To attract traffic to Telegram in 2026, first screen the robot account or the active account

existIn the Telegram traffic diversion scenario, the data question has changed from “are there users?” to “are the users valid?” As the number of accounts continues to increase, the proportion of robot accounts, abnormal accounts, and low-active users in the data has increased significantly. Without filtering, the imported user pool can easily be diluted by these low-quality data, directly affecting subsequent interactions and conversions.

In this case, a key question began to come to the forefront: when filtering, should we prioritize robot accounts or active users?

The impacts of robot accounts and low activity accounts are essentially different

These two types of accounts affect data in different ways.

The robot number belongs to"Abnormal data" often has no real behavior and may even interfere with the community structure, such as washing volume or creating false activity. Low-activity accounts are "silent data" and will not actively participate in interactions, but will not directly damage the structure.

Therefore, one is"Polluted data", one is "lowering efficiency", and the processing logic also needs to be distinguished.

Why filtering order affects final results

In large-scale data, the filtering order determines the subsequent processing cost.

If active users are screened first and there are a large number of robot accounts in the data, the results of active screening may be inaccurate; conversely, if abnormal accounts are cleared first and then active screening is performed, the user structure obtained will be more stable.

Therefore, the order affects not only efficiency but also the quality of the results.

Under what circumstances should priority be given to screening robot numbers?

In the following scenarios, it is more appropriate to deal with the robot number first.

For example, in the cold start stage, a basic user pool needs to be established quickly, but the data sources are complex; or the data needs to be clean before importing users in batches. In these cases, if abnormal accounts are not cleared first, subsequent screening can easily become ineffective.

Therefore, identifying anomalies first is the key to ensuring the data foundation.

Under what circumstances is it more appropriate to screen active users first?

When there is already a certain user base, the focus often turns to conversion efficiency.

For example, you already have a community, but the interaction is low, and you want to increase its activity; or you are doing transformational traffic, and you want to give priority to users who are more likely to respond. At this time, active users are prioritized to see results faster.

In this scenario, the data"Quality" requirements are higher than "purity".

A more stable screening method is usually layered processing

In actual operation, the more stable way is not to choose one of the two, but to deal with it in layers.

You can first identify abnormal accounts and filter out robot accounts and obviously low-quality data; then perform activity screening to filter out high-value users. Through such a process, data can be guaranteed to be clean and valid at the same time.

In this process, it can be carried out through Digital PlanetTelegram account detection, abnormal account identification and active user screening support batch processing, making the screening process more stable and reducing manual intervention.

How filtering logic affects traffic drainage effects

When the screening order is reasonable, the drainage effect will be more stable.

The imported users are more real, the interactions are more focused, and the subsequent conversion path is clearer. And if the filtering order is chaotic, there may be a situation where the amount of data is large but the actual effective users are few.

This difference will be significantly amplified in batch operations.

fromThe core change from “pulling people” to “screening people”

Telegram’s core logic of attracting traffic is changing.

In the past, more emphasis was placed on how to attract people quickly, but now more emphasis is placed on how to screen out effective users. As data complexity increases, this change will become more and more obvious.

existIn the traffic drainage environment of 2026, screening is no longer an auxiliary action, but a key step that determines the effect.

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