Dynamic management method based on user portrait

Abstract

The invention relates to the technical field of data analysis and processing, in particular to a dynamic management method based on a user portrait, which comprises the following steps: during specific use, firstly collecting static data and dynamic data of a user; performing tagging processing on the collected static data and dynamic data of the user in combination with a data use scene; constructing a user portrait based on the user tag, and performing deep analysis; the user portrait analysis result is applied to product experience optimization and service strategy making; the application effect of the portrait analysis result is evaluated and fed back, so that the problems that in the prior art, due to the fact that users in reality are dynamic, the demands and behaviors of the users change remarkably along with changes of time, environment and other variables, the changes cannot be captured, and the user experience is poor are solved. And the technical problem that the product experience really meeting the diversified requirements of the user cannot be provided is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis and processing, and in particular to a dynamic management method based on user portraits. Background Art

[0002] In the current digital age, user portraits, as a key tool for understanding and predicting user behaviors, preferences, and needs, play an irreplaceable role in improving product experience and optimizing service strategies. Traditional user portrait construction methods mostly use static user data collected at a specific moment or stage, which can outline the basic profile of users to a certain extent.

[0003] However, since real users are dynamic, their needs and behaviors will change significantly with time, environment and other variables. The above method cannot capture these changes, resulting in the inability to provide a product experience that truly meets the diverse needs of users. Summary of the invention

[0004] The purpose of the present invention is to provide a dynamic management method based on user portraits, aiming to solve the technical problem in the prior art that, since users in reality are dynamic, their needs and behaviors will change significantly with time, environment and other variables, and the above method cannot capture these changes, resulting in the inability to provide a product experience that truly meets the diverse needs of users.

[0005] To achieve the above purpose, the present invention adopts a dynamic management method based on user portrait, which includes the following steps:

[0006] Step 1: First, collect the user's static data and dynamic data;

[0007] Step 2: Label the collected user static data and dynamic data based on the data usage scenario;

[0008] Step 3: Build user portraits based on user tags and conduct in-depth analysis;

[0009] Step 4: Apply the results of user portrait analysis to product experience optimization and service strategy formulation;

[0010] Step 5: Evaluate and provide feedback on the application effect of the portrait analysis results.

[0011] Among them, in step one:

[0012] The static data collected refers to relatively static data, including user's natural attributes and geographical attributes;

[0013] The dynamic data collected refers to data that changes in real time, which is user behavior data, such as user browsing behavior and comment behavior on the website or APP; dynamic data collection is usually combined with static data collection. For the data that has been generated (such as the data generated on or before the day before the data analysis time), static data is used for collection, and for the data of the day, real-time data is used for collection.

[0014] Among them, the specific method of labeling the collected user static data and dynamic data in combination with the data usage scenario is as follows:

[0015] Quantitatively define user tags, and then label each user data. Common user tags include basic attribute tags, consumption behavior tags, psychological characteristic tags, and social behavior tags.

[0016] The specific methods of building user portraits based on user tags and conducting in-depth analysis are as follows:

[0017] First, based on the labels given to each user and the data usage scenarios, select the users and the dimensions to be analyzed.

[0018] Analyze the distribution of the number of users and determine whether the user data distribution can be used for user marketing based on the significant differences in the distribution;

[0019] At the same time, machine learning algorithms are used to further explore and predict user portraits to improve the accuracy and application value of user portraits.

[0020] Among them, the application scenarios of applying the results of user portrait analysis to product experience optimization and service strategy formulation include precise advertising delivery, precise recommendation of user products, and private domain user marketing.

[0021] Among them, the specific methods for evaluating and providing feedback on the application effect of the portrait analysis results are:

[0022] Collect data for the people recalled in the application step of the portrait analysis results, update the existing user label data, and supplement the user data that has not been collected yet.

[0023] Compare the user volume ratios of each dimension of user portraits before and after marketing to analyze the marketing effect;

[0024] Based on the evaluation results, adjust the user portrait construction and analysis strategy to optimize product experience and service strategy.

