200] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.
[0201] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.
[0202] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.
[0203] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.
[0204] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0205] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.
[0206] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.
[0207] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0208] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.
[0209] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0210] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.
Claims
1. A business recommendation method, characterized in that: The method comprises: In response to a target user's access request to a first business page of a target business, obtaining a user profile of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business; Determining target display information for the first business page based on the user portrait; Displaying the first business page using the target display information; Execute a target operation corresponding to the target service according to the association information.
2. The method according to claim 1, characterized in that The performing of a target operation corresponding to the target service according to the association information includes: In a case where the association information indicates that the target user has added a business contact for the target business, determining a second business page for the target business based on the first information; wherein the first information includes at least one of the following: behavioral data of the target user on the first business page; business information related to the business contact in the target business; Push the link of the second business page to the target user.
3. The method according to claim 1, characterized in that The performing of a target operation corresponding to the target service according to the association information includes: If the association information indicates that the target user has not added a business contact for the target business, determining a business recommended contact for the target user based on second information; wherein the second information includes at least one of the following: the user portrait; and the target user's behavior data on the first business page; Push the add link of the business recommendation contact to the target user.
4. The method according to claim 3, characterized in that After pushing the added link of the business recommendation contact to the target user, the method further includes: In response to the target user's request to add the business recommendation contact, adding the target user as a friend; Determining target welcome content based on the user profile of the target user; The target welcome content is displayed on a page for adding the target user as a friend.
5. The method according to claim 4, characterized in that After adding the target user as a friend in response to the add request of the target user, the method further includes: The corresponding relationship between the target user and the link of the first business page and the business recommendation contact is recorded in the log system.
6. The method according to claim 1, wherein determining target display information of the first business page based on the user portrait comprises: The target display information of the first business page is determined based on the user portrait and the relevant information of the access request; wherein the relevant information includes at least one of the following: the request time of the access request and the weather corresponding to the request time.
7. The method according to claim 1, characterized in that Before obtaining a user portrait of the target user in response to a target user's access request to the first business page of the target business, the method further includes: Obtaining the user's personal information and historical behavior data, including the content data the user browses and the time the user stays on a page; Based on the user's personal information and historical behavior data, corresponding tags are added to the user according to preset tag adding rules to generate a user profile of the user; Constructing a user portrait table using the personal information and the user portrait, wherein the user portrait table includes multiple user portraits and the personal information corresponding to each user portrait; The step of obtaining a user profile of the target user in response to a target user's access request to the first business page of the target business includes: Obtaining target personal information of the target user; A user portrait corresponding to the target personal information is obtained from the user portrait table as the user portrait of the target user.
8. A business recommendation device, characterized in that: The device comprises: an acquisition module, configured to, in response to a target user's access request to a first business page of a target business, acquire a user profile of the target user and association information between the target user and the target business; wherein the association information is used to indicate whether the target user has added a business contact for the target business; a determination module, configured to determine target display information of the first business page according to the user portrait; A display module, configured to display the first business page using the target display information; An execution module is used to execute a target operation corresponding to the target business according to the association information.
9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the service recommendation method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the service recommendation method according to any one of claims 1 to 7 is implemented.