In recent times, male Telegram users in Southeast Asia have become more "tight". Not only is it used in a single industry, currency circle