[0025] When collecting static and dynamic data of users, the user data needs to be anonymized or desensitized to protect user privacy;

[0026] At the same time, in actual use, privacy protection training and compliance audits are required on a regular basis to ensure that team members understand and comply with relevant laws and regulations.

[0027] Among them, the dynamic management method based on user portraits also includes: establishing a risk warning mechanism to promptly discover and deal with potential data leakage and privacy infringement issues; and formulating emergency plans to ensure that rapid response and measures can be taken in the event of emergencies such as data leakage.

[0028] When using it, you can also evaluate and select appropriate third-party data sources to ensure the accuracy and legality of the data.

[0029] Introduce social media analysis tools to explore users’ behaviors, interests and preferences on social media.

[0030] Use IoT technology to collect users' behavioral data in daily life, such as smart home usage habits and health monitoring data.

[0031] At the same time, we develop user portrait visualization tools to support multi-dimensional data display and analysis.

[0032] Provide user portrait interpretation training to help team members understand the composition and meaning of user portraits.

[0033] Customize user portrait reports based on business needs to provide data support for decision-making.

[0034] Monitor the operational performance of the entire method to promptly identify and resolve potential technical issues.

[0035] Based on business needs and technological development, the user portrait management method is expanded and optimized in terms of functionality.

[0036] Back up user data regularly to ensure data security and recoverability.

[0037] Pay attention to industry dynamics and the latest technological trends, and introduce new technologies and methods in a timely manner to improve the accuracy and application value of user portraits.

[0038] Regularly evaluate and summarize user portrait dynamic management methods to identify existing problems and areas for improvement.

[0039] Encourage team members to participate in relevant training and exchange activities to improve their professional skills and knowledge.

[0040] The dynamic management method based on user portrait of the present invention, when used specifically, first collects the static data and dynamic data of the user; labels the collected static data and dynamic data of the user in combination with the data usage scenario; constructs a user portrait based on the user label and conducts an in-depth analysis; applies the user portrait analysis results to product experience optimization and service strategy formulation; and evaluates and provides feedback on the application effect of the portrait analysis results. In this way, the technical problem in the prior art that, because users in reality are dynamic, their needs and behaviors will change significantly with time, environment and other variables, and the above method cannot capture these changes, resulting in an inability to provide a product experience that truly meets the diverse needs of users.

[0041] The dynamic management method based on user portraits of the present invention solves the problems of lack of data timeliness and lack of evaluation mechanism for authenticity and accuracy of traditional static user portrait management methods; at the same time, it can realize dynamic dimensional analysis of user portraits instead of being limited to limited dimensions, which is conducive to providing more refined marketing population portraits and improving the self-update and iteration mechanism of the user portrait management method. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is a flowchart of the steps of the dynamic management method based on user portrait of the present invention. DETAILED DESCRIPTION

[0044] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0045] See also Figure 1 , Figure 1 It is a flowchart of the steps of the dynamic management method based on user portrait of the present invention.

[0046] The present invention provides a dynamic management method based on user portrait, comprising the following steps:

[0047] S101, first collect the user's static data and dynamic data;

[0048] For this specific implementation, the collected static data refers to relatively static data, including user natural attributes and geographical attributes;

[0049] The dynamic data collected refers to data that changes in real time, which is user behavior data, such as user browsing behavior and comment behavior on the website or APP; dynamic data collection is usually combined with static data collection. For the data that has been generated (such as the data generated on or before the day before the data analysis time), static data is used for collection, and for the data of the day, real-time data is used for collection.

[0050] In addition, encryption technology is used to store and transmit user data to prevent data leakage and illegal access.

[0051] Establish a strict data access permission control mechanism to ensure that only authorized personnel can access sensitive data.

[0052] Conduct data security audits and risk assessments regularly to promptly identify and address potential security risks.

[0053] S102, labeling the collected user static data and dynamic data in combination with data usage scenarios;

[0054] For this specific implementation, combined with the data usage scenario, the specific method of labeling the collected user static data and dynamic data is as follows:

[0055] Quantitatively define user tags, and then label each user data. Common user tags include basic attribute tags, consumption behavior tags, psychological characteristic tags, and social behavior tags.

