多维度数据筛选-WhatsApp号码筛料 | Telegram号码筛料 | Line号码筛料 | WS号码筛料

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19

2025-06

How to check the online status of WS/TG? Use Digital Planet’s multi-dimensional data screening to get it done

Multi-dimensional data filtering is becoming a core tool for the refined operation of social platforms, especially in determining the online status of users. Multi-dimensional data filtering provides a deeper and more dynamic judgment system than the traditional "registered/unregistered". Many teams doing marketing for WhatsApp, Telegram, Line and even Facebook Messenger have realized that it is not enough to just know whether the user has an account and when they registered. Only by knowing "whether this person is here now" and "whether he has been online recently" can we truly improve the message reach rate and conversion efficiency.

19

2025-06

Can multi-dimensional data filtering reveal the registration time? Digital planet social app data i detection

Multi-dimensional data filtering is an important method to accurately identify user life cycle stages, especially in social platform marketing. Multi-dimensional data filtering is no longer limited to basic judgments such as "whether there is registration or not", but extends to deeper applications, such as registration time filtering. Through the dimension of "registration time", the team can effectively determine whether the user is a new user or an old user, thereby formulating a more matching conversion strategy, operation rhythm and content recommendation logic.

19

2025-06

How to find truly active social users through multi-dimensional data filtering?

Multi-dimensional data screening is the key starting point for building a precision marketing system. Especially now that there are a huge number of social platform users and serious information redundancy, if you want to improve promotion efficiency and reduce operating costs, you must rely on multi-dimensional data screening to accurately identify user status. Through "multi-dimensional data screening", operators can systematically dismantle information such as user activity, registration time, online status, device usage type, etc., so as to retain only those customers who are "worth investing".

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