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24

2026-06

Actual test results of Telegram marketing number detection: A set of screening methods can directly double the conversion rate

When many teams are doing Telegram marketing, they will go through a very typical stage: more and more accounts are added, the number of groups is getting larger and larger, but the actual conversion does not increase simultaneously. On the surface, it seems to be a content problem, but after multiple rounds of actual testing, it was found that the more core problems often occur "before the number enters the system."

22

2026-06

Real-time TG filter usage guide to quickly detect Telegram account status and activity

Telegram’s user base has grown rapidly in recent years, but many people have overlooked one point: rapid growth does not mean that the data is “useful”. When doing community operations, cross-border traffic diversion, or Web3 user management, the most common problem is not that there are not enough users, but that users "can see it but can't use it."

15

2026-06

Telegram user online status query to gain insight into recent active user behavior

A team that operates overseas communities once encountered a very typical situation: they had accumulated tens of thousands of members on Telegram and continued to post content every day, but the channel interaction data was always unstable. Some posts get good reads, while others get little to no feedback. Later, they did a simple split and discovered a key problem - a large number of members had not been online for a long time, and their operating rhythm was still designed according to "full active users".

16

2026-04

There are many Telegram group members but they don’t speak. Can the active screening be solved in advance?

In Telegram community operations, a common phenomenon is that the number of people in the group continues to grow, but the number of interactions becomes less and less. On the surface, the group size is expanding, but the actual proportion of effective users is declining. This situation is not a content problem, but often due to deviations in the data structure imported earlier.

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