[0056] S103. Build user portraits based on user tags and conduct in-depth analysis;

[0057] For this specific implementation, firstly, based on the tags given to each user and according to the data usage scenario, the user is circled and the dimension to be analyzed is selected;

[0058] Analyze the distribution of the number of users and determine whether the user data distribution can be used for user marketing based on the significant differences in the distribution;

[0059] At the same time, machine learning algorithms are used to further explore and predict user portraits to improve the accuracy and application value of user portraits.

[0060] S104. Apply the results of user portrait analysis to product experience optimization and service strategy formulation;

[0061] For this specific implementation method, the application scenarios of applying the user portrait analysis results to product experience optimization and service strategy formulation include precise advertising delivery, precise recommendation of user products, and private domain user marketing.

[0062] S105. Evaluate and provide feedback on the application effect of the portrait analysis results.

[0063] For this specific implementation, the specific method for evaluating and providing feedback on the application effect of the image analysis results is as follows:

[0064] Collect data for the people recalled in the application step of the portrait analysis results, update the existing user label data, and supplement the user data that has not been collected yet.

[0065] Compare the user volume ratios of each dimension of user portraits before and after marketing to analyze the marketing effect;

[0066] Based on the evaluation results, adjust the user portrait construction and analysis strategy to optimize product experience and service strategy.

[0067] In addition, when collecting static and dynamic data of users, the user data needs to be anonymized or desensitized to protect user privacy;

[0068] At the same time, in actual use, privacy protection training and compliance audits are required on a regular basis to ensure that team members understand and comply with relevant laws and regulations.

[0069] Among them, the dynamic management method based on user portraits also includes: establishing a risk warning mechanism to promptly discover and deal with potential data leakage and privacy infringement issues; and formulating emergency plans to ensure that rapid response and measures can be taken in the event of emergencies such as data leakage.

[0070] At the same time, during actual use, set up a user feedback portal in the product or service to facilitate users to provide opinions and suggestions at any time; organize user surveys and interviews regularly to deeply understand users' real needs and pain points; use social media and other channels to interact and communicate with users and collect user feedback and opinions.

[0071] Again, the dynamic management method based on user portraits also includes: establishing a continuous improvement mechanism to continuously optimize the dynamic management method based on user portraits.

[0072] Example:

[0073] By utilizing dynamic management of user portraits, we can recommend products that are in the user's preferred category to people who enter the website by clicking on the bikini ads placed in the meta.

[0074] In the user data collection part, we use a combination of static and dynamic methods to collect data. For the static part, we use the offline data warehouse to collect the historical user data that entered the site from the bikini ads in meta. For the dynamic part, we use the real-time data warehouse to obtain the user data that entered the site from the bikini ads in meta on the same day.

[0075] In the user label cleaning part, the collected users are labeled as "meta bikini preference group".

[0076] In the user portrait analysis section, the group labeled "meta bikini preference group" was circled as the basic analysis group, and then the user preference category was selected as the portrait analysis dimension. The analysis showed that among this group of people, 60% of users preferred bikinis, 20% of users preferred one-piece swimsuits, and 7% of users preferred dresses. There were significant differences in the distribution of user preferences.

[0077] In the application part of the portrait analysis results, targeted products are recommended to people who enter the website by clicking on the bikini ads placed in the meta. 60% of the products display bikinis, 20% of the products display one-piece swimsuits, and 7% of the products display dresses.

[0078] Through dynamic data collection, we can collect in real time the distribution of product categories purchased by people who click on the bikini ads placed in meta and enter the website after seeing the recommended products. We can find that 70% of the categories purchased by users are bikinis and 22% are conjoined users, and we can get a new user profile that meets the significant difference. In addition, the proportion of bikinis in the categories actually purchased exceeds 60% and reaches 70%. We can appropriately increase the proportion of bikinis in the products that people who click on the bikini ads placed in meta and enter the website can see.

