User behavior data analysis system capable of distinguishing clients by labels
A data analysis system and user technology, applied in the field of network information, can solve problems such as distinguishing users and not being able to use tags, and achieve the effects of improving efficiency, increasing diversity, and accurate tag libraries
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Embodiment 1
[0032] refer to Figure 1-2 , a user behavior data analysis system capable of labeling and distinguishing customers, comprising the following steps:
[0033] S1: Social survey, first determine the target APP, and then conduct random user surveys to collect basic information and preferences of users in the form of questionnaires;
[0034] S2: Information collection, collecting user information of the target APP. User information includes demographic attributes, credit information, and behavior characteristics. Through information collection, different types of users can be better distinguished. After collecting user information, for the data in the log, Merge and remove unnecessary fields in the log, fill in the missing content, and reduce the data to obtain simplified data;
[0035] S3: Build a tag library, and build a user tag library based on the collected user information;
[0036] S4: Match the tag library, and obtain the strongly relevant data corresponding to the set t...
Embodiment 2
[0042] refer to Figure 1-2 , a user behavior data analysis system capable of labeling and distinguishing customers, comprising the following steps:
[0043] S1: Social survey, first determine the target APP, and then conduct random user surveys to collect basic information and preferences of users in the form of questionnaires;
[0044] S2: Information collection, collecting user information of the target APP. User information includes demographic attributes, credit information, and behavior characteristics. Through information collection, different types of users can be better distinguished. After collecting user information, for the data in the log, Merge and remove unnecessary fields in the log, fill in the missing content, and reduce the data to obtain simplified data;
[0045] S3: Build a tag library, and build a user tag library based on the collected user information;
[0046] S4: Match the tag library, and obtain the strongly relevant data corresponding to the set tar...
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