Private domain traffic distribution system based on WeChat social fission

Abstract

The invention discloses a private domain traffic distribution system based on WeChat social fission, and relates to the technical field of traffic distribution. The private domain traffic distribution system based on WeChat social fission comprises a user portrait and bait strategy unit, a private domain traffic pool construction and optimization unit, a fission activity implementation and monitoring unit, a user maintenance and conversion promotion unit and a data analysis and redisk optimization unit. Valuable contents are published regularly, so that the stickiness and activeness of users are enhanced, and a high-quality flow basis is provided for fission activities. And furthermore, by utilizing A / B testing and fission effect prediction, flexible adjustment of an activity strategy is realized, and the increasing speed of the number of users is remarkably increased. And finally, due to the application of a user maintenance and conversion promotion unit and a data analysis and redisk optimization unit, the user conversion rate and the repurchase rate are improved, and precious experience and optimization direction are provided for future activities through data visualization analysis and sensitivity evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic distribution, and specifically provides a private domain traffic distribution system based on WeChat social fission. Background Art

[0002] Private domain traffic refers to the traffic that a brand or an individual independently owns, can freely control, and can be utilized multiple times for free or at low cost. It mainly comes from users' active attention, registration, subscription and other behaviors, such as WeChat friends, WeChat groups, enterprise WeChat groups, moments, official account fans, etc. Enterprises need to establish their own private domain traffic pools to store and operate the users diverted from public domain traffic. Private domain traffic distribution refers to the promotion and distribution of targeted content, products or services through the user resources accumulated and operated by a brand or an individual through its own channels (such as official websites, social media accounts, WeChat mini-programs, apps, etc.).

[0003] For example, a content push method and a social network platform based on big data and private domain traffic disclosed in the publication number CN113098934A analyze, through the user subscription information knowledge base corresponding to the private domain traffic pool of the target platform users to whom content is to be pushed, the interactive user interest characteristics of each interactive platform user in the service subscription content provided by the social network platform and the target user interest characteristics of the target platform users in the service subscription content, and then, based on the interactive user interest characteristics and the target user interest characteristics, push the service subscription content based on the private domain traffic pool of the target platform users.

[0004] However, as shown in the above technologies, at present, some enterprises still have the following defects in the distribution of private domain traffic:

[0005] Lack of precision in operation: Many enterprises lack precision in the operation of private domain traffic and often neglect the analysis and integration ability of user data. This results in enterprises being unable to accurately understand user needs and preferences, and thus it is difficult to provide personalized services and products;

[0006] Low traffic conversion rate: Although private domain traffic has a certain degree of stickiness, the conversion rate is often not high. This may be because enterprises lack effective conversion strategies in the operation process, or because users have insufficient interest in products or services.

[0007] High operation cost: In order to maintain the private domain traffic pool, enterprises need to invest a large amount of manpower, material resources and financial resources. However, due to problems such as low conversion rate and poor interactivity, these investments often fail to obtain corresponding returns. Summary of the Invention

[0008] In view of the deficiencies of the prior art, the present invention provides a private domain traffic distribution system based on WeChat social fission, which solves some defects existing in the distribution of private domain traffic by some enterprises at present.

[0009] To achieve the above objectives, the present invention is realized through the following technical solutions: A private domain traffic distribution system based on WeChat social fission, comprising:

[0010] A user portrait and bait strategy unit, used to construct a target user portrait, analyze user preferences, set bait strategies, and locate the audience through questionnaire surveys and data analysis means, calculate the bait cost-benefit ratio, and select the most cost-effective bait plan;

[0011] A private domain traffic pool construction and optimization unit, used to build a private domain traffic pool for official accounts and communities, regularly publish valuable content to attract user attention and retention, and through data analysis, evaluate the content effect, optimize the content strategy, improve user stickiness and activity, and provide a high-quality traffic foundation for fission activities;

[0012] A fission activity implementation and monitoring unit, used to design fission activity rules, produce fission posters, start fission activities, monitor activity data through A / B testing and fission effect prediction means, adjust activity strategies in a timely manner, optimize fission effects, and achieve rapid growth in the number of users;

[0013] A user maintenance and conversion improvement unit, used for user life cycle management, formulating marketing strategies for different stages, finding out the key factors affecting the conversion rate by analyzing conversion rate data, optimizing page design and price strategies, improving user conversion rate and repurchase rate, and achieving effective conversion of private domain traffic;

[0014] A data analysis and review optimization unit, used to use data visualization tools to visually analyze the data of fission activities, evaluate the activity effect through sensitivity analysis means, and summarize activity experience.