[0079] A dynamic management method based on user portraits in this embodiment is used. When it is used specifically, the static data and dynamic data of users are first collected; the collected static data and dynamic data of users are labeled in combination with data usage scenarios; user portraits are constructed based on user labels and in-depth analysis is performed; the results of user portrait analysis are applied to product experience optimization and service strategy formulation; and the application effect of the portrait analysis results is evaluated and feedback is provided. In this way, the technical problem in the prior art that, because users in reality are dynamic, their needs and behaviors will change significantly with time, environment and other variables, and the above method cannot capture these changes, resulting in the inability to provide a product experience that truly meets the diverse needs of users.

[0080] The dynamic management method based on user portraits of the present invention solves the problems of lack of data timeliness and lack of evaluation mechanism for authenticity and accuracy of traditional static user portrait management methods; at the same time, it can realize dynamic dimensional analysis of user portraits instead of being limited to limited dimensions, which is conducive to providing more refined marketing population portraits and improving the self-update and iteration mechanism of the user portrait management method.

[0081] What is disclosed above is only a preferred embodiment of the present invention, and it certainly cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A dynamic management method based on user portraits, It is characterized in that The following steps are involved: Step 1: First, collect the user's static data and dynamic data; Step 2: Label the collected user static data and dynamic data based on the data usage scenario; Step 3: Build user portraits based on user tags and conduct in-depth analysis; Step 4: Apply the results of user portrait analysis to product experience optimization and service strategy formulation; Step 5: Evaluate and provide feedback on the application effect of the portrait analysis results.

2. The dynamic management method based on user portrait according to claim 1, characterized in that: In step one: The static data collected refers to relatively static data, including user's natural attributes and geographical attributes; The dynamic data collected refers to data that changes in real time, which is user behavior data, such as user browsing behavior and comment behavior on the website or APP; dynamic data collection is usually combined with static data collection. For the generated data, static methods are used for collection, and for the data of the day, real-time collection methods are used for collection.

3. The dynamic management method based on user portrait according to claim 2, characterized in that: Combined with the data usage scenario, the specific method of labeling the collected user static data and dynamic data is as follows: User tags are quantitatively defined, and then each user data is labeled. User tags include basic attribute tags, consumption behavior tags, psychological characteristic tags, and social behavior tags.

4. The dynamic management method based on user portrait according to claim 3, characterized in that: The specific methods for building user portraits based on user tags and conducting in-depth analysis are as follows: First, based on the labels for each user and the data usage scenarios, select the users and the dimensions to be analyzed. Analyze the distribution of the number of users and determine whether the user data distribution can be used for user marketing based on the significant differences in the distribution; At the same time, machine learning algorithms are used to further explore and predict user portraits to improve the accuracy and application value of user portraits.

5. The dynamic management method based on user portrait according to claim 4, characterized in that: Application scenarios for applying user portrait analysis results to product experience optimization and service strategy formulation include precise advertising delivery, precise recommendations for user products, and private domain user marketing.

6. The dynamic management method based on user portrait according to claim 5, characterized in that: The specific methods for evaluating and providing feedback on the application effect of the portrait analysis results are as follows: Collect data for the people recalled in the application step of the portrait analysis results, update the existing user label data, and supplement the user data that has not been collected yet; Compare the user volume ratios of each dimension of user portraits before and after marketing to analyze the marketing effect; Based on the evaluation results, adjust the user portrait construction and analysis strategy to optimize product experience and service strategy.

7. The dynamic management method based on user portrait according to claim 6, characterized in that: When collecting static and dynamic data of users, the user data needs to be anonymized or desensitized to protect user privacy; At the same time, in actual use, privacy protection training and compliance audits are required on a regular basis to ensure that team members understand and comply with relevant laws and regulations.

8. The dynamic management method based on user portrait according to claim 7, characterized in that: The dynamic management method based on user portraits also includes: establishing a risk warning mechanism to promptly detect and deal with potential data leaks and privacy violations; and formulating emergency plans to ensure that rapid responses and measures can be taken in the event of emergencies such as data leaks.

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