Private domain operation method based on enterprise WeChat

Abstract

The invention discloses a private domain operation method based on enterprise WeChat. The private domain operation method comprises the following steps: constructing a customer portrait; personalized content is pushed; intelligent customer service and interaction; community operation and management; and data-driven decision making. Through the AI technology, accurate construction of customer portraits and intelligent pushing of personalized contents are realized, and the marketing efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the field of enterprise private domain traffic operation, and in particular to a private domain management method based on enterprise WeChat. Background Art

[0002] With the widespread application of WeChat for Business in the operation of private domain traffic, traditional operation methods can no longer meet the needs of enterprises for efficiency, accuracy and personalization. Most of the existing private domain operation methods rely on manual operations and preset rules, which makes it difficult to respond to customer needs and market changes in real time.

[0003] Disadvantages of existing technology:

[0004] 1. Accuracy issues in personalized content push and lack of customer feedback mechanism: After content is pushed, there is a lack of an effective customer feedback mechanism to evaluate the effectiveness of the content, making it difficult to adjust and optimize the push strategy in a timely manner.

[0005] 2. Limitations of intelligent customer service and interaction, and delayed knowledge base updates: The knowledge base of intelligent customer service needs to be updated regularly to cope with new business scenarios and problems, but existing technical solutions may have delayed knowledge base updates, affecting customer service efficiency and quality.

[0006] 3. Efficiency issues in community operation and management, and difficulty in sustaining community activity: Community operation requires continuous content input and event planning, but existing technical solutions may lack effective incentive mechanisms and creative support, making it difficult to sustain community activity.

[0007] 4. Limitations of data-driven decision-making and insufficient decision support: Data analysis results need to be converted into specific business decisions, but existing technical solutions may lack a complete decision support system, resulting in an unscientific and inefficient decision-making process. Summary of the invention

[0008] In view of the above problems, the present invention is proposed to provide a private domain management method based on enterprise WeChat that overcomes the above problems or at least partially solves the above problems.

[0009] According to one aspect of the present invention, a private domain management method based on enterprise WeChat is provided, and the private domain management method comprises:

[0010] Build customer profiles;

[0011] Push personalized content;

[0012] Intelligent customer service and interaction;

[0013] Community operation and management;

[0014] Data drives decisions.

[0015] Optionally, the building of the customer portrait specifically includes: data collection, regularly capturing the customer's basic information, chat records and purchase history through the enterprise WeChat API interface;

[0016] Data cleaning and preprocessing: deduplication, missing value filling, and outlier processing of collected data;

[0017] Extract key features based on business needs;

[0018] Use machine learning algorithms to train customer profiling models and evaluate model performance through cross-validation;

[0019] Build detailed customer profiles based on model outputs and update them in real time to reflect customer changes.

[0020] Optionally, the key features include: customer age, gender, consumption frequency and preferred categories.

[0021] Optionally, the machine learning algorithm specifically includes: decision tree, random forest and neural network.

[0022] Optionally, the pushing of personalized content includes:

[0023] Content template design: design a variety of content templates based on marketing goals and customer portraits;

[0024] Content generation, using AI algorithms to automatically generate personalized content based on customer profiles and marketing needs;

[0025] Content review and optimization, manual review or automatic verification of generated content;

[0026] Content push: Push personalized content to target customer groups through the WeChat for Business API interface.

[0027] Optionally, the content template includes text, pictures, and videos.

[0028] Optionally, the intelligent customer service and interaction specifically include:

[0029] Chatbot deployment: deploy AI chatbots in WeChat for Enterprises and configure basic questions and answer libraries;

[0030] NLP model training, using NLP technology to train chatbot models;

[0031] Intelligent customer service interaction: customers interact with chatbots through WeChat for Business, and the robots automatically answer customer questions or guide them to human customer service;

[0032] Interaction data recording and analysis: record the interaction data between customers and chatbots, analyze customer needs and behavior changes, and provide a basis for optimizing marketing strategies.

[0033] Optionally, the community operation and management specifically includes:

[0034] Community creation and classification: create communities with different themes based on customer needs and interests, and manage them by category;

[0035] Automated community management, using RPA technology and Python scripts to achieve automated community management, including group member management, group message monitoring, and group activity organization;

[0036] Community content push: formulate personalized community content push plans based on community characteristics and member needs, and realize automatic push through the WeChat for Business API interface;

[0037] Community data analysis and optimization: regularly analyze community data, evaluate operational effectiveness, and adjust community operation strategies based on data analysis results.