[0015] Preferably, the user portrait and bait strategy unit includes:

[0016] A user portrait positioning module, which constructs a detailed user portrait through market research and data analysis means, sets parameters such as age, gender, region, consumption ability, and interest preferences to accurately locate the target user group;

[0017] A bait design module, which designs baits that meet the needs of target users according to the user portrait, such as coupons, discount codes, free trial packs, etc., and then conducts cost-benefit analysis:

[0018] Using the formula: Conduct cost-benefit analysis, establish a set A=(A 1 , A 2 , A 3 ,..., A n ) of the bait cost-benefit ratios of different schemes, and select the maximum bait cost-benefit ratio Amax The corresponding decoy plan.

[0019] Preferably, the processing of the private domain traffic pool by the private domain traffic pool construction and optimization unit includes:

[0020] Construction of official accounts and service accounts:

[0021] Content planning: According to the user portrait, plan valuable content such as health knowledge, product introductions, and promotional activities to improve user stickiness;

[0022] Data analysis: Use parameters such as the number of reads, likes, and forwards to analyze user preferences and optimize the content strategy;

[0023] Enterprise WeChat community operation:

[0024] Community construction: Create an Enterprise WeChat community, invite target users to join, and regularly hold interactive activities to improve user activity;

[0025] Activity evaluation: Use the formula: Evaluate the community activity and adjust the operation strategy according to the evaluation results.

[0026] Preferably, the working steps of the fission activity implementation and monitoring unit include:

[0027] a1. Data collection and preprocessing: Collect data such as the initial number of users, historical fission data, user portraits, and historical behaviors, and perform preprocessing;

[0028] a2. Fission coefficient calculation: Calculate the fission coefficient according to the historical data method, A / B test method, or model prediction method;

[0029] a3. System carrying capacity evaluation: Evaluate the carrying capacity of the system through stress testing and performance testing;

[0030] a4. Prediction of traffic peaks and valleys: Use time series analysis and regression analysis to predict traffic peaks and valleys;

[0031] a5. Formulation of traffic regulation strategies: According to the prediction results, formulate traffic limiting strategies, capacity expansion strategies, and rhythm control strategies;

[0032] a6. Implementation and monitoring: Implement the fission activity and monitor the traffic changes in real time, and adjust the strategy as needed;

[0033] a7. Effect evaluation and optimization: After the activity ends, evaluate the fission effect and optimize according to the data feedback.

[0034] Preferably, the specific steps of the fission coefficient calculation include:

[0035] a2.1. Directly obtain the current number of users through the platform background data, and then calculate the expected number of users before the event based on the historical growth rate or user growth trend. Set the user base before the start of the fission activity as N, which can be the number of official account fans, the number of enterprise WeChat community members, etc.

[0036] a2.2. Set the fission coefficient K to represent the number of new users that each initial user can bring, that is, the fission efficiency. The fission coefficient K is obtained through one of the following methods: historical data method, A / B test method, or model prediction method.

[0037] Historical data method: Calculate the average fission coefficient according to the data of previous similar fission activities. The formula is expressed as:

[0038] A / B test method: Through A / B testing different fission strategies (such as poster design, reward mechanism, etc.), select the strategy with the highest fission coefficient; design an A / B test plan, implement the test, and select the strategy with the highest fission coefficient. The formula is expressed as: K A / B =max(K 1 ,K 2 ,...,K n ), where K i is the fission coefficient under different strategies.

[0039] Model prediction method: Use a machine learning model to predict the fission coefficient based on data such as user portraits and historical behaviors.

[0040] Preferably, the steps of system carrying capacity evaluation and traffic peak and valley value prediction specifically include:

[0041] Set the system carrying capacity C, which refers to the maximum number of users or requests that the platform or system can handle within a specific time, and is evaluated through stress testing or performance testing:

[0042] Stress testing: Simulate a high-concurrency scenario and test indicators such as system response time and throughput;

[0043] Performance testing: Evaluate the performance indicators of the system under different loads, such as CPU usage rate and memory occupancy;

[0044] Set the traffic peak P and valley value V, which refer to the highest and lowest points of user traffic during the fission activity, and are predicted through time series analysis or regression analysis:

[0045] Time series analysis: Use historical traffic data to establish a time series model to predict future traffic trends;

[0046] Regression analysis: According to factors such as user portraits and activity strategies, establish a regression model to predict the traffic peak and valley values.

