When doing Telegram community drainage, many people will encounter a situation: there are many people joining the group, but there is almost no interaction in the group, and even a large number of accounts have not spoken for a long time. This type of problem is usually not a content or operational problem, but a large number of dead and abnormal accounts mixed into the data itself.
If no filtering is done before traffic is diverted, these low-quality accounts will directly enter the community, occupying resources and reducing overall activity.
What are the general characteristics of dead accounts and abnormal accounts?
In actual data, dead accounts and abnormal accounts are not difficult to identify, but they can easily be ignored if not filtered.
Common characteristics include:
- No login or usage records for a long time
- No avatar or extremely incomplete information
- No group participation or interaction
- Account status is abnormal or unstable
Even if such accounts are pulled into the group, they will not interact and are basically worthless for attracting traffic.
Why not filtering is a waste of resources
If dead accounts and abnormal accounts are directly imported into the community, several problems will arise.
First, the activity level within the group has been reduced. After users enter, they see a large number of silent accounts, making it difficult to create an interactive atmosphere. Secondly, the management cost increases, and these accounts need to be cleaned up later. Then there is the waste of resources. Operations that could have been used to reach real users are occupied by invalid data.
Therefore, screening before drainage is more important than cleaning up after drainage.
The first step is to do basic screening and filter out invalid accounts.
Before importing data, do a round of number detection to eliminate accounts that are not registered with Telegram or are in abnormal status.
This layer can directly reduce some obviously invalid data, so that the remaining accounts have basic conditions for use.
If you skip this step, all subsequent operations will be interfered with by this data.
The second step is to screen active users and increase the interaction rate within the group.
Even if the account exists, you still need to determine whether it is in use.
When filtering, you can prioritize users with usage behaviors, such as accounts with account information and interaction records. Filtering out low-active users can significantly improve the quality of interaction within the group.
After this layer of filtering is completed, the data imported into the community will be more concentrated.
The third step is to control data quality rather than just quantity.
It is easy to pursue quantity when attracting traffic, but if the data quality is not high, the increase in the number of groups will not bring actual results.
A more reasonable approach is to control data quality first and then gradually expand the scale. In this way, the community will have basic activity from the beginning, making it easier to form a virtuous cycle.
Batch filtering can reduce invalid operations in advance
When the amount of data is large, manual filtering is difficult to complete and inconsistent judgments are prone to occur.
Through Shianman, you can perform batch detection on Telegram accounts, quickly filter dead accounts and abnormal accounts, and screen out users with usage behavior. The data has been processed before being imported into the community and does not need to be cleaned repeatedly later.
Putting the filter number in front makes it easier for the community to run
When the screening layer is completed in advance, the quality of users entering the community will be significantly improved. Interactions occur more easily and administrative costs are reduced.
Drainage itself is not a problem, the key is to choose the right people. As long as the data is clean enough, the performance of the community will usually be more stable.
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The main core functions cover multi-dimensional precise screening such as activation, activity, interaction, gender, avatar, age, online, accuracy, empty account, mobile phone device, etc., and can flexibly meet the needs of different users. Its core advantage is to integrate global mainstream social and application resources to provide users with one-stop, real-time and efficient number precision screening services, helping customers achieve global digital layout.
It is a common choice for all professional teams to complete rational screening before actually reaching users.
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