[0038] Optionally, the data-driven decision specifically includes:

[0039] Data integration: integrating various data in WeChat for Business, including customer data, marketing data, and community data;

[0040] Use data analysis tools to conduct data mining and analysis to discover potential market opportunities and customer needs;

[0041] Data visualization, using data visualization tools to present analysis results to decision makers in the form of charts;

[0042] Business decision making: Make scientific business decisions based on data analysis results to guide the continuous optimization and upgrading of the company's private domain traffic.

[0043] The present invention provides a private domain management method based on enterprise WeChat, which includes: building customer portraits; pushing personalized content; intelligent customer service and interaction; community operation and management; and data-driven decision-making. Through AI technology, accurate construction of customer portraits and intelligent push of personalized content are achieved, thereby improving marketing efficiency and accuracy.

[0044] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0046] Figure 1 A flowchart of a private domain management method based on enterprise WeChat provided by an embodiment of the present invention;

[0047] Figure 2 A block diagram of the composition of a system corresponding to a private domain management method based on enterprise WeChat provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0050] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0051] like Figure 1 As shown, a private domain management method based on enterprise WeChat includes:

[0052] 1. Customer portrait construction

[0053] Step 1: Data collection: Regularly capture customers’ basic information, chat records, purchase history and other data through the WeChat for Business API interface.

[0054] Step 2: Data cleaning and preprocessing: Remove duplicates, fill missing values, and process outliers on the collected data.

[0055] Step 3: Feature Engineering: Extract key features based on business needs, such as customer age, gender, consumption frequency, preferred categories, etc.

[0056] Step 4: Model training and evaluation: Use machine learning algorithms (such as decision trees, random forests, neural networks, etc.) to train the customer profiling model and evaluate the model performance through cross-validation.

[0057] Step 5: Customer portrait construction. Build a detailed customer portrait based on the model output and update it in real time to reflect customer changes.

[0058] 2. Personalized content push

[0059] Step 1: Content template design. Design a variety of content templates based on marketing goals and customer profiles, including text, pictures, videos, etc.

[0060] Step 2: Content generation: Use AI algorithms (such as text generation models, image recognition and generation technology) to automatically generate personalized content based on customer portraits and marketing needs.

[0061] Step 3: Content review and optimization: Manually review or automatically verify the generated content to ensure content quality and compliance.

[0062] Step 4: Content push: Push personalized content to target customer groups through the WeChat for Business API.

[0063] 3. Intelligent customer service and interaction

[0064] Step 1: Chatbot deployment: Deploy the AI ​​chatbot in WeChat for Business and configure the basic questions and answer library.

[0065] Step 2: NLP model training: Use NLP technology to train the chatbot model so that it can understand customer intentions and give accurate answers.

[0066] Step 3: Intelligent customer service interaction. Customers interact with the chatbot through WeChat for Business, and the chatbot automatically gives answers to customer questions or guides them to human customer service.

[0067] Step 4: Interaction data recording and analysis: Record the interaction data between customers and chatbots, analyze customer needs and behavior changes, and provide a basis for optimizing marketing strategies.

[0068] 4. Community operation and management

[0069] Step 1: Community creation and classification. Create communities with different themes based on customer needs and interests, and manage them by category.

[0070] Step 2: Automated community management: Use RPA technology and Python scripts to achieve automated community management, including group member management, group message monitoring, group activity organization, etc.

[0071] Step 3: Community content push: Develop a personalized community content push plan based on community characteristics and member needs, and implement automated push through the WeChat for Business API interface.

[0072] Step 4: Community data analysis and optimization. Regularly analyze community data, evaluate operational effectiveness, and adjust community operation strategies based on data analysis results.

[0073] 5. Data-driven decision making

[0074] Step 1: Data integration: Integrate various data in WeChat for Business, including customer data, marketing data, community data, etc.

[0075] Step 2: Data analysis and mining: Use data analysis tools to mine and analyze data to discover potential market opportunities and customer needs.

[0076] Step 3: Data visualization: Use data visualization tools to present the analysis results to decision makers in the form of charts.

[0077] Step 4: Business decision making. Make scientific business decisions based on data analysis results to guide the continuous optimization and upgrading of the company's private domain traffic.