[0047] Preferably, the flow rate adjustment strategy specifically includes:

[0048] Flow limiting strategy: When the predicted flow rate approaches or exceeds the flow limiting threshold, flow limiting measures are taken, such as restricting new user registrations, delaying message pushes, etc. Set: flow limiting threshold = C × safety factor, where the safety factor is taken as 0.8 - 0.9, leaving a buffer space for system operation when the flow rate exceeds the flow limiting threshold;

[0049] Expansion strategy: When the predicted flow rate is large, the system is expanded in advance, such as increasing the number of servers, optimizing code performance, etc.; Calculate the number of servers to be added or the requirements for performance optimization through the formula: expansion requirement = predicted peak - C;

[0050] Rhythm control: By adjusting the start time, duration, reward distribution rhythm, etc. of the fission activity, control the growth rate and peak of user traffic. The calculation formula for the optimal start time of the fission activity is expressed as:

[0051] Preferably, the analysis of the conversion rate data in the user maintenance and conversion improvement unit includes:

[0052] Analysis of conversion rate data, including:

[0053] Conversion rate calculation formula: Use the formula Calculate the overall conversion rate and monitor and analyze it regularly; Decompose the conversion rate into conversion rates of multiple steps, including click-through rate, add-to-cart rate, settlement rate, to find out the key factors affecting the overall conversion rate;

[0054] Analysis of key indicators, including:

[0055] Bounce rate analysis: Analyze the bounce rate after users visit the page, find out the reasons for the high bounce rate, and optimize it. The formula is as follows:

[0056]

[0057] Average visit duration: Analyze the average visit duration of users on the page to evaluate the attractiveness of the page and user engagement. The formula is as follows:

[0058]

[0059] Preferably, in the fission activity, the parameters of the sensitivity analysis step of the data analysis and review optimization unit are set as follows:

[0060] Fission coefficient k: Represents the average number of new users that each user can bring;

[0061] Conversion rate CR: Represents the proportion of users who actually participate from contacting the fission activity;

[0062] Reward amount R: The fission reward amount or value given to users;

[0063] Promotion channel cost C: The cost invested in different promotion channels;

[0064] Activity time T: The duration of the fission activity;

[0065] Establish a set X = (k, CR, R, C, T) for key parameters, and establish SX = (Sk, SCR, SR, SC, ST) for the sensitivity corresponding to the subsets of set X. Then the sensitivity calculation formula is expressed as:

[0066]

[0067] Among them, Δ target value represents the change in the fission activity target value (such as the number of new users), and ΔX i represents the change in the i-th key coefficient;

[0068] To conduct sensitivity analysis, it is necessary to collect historical data of the fission activity and simulate the target value after parameter changes.

[0069] Preferably, adjust the strategy of the fission activity according to the sensitivity analysis results to optimize the activity effect:

[0070] Prioritize adjusting high-sensitivity parameters: If the sensitivity of a certain parameter is high, it means that it has a greater impact on the target value. Then, prioritize adjusting the parameter with a greater impact to obtain an improvement in the effect;

[0071] Continuously monitor and iterate: Regularly collect data, recalculate the sensitivity, and adjust the strategy according to the new analysis results.

[0072] The present invention provides a private domain traffic distribution system based on WeChat social fission. Compared with the prior art, it has the following beneficial effects:

[0073] 1. For the private domain traffic distribution system based on WeChat social fission, through the accurate user portrait and bait strategy unit, the system can more effectively locate target users, improve the cost performance of the bait strategy, and thus attract more potential users. Secondly, the private domain traffic pool construction and optimization unit enhances user stickiness and activity by regularly publishing valuable content, providing a high-quality traffic foundation for the fission activity. Furthermore, the fission activity implementation and monitoring unit uses A / B testing and fission effect prediction to achieve flexible adjustment of the activity strategy, significantly improving the growth rate of the number of users. Finally, the application of the user maintenance and conversion improvement unit and the data analysis and review optimization unit not only improves the user conversion rate and repurchase rate, but also provides valuable experience and optimization directions for future activities through data visualization analysis and sensitivity evaluation.

[0074] 2. The private domain traffic distribution system based on WeChat social fission can, through detailed market research and data analysis, enable the user portrait positioning module to more accurately lock in target users and improve the pertinence of the bait strategy. The cost-benefit analysis of the bait design module ensures the economy and efficiency of the bait plan. At the same time, the private domain traffic pool construction and optimization unit effectively enhances user stickiness and activity through content planning and data analysis of official accounts and service accounts, as well as the operation and activity evaluation of enterprise WeChat communities, providing a solid traffic foundation for fission activities.

[0075] 3. The private domain traffic distribution system based on WeChat social fission can, through steps such as data collection and preprocessing, and fission coefficient calculation, enable enterprises to more accurately evaluate the user base and fission efficiency before fission activities, laying a solid foundation for the successful implementation of the activities. Secondly, the application of system capacity evaluation and prediction of traffic peaks and valleys enables enterprises to anticipate system pressure and traffic fluctuations in advance, and thus adopt targeted traffic regulation strategies such as traffic limiting, capacity expansion, and rhythm control, effectively avoiding system overload and resource waste, and ensuring the smooth operation of the activities. The formulation and implementation of these strategies are all data-driven, improving the scientificity and accuracy of decision-making, helping enterprises optimize resource allocation, enhance user experience, and achieve the best balance between fission activities and resource utilization.

[0076] 4. The private domain traffic distribution system based on WeChat social fission can, through the application of the conversion rate calculation formula, enable enterprises to more accurately measure the effectiveness of marketing activities. Regular monitoring and analysis of the conversion rate help to adjust strategies in a timely manner and improve the overall conversion efficiency. Secondly, decomposing the conversion rate into conversion rates for multiple steps helps to deeply explore the key factors affecting conversion, and thus adopt targeted optimization measures. In addition, the introduction of bounce rate analysis and average visit duration further enriches the dimensions of user behavior analysis, providing strong support for enterprises to optimize page design and enhance user experience.

[0077] 5. The private domain traffic distribution system based on WeChat social fission can, by quantifying the impact of key parameters on the activity target value, enable enterprises to more accurately identify the optimization direction and preferentially adjust highly sensitive parameters to obtain effectiveness improvement. At the same time, this method also emphasizes the balance between cost and effectiveness, as well as the importance of multi-channel testing and optimization, helping enterprises achieve the optimal allocation of resources. In addition, the process of continuous monitoring and iteration ensures that the strategy can be flexibly adjusted with changes in the market environment, enhancing the overall effectiveness of fission activities and the market competitiveness of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is the general system principle block diagram of the present invention;

[0079] Figure 2Schematic diagram of the step process for the third embodiment of the present invention. Specific implementation mode

[0080] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0081] Refer to Figure 1 - Figure 2 , the present invention provides the following five technical solutions:

[0082] The first implementation mode: A private domain traffic distribution system based on WeChat social fission, including:

[0083] A user portrait and bait strategy unit, which is used to construct a target user portrait, analyze user preferences, set bait strategies, locate the audience through questionnaire surveys and data analysis means, calculate the bait cost-benefit ratio, and select the most cost-effective bait plan;

[0084] A private domain traffic pool construction and optimization unit, which is used to build a public account and community private domain traffic pool, regularly publish valuable content, attract user attention and retention, and through data analysis, evaluate the content effect, optimize the content strategy, improve user stickiness and activity, and provide a high-quality traffic foundation for fission activities;

[0085] A fission activity implementation and monitoring unit, which is used to design fission activity rules, produce fission posters, start fission activities, monitor activity data through A / B testing and fission effect prediction means, adjust activity strategies in a timely manner, optimize fission effects, and achieve rapid growth of the number of users;

[0086] A user maintenance and conversion improvement unit, which is used for user life cycle management, formulates marketing strategies at different stages, finds out the key factors affecting the conversion rate by analyzing conversion rate data, optimizes page design and price strategies, improves user conversion rate and repurchase rate, and realizes the effective conversion of private domain traffic;

[0087] A data analysis and review optimization unit, which is used to use data visualization tools to visually analyze the data of fission activities, evaluate the activity effects through sensitivity analysis means, and summarize activity experience.

[0088] In this embodiment, through the precise user portrait and bait strategy unit, the system can more effectively locate target users, improve the cost performance of the bait strategy, and thus attract more potential users. Secondly, the private domain traffic pool construction and optimization unit enhances user stickiness and activity by regularly releasing valuable content, providing a high-quality traffic foundation for the fission activity. Furthermore, the fission activity implementation and monitoring unit uses A / B testing and fission effect prediction to achieve flexible adjustment of the activity strategy, significantly increasing the growth rate of the user population. Finally, the application of the user maintenance and conversion improvement unit and the data analysis and review optimization unit not only improves the user conversion rate and repurchase rate, but also provides valuable experience and optimization directions for future activities through data visualization analysis and sensitivity assessment.

[0089] The second implementation method, the main difference from the first implementation method is that: the user portrait and bait strategy unit includes:

[0090] The user portrait positioning module constructs a detailed user portrait through market research and data analysis means, sets parameters such as age, gender, region, consumption ability, and interest preferences to accurately locate the target user group;

[0091] The bait design module designs baits that meet the needs of target users according to the user portrait, such as coupons, discount codes, free trial packs, etc., and then conducts a cost-benefit analysis:

[0092] Using the formula: Conduct a cost-benefit analysis, establish a set A=(A 1 , A 2 , A 3 ,..., A n ) for the bait cost-benefit ratios of different schemes, and select the bait scheme corresponding to the maximum bait cost-benefit ratio A max .

[0093] The processing of the private domain traffic pool by the private domain traffic pool construction and optimization unit includes:

[0094] Construction of official accounts and service accounts:

[0095] Content planning: According to the user portrait, plan valuable content, such as health knowledge, product introductions, promotional activities, etc., to improve user stickiness;

[0096] Data analysis: Use parameters such as the number of reads, likes, and forwards to analyze user preferences and optimize the content strategy;

[0097] Enterprise WeChat community operation:

[0098] Community construction: Create an Enterprise WeChat community, invite target users to join, and regularly hold interactive activities to improve user activity;

[0099] Activity assessment: Using the formula: Assess the community activity and adjust the operation strategy according to the assessment results.