[0078] like Figure 2 As shown, a system corresponding to a private domain management method based on enterprise WeChat includes:

[0079] Data collection layer: obtain customer data, chat records, community information, etc. through the enterprise WeChat API interface.

[0080] Data processing layer: Use big data processing platforms (such as Hadoop and Spark) to clean, convert and store data.

[0081] AI analysis layer: Integrates NLP and machine learning algorithms to build customer portraits, generate content, and provide intelligent customer service.

[0082] Application service layer: provides the front-end interface and API interface for enterprise WeChat private domain operations, and supports personalized content push, community management and other functions.

[0083] Monitoring and optimization layer: monitor operational results in real time and optimize strategies through data analysis and feedback.

[0084] Beneficial effects: Efficient and accurate: Through AI technology, accurate construction of customer portraits and intelligent push of personalized content can be achieved, improving marketing efficiency and accuracy.

[0085] Intelligent service: Deploy AI chatbots to achieve intelligent customer service and interaction, and improve customer satisfaction and response speed.

[0086] Community activity: Use AI technology to achieve automated management and personalized operation of communities, and improve community activity and user stickiness.

[0087] Data-driven: Build a comprehensive data analysis system, use AI technology to mine and analyze data, and provide a scientific basis for business decisions.

[0088] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A private domain management method based on enterprise WeChat, characterized in that: The private domain management method includes: Build customer profiles; Push personalized content; Intelligent customer service and interaction; Community operation and management; Data drives decisions.

2. According to the private domain management method based on enterprise WeChat according to claim 1, it is characterized in that: The construction of customer portraits specifically includes: Data collection: regularly capture customers’ basic information, chat records, and purchase history through the WeChat for Business API interface; Data cleaning and preprocessing: de-duplication, missing value filling, and outlier processing of collected data; Extract key features based on business needs; Use machine learning algorithms to train customer profiling models and evaluate model performance through cross-validation; Build detailed customer profiles based on model outputs and update them in real time to reflect customer changes.

3. According to the key feature of claim 2, a private domain management method based on enterprise WeChat is characterized in that: The key characteristics include: customer age, gender, consumption frequency and preferred categories.

4. According to the key feature of claim 2, a private domain management method based on enterprise WeChat is characterized in that: The machine learning algorithms specifically include: decision tree, random forest and neural network.

5. According to the private domain management method based on enterprise WeChat according to claim 1, it is characterized in that: The personalized content push includes: Content template design: design a variety of content templates based on marketing goals and customer portraits; Content generation, using AI algorithms to automatically generate personalized content based on customer profiles and marketing needs; Content review and optimization, manual review or automatic verification of generated content; Content push: Push personalized content to target customer groups through the WeChat for Business API interface.

6. A private domain management method based on enterprise WeChat according to claim 5, characterized in that: The content template includes text, pictures, and videos.

7. The private domain management method based on enterprise WeChat according to claim 1 is characterized in that: The intelligent customer service and interaction specifically include: Chatbot deployment: deploy AI chatbots in WeChat for Enterprises and configure basic questions and answer libraries; NLP model training, using NLP technology to train chatbot models; Intelligent customer service interaction: customers interact with chatbots through WeChat for Business, and the robots automatically answer customer questions or guide them to human customer service; Interaction data recording and analysis: record the interaction data between customers and chatbots, analyze customer needs and behavior changes, and provide a basis for optimizing marketing strategies.

8. The private domain management method based on enterprise WeChat according to claim 1, characterized in that: The community operation and management specifically include: Community creation and classification: create communities with different themes based on customer needs and interests, and manage them by category; Automated community management, using RPA technology and Python scripts to achieve automated community management, including group member management, group message monitoring, and group activity organization; Community content push: formulate personalized community content push plans based on community characteristics and member needs, and realize automatic push through the WeChat for Business API interface; Community data analysis and optimization: regularly analyze community data, evaluate operational effectiveness, and adjust community operation strategies based on data analysis results.

9. The private domain management method based on enterprise WeChat according to claim 1 is characterized in that: The data-driven decision-making specifically includes: Data integration: integrating various data in WeChat for Business, including customer data, marketing data, and community data; Use data analysis tools to conduct data mining and analysis to discover potential market opportunities and customer needs; Data visualization, using data visualization tools to present analysis results to decision makers in the form of charts; Business decision making: Make scientific business decisions based on data analysis results to guide the continuous optimization and upgrading of the company's private domain traffic.

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