[0100] In this embodiment, through detailed market research and data analysis, the user portrait positioning module can more accurately lock in target users and improve the pertinence of the bait strategy. The cost-benefit analysis of the bait design module ensures the economy and efficiency of the bait plan. At the same time, the construction and optimization unit of the private domain traffic pool effectively improves user stickiness and activity through content planning and data analysis of the official account and service account, as well as the operation and activity assessment of the enterprise WeChat community, providing a solid traffic foundation for the fission activity.

[0101] The third implementation method is mainly different from the first implementation method in that the working steps of the fission activity implementation and monitoring unit include:

[0102] a1. Data collection and preprocessing: Collect data such as the initial number of users, historical fission data, user portraits, and historical behaviors, and perform preprocessing;

[0103] a2. Fission coefficient calculation: Calculate the fission coefficient according to the historical data method, A / B test method, or model prediction method;

[0104] a3. System carrying capacity assessment: Assess the system's carrying capacity through stress testing and performance testing;

[0105] a4. Prediction of traffic peak and valley values: Use time series analysis and regression analysis to predict traffic peak and valley values;

[0106] a5. Formulation of traffic regulation strategies: According to the prediction results, formulate traffic limiting strategies, capacity expansion strategies, and rhythm control strategies;

[0107] a6. Implementation and monitoring: Implement the fission activity, monitor the traffic changes in real time, and adjust the strategy as needed;

[0108] a7. Effect evaluation and optimization: After the activity ends, evaluate the fission effect and optimize according to the data feedback.

[0109] Through steps such as data collection and preprocessing, and fission coefficient calculation, this embodiment enables enterprises to more accurately evaluate the user base and fission efficiency before the fission activity, laying a solid foundation for the successful implementation of the activity. Secondly, the application of system carrying capacity assessment and traffic peak and valley prediction enables enterprises to predict system pressure and traffic fluctuations in advance, so as to adopt targeted traffic regulation strategies, such as current limiting, capacity expansion, and rhythm control, which effectively avoids system overload and resource waste, and ensures the smooth operation of the activity. The formulation and implementation of these strategies are based on data-driven, which improves the scientificity and accuracy of decision-making, helps enterprises optimize resource allocation, improve user experience, and achieve the best balance between fission activities and resource utilization.

[0110] The fission coefficient calculation steps specifically include:

[0111] a2.1. Directly obtain the current number of users through the platform background data, and then calculate the expected number of users before the activity based on the historical growth rate or user growth trend. Set the user base before the fission activity to N, which can be the number of public account fans, the number of corporate WeChat community members, etc.;

[0112] a2.2. Set the fission coefficient K to represent the number of new users that each initial user can bring, that is, the fission efficiency; the fission coefficient K is obtained by one of the historical data method, A / B test method or model prediction method:

[0113] Historical data method: Based on the data of previous fission activities of the same type, the average fission coefficient is calculated. The formula is:

[0114] A / B testing method: Through A / B testing of different fission strategies (such as poster design, reward mechanism, etc.), select the strategy with the highest fission coefficient; design an A / B testing plan, implement the test, and select the strategy with the highest fission coefficient. The formula is: K A / B =max(K 1 , K 2 , ..., K n ), where K i is the fission coefficient under different strategies;

[0115] Model prediction method: Use machine learning models to predict the fission coefficient based on user portraits, historical behavior and other data.

[0116] The user base is set by comprehensively considering the historical growth rate and user growth trend, which improves the accuracy of user base estimation. Secondly, a variety of methods (historical data method, A / B testing method, model prediction method) are introduced to obtain the fission coefficient K, which enhances the flexibility and scientificity of the fission coefficient calculation. Finally, the specific meaning of the fission coefficient K is clarified, that is, the number of new users that each initial user can bring, making quantitative evaluation of the fission effect possible.

[0117] The steps for evaluating the system's carrying capacity and predicting the peak and valley values of traffic specifically include:

[0118] Set the system carrying capacity C, which refers to the maximum number of users or requests that the platform or system can handle within a specific time, and evaluate it through stress testing or performance testing:

[0119] Stress testing: Simulate high-concurrency scenarios and test indicators such as system response time and throughput;

[0120] Performance testing: Evaluate the performance indicators of the system under different loads, such as CPU usage rate and memory occupancy;

[0121] Set the peak traffic P and valley value V, which refer to the highest and lowest points of user traffic during the fission activity, and predict them through time series analysis or regression analysis:

[0122] Time series analysis: Use historical traffic data to establish a time series model to predict future traffic trends;

[0123] Regression analysis: Establish a regression model based on factors such as user portraits and activity strategies to predict the peak and valley values of traffic.

[0124] Through the comprehensive application of stress testing and performance testing, the system's carrying capacity can be evaluated more accurately, ensuring the stable operation of the system in high-concurrency scenarios; secondly, the methods of time series analysis and regression analysis are introduced to predict the peak and valley values of traffic, improving the scientificity and accuracy of prediction, which helps enterprises better cope with traffic fluctuations and optimize resource allocation; finally, the application of these methods makes system evaluation and traffic prediction more data-driven, providing strong support for enterprise decision-making.

[0125] The traffic regulation strategies specifically include:

[0126] Flow limiting strategy: When the predicted traffic approaches or exceeds the flow limiting threshold, take flow limiting measures, such as restricting new user registrations and delaying message pushes. Set: Flow limiting threshold = C × safety factor, where the safety factor is taken as 0.8 - 0.9, leaving a buffer space for the system operation when the traffic exceeds the flow limiting threshold;

[0127] Expansion strategy: When the predicted traffic is large, expand the system in advance, such as increasing the number of servers and optimizing code performance; Calculate the number of servers to be added or the requirements for optimizing performance through the formula: Expansion requirement = Predicted peak - C;

[0128] Rhythm control: By adjusting the start time, duration, reward distribution rhythm, etc. of the fission activity, control the growth rate and peak value of user traffic. The calculation formula for the best start time of the fission activity is expressed as:

[0129] By setting a reasonable current-limiting threshold and taking current-limiting measures, the risk of system collapse due to traffic overload is effectively avoided, enhancing the stability and reliability of the system. Secondly, the application of the capacity expansion strategy ensures the smooth operation of the system during high-traffic periods. By accurately calculating the capacity expansion requirements, reasonable allocation and optimization of resources are achieved. Finally, the rhythm control strategy provides enterprises with a means to flexibly adjust the fission activities, helping enterprises better control the growth rhythm of user traffic, optimize the user experience, and at the same time achieve the best balance between traffic and resource utilization.

[0130] The main difference between the fourth implementation method and the first implementation method is that the analysis of conversion rate data in the user maintenance and conversion improvement unit includes:

[0131] Analysis of conversion rate data, including:

[0132] Conversion rate calculation formula: Use the formula to calculate the overall conversion rate, and regularly monitor and analyze it; decompose the conversion rate into conversion rates of multiple steps, including click-through rate, add-to-cart rate, and settlement rate, to identify the key factors affecting the overall conversion rate;

[0133] Analysis of key indicators, including:

[0134] Bounce rate analysis: Analyze the bounce rate after users visit the page, find out the reasons for the high bounce rate, and optimize it. The formula is as follows:

[0135]

[0136] Average visit duration: Analyze the average visit duration of users on the page to evaluate the attractiveness of the page and user engagement. The formula is as follows:

[0137]

[0138] Through the application of the conversion rate calculation formula, enterprises can more accurately measure the effectiveness of marketing activities. Regularly monitoring and analyzing the conversion rate helps to adjust strategies in a timely manner and improve the overall conversion efficiency. Secondly, decomposing the conversion rate into conversion rates of multiple steps helps to deeply explore the key factors affecting conversion, so as to take targeted optimization measures. In addition, the introduction of bounce rate analysis and average visit duration further enriches the dimensions of user behavior analysis, providing strong support for enterprises to optimize page design and improve user experience.

[0139] The main difference between the fifth implementation method and the first implementation method is that in the fission activity, the parameters of the sensitivity analysis step in the data analysis and review optimization unit are set as follows:

[0140] Fission coefficient k: Represents the average number of new users that each user can bring.

[0141] Conversion rate CR: Represents the proportion of users who actually participate in the fission activity from the moment they are exposed to it.

[0142] Reward amount R: The fission reward amount or value given to users.

[0143] Promotion channel cost C: The cost invested in different promotion channels.

[0144] Activity time T: The duration of the fission activity.

[0145] Establish a set X = (k, CR, R, C, T) for the key parameters, and establish SX = (Sk, SCR, SR, SC, ST) for the sensitivity corresponding to the subsets of the set X. According to actual needs, more parameters can be added, and the sensitivity calculation formula is expressed as:

[0146]

[0147] Among them, Δ target value represents the change in the target value of the fission activity (such as the number of new users), and ΔX i represents the change in the i-th key coefficient;

[0148] To conduct sensitivity analysis, it is necessary to collect historical data of the fission activity and simulate the target value after parameter changes; for example, it can be assumed that the fission coefficient increases from 1.2 to 1.3, and then calculate the change in the target value, and then obtain the sensitivity of the fission coefficient.

[0149] Adjust the strategy of the fission activity according to the sensitivity analysis results to optimize the activity effect:

[0150] Prioritize adjusting high-sensitivity parameters: If the sensitivity of a certain parameter is high, it means that it has a greater impact on the target value, so prioritize adjusting the parameter with a greater impact to improve the effect; for example, if the sensitivity of the fission coefficient is the highest, it can be considered to increase the fission reward, optimize the fission mechanism or improve user participation to increase the fission coefficient;

[0151] Balance cost and effect: When adjusting parameters, it is also necessary to consider the balance between cost and effect; for example, although increasing the reward amount may increase the conversion rate, it will also increase the cost; therefore, it is necessary to determine the optimal reward amount based on the sensitivity analysis results and cost-benefit analysis;

[0152] Multi-channel testing and optimization: Multi-channel testing and optimization can be performed for parameters such as promotion channel cost and time. By investing different costs in different channels and observing the changes in target values, it is possible to determine which channel has the highest cost-effectiveness and optimize the promotion strategy. At the same time, by adjusting the activity time, the best activity duration can be found to maximize the activity effect.

[0153] Continuous monitoring and iteration: Sensitivity analysis of fission activities is not a one-time task, but a process that requires continuous monitoring and iteration. As the market environment changes and user behavior evolves, the sensitivity of key parameters may change. Therefore, it is necessary to regularly collect data, recalculate sensitivity, and adjust strategies based on new analysis results.

[0154] By quantifying the impact of key parameters on the activity target value, companies can more accurately identify optimization directions and prioritize the adjustment of highly sensitive parameters to achieve improved results. At the same time, this method also emphasizes the balance between cost and effect, as well as the importance of multi-channel testing and optimization, which helps companies achieve optimal resource allocation. In addition, the process of continuous monitoring and iteration ensures that strategies can be flexibly adjusted as the market environment changes, improving the overall effect of fission activities and the market competitiveness of companies.

[0155] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0156] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0157] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A private domain traffic distribution system based on WeChat social fission, characterized in that: include: User portrait and bait strategy unit, used to build target user portraits, analyze user preferences, set bait strategies, locate audiences through questionnaires and data analysis, calculate bait cost-effectiveness, and select the most cost-effective bait solution; The private traffic pool construction and optimization unit is used to build the public account and community private traffic pool, regularly publish valuable content, attract user attention and retention, and evaluate content effects and optimize content strategies through data analysis; The fission activity implementation and monitoring unit is used to design fission activity rules, make fission posters, launch fission activities, monitor activity data through A / B testing and fission effect prediction methods, adjust activity strategies in a timely manner, and optimize fission effects; User maintenance and conversion improvement unit is used for user life cycle management, formulating marketing strategies at different stages, analyzing conversion rate data, identifying key factors affecting conversion rate, optimizing page design and pricing strategy, and improving user conversion rate and repurchase rate; The data analysis and review optimization unit is used to use data visualization tools to conduct visual analysis of various data of fission activities, evaluate the effectiveness of activities through sensitivity analysis, and summarize activity experience.

2. A private domain traffic distribution system based on WeChat social fission according to claim 1, characterized in that: The user portrait and bait strategy unit includes: User portrait positioning module, through market research and data analysis, builds detailed user portraits, sets age, gender, region, spending power, interest preference parameters, and accurately locates the target user group; The bait design module designs baits that meet the needs of target users based on user portraits, and then conducts cost-benefit analysis: Using the formula: Perform cost-benefit analysis and establish a set A = (A1, A2, A3, ..., A n ), select the maximum bait cost-effectiveness ratio A max Corresponding bait scheme.

3. According to claim 1, a private domain traffic distribution system based on WeChat social fission is characterized by: The processing of the private domain traffic pool by the private domain traffic pool construction and optimization unit includes: Public account and service account construction: Content planning: plan valuable content based on user portraits; Data analysis: Analyze user preferences and optimize content strategies using reading volume, likes, and reposts; Enterprise WeChat community operation: Community building: Create corporate WeChat communities, invite target users to join, and regularly hold interactive activities to increase user activity; Activity evaluation: Using the formula: Evaluate community activity and adjust operational strategies based on the evaluation results.

4. According to claim 1, a private domain traffic distribution system based on WeChat social fission is characterized by: The working steps of the fission activity implementation and monitoring unit include: a1. Data collection and preprocessing: collect the initial number of users, historical fission data, user portraits, historical behavior data, and perform preprocessing; a2. Calculation of fission coefficient: Calculate the fission coefficient based on historical data method, A / B test method or model prediction method; a3. System carrying capacity assessment: Evaluate the system carrying capacity through stress testing and performance testing; a4. Traffic peak and valley prediction: Use time series analysis and regression analysis to predict traffic peak and valley values; a5. Flow regulation strategy formulation: formulate flow limiting strategy, capacity expansion strategy and rhythm control strategy according to the prediction results; a6. Implementation and monitoring: Implement fission activities, monitor traffic changes in real time, and adjust strategies as needed; a7. Effect evaluation and optimization: After the activity is over, evaluate the fission effect and optimize it based on data feedback.

5. A private domain traffic distribution system based on WeChat social fission according to claim 4, characterized in that: The fission coefficient calculation step specifically includes: a2.

1. Directly obtain the current number of users through the platform background data, and then calculate the expected number of users before the activity based on the historical growth rate or user growth trend, and set the user base before the fission activity to N; a2.

2. Set the fission coefficient K to represent the number of new users that each initial user can bring, that is, the fission efficiency; the fission coefficient K is obtained by one of the historical data method, A / B test method or model prediction method: Historical data method: Based on the data of previous fission activities of the same type, the average fission coefficient is calculated. The formula is: A / B testing method: Use A / B testing to test different fission strategies and select the strategy with the highest fission coefficient; design an A / B testing plan, implement the test, and select the strategy with the highest fission coefficient. The formula is: K A / B =max(K1, K2, ..., K n ), where K i is the fission coefficient under different strategies; Model prediction method: Use machine learning models to predict the fission coefficient based on user portraits and historical behavior data.

6. A private domain traffic distribution system based on WeChat social fission according to claim 4, characterized in that: The system carrying capacity assessment and flow peak and valley value prediction steps specifically include: Set the system carrying capacity C, which refers to the maximum number of users or requests that the platform or system can handle within a specific period of time, and is evaluated through stress testing or performance testing: Stress testing: simulate high-concurrency scenarios to test system response time and throughput indicators; Performance testing: evaluate the performance indicators of the system under different loads; Set the traffic peak value P and valley value V, which refer to the highest and lowest points of user traffic during the fission activity, and predict through time series analysis or regression analysis: Time series analysis: Use historical traffic data to build a time series model and predict future traffic trends; Regression analysis: Based on user portraits and activity strategy factors, a regression model is established to predict traffic peaks and valleys.

7. A private domain traffic distribution system based on WeChat social fission according to claim 4, characterized in that: The flow regulation strategy specifically includes: Current limiting strategy: When the predicted flow is close to or exceeds the current limiting threshold, current limiting measures are taken and set: current limiting threshold = C × safety factor, where the safety factor is 0.8-0.9, to reserve buffer space for system operation when the flow exceeds the current limiting threshold; Expansion strategy: When large traffic is predicted, system expansion is performed in advance. The formula: expansion demand = predicted peak value - C is used to calculate the number of servers to be added or the need to optimize performance. Rhythm control: By adjusting the start time, duration, and reward distribution rhythm of the fission activity, the growth rate and peak value of user traffic can be controlled. The calculation formula for the optimal start time of the fission activity is expressed as:

8. According to claim 1, a private domain traffic distribution system based on WeChat social fission is characterized by: The analysis of conversion rate data in the user maintenance and conversion improvement unit includes: Conversion rate data analysis, including: Conversion rate calculation formula: Use the formula Calculate the overall conversion rate, and monitor and analyze it regularly; break down the conversion rate into the conversion rates of multiple steps, including click-through rate, add-to-cart rate, and checkout rate, to find out the key factors that affect the overall conversion rate; Key indicator analysis, including: Bounce rate analysis: Analyze the bounce rate after users visit the page, find out the reasons for the high bounce rate, and optimize it. The formula is as follows: Average Visit Duration: Analyze the average visit duration of users on a page to evaluate the attractiveness and user engagement of the page. The formula is as follows:

9. A private domain traffic distribution system based on WeChat social fission according to claim 1, characterized in that: In the fission activity, the sensitivity analysis step of the data analysis and replay optimization unit sets the parameters as follows: Fission coefficient k: represents the average number of new users that each user can bring; Conversion rate CR: indicates the proportion of users who are exposed to fission activities and actually participate in them; Reward amount R: the amount or value of the fission reward given to the user; Promotion channel costs C: costs invested in different promotion channels; Activity time T: duration of fission activity; For the key parameters, a set X = (k, CR, R, C, T) is established, and for the sensitivity corresponding to the subset of the set X, SX = (Sk, SCR, SR, SC, ST) is established. The sensitivity calculation formula is expressed as: Among them, Δ target value represents the change in the fission activity target value, ΔX i Represents the change of the i-th key coefficient; To perform sensitivity analysis, it is necessary to collect historical data on fission activity and simulate target values ​​after parameter changes.

10. A private domain traffic distribution system based on WeChat social fission according to claim 9, characterized in that: Adjust the strategy of fission activities according to the results of sensitivity analysis to optimize the activity effect: Prioritize adjustment of highly sensitive parameters: If a parameter has a high sensitivity, it means that it has a greater impact on the target value. In this case, the parameter with a greater impact should be adjusted first to improve the effect. Continuous monitoring and iteration: Regularly collect data, recalculate sensitivity, and adjust strategies based on new analysis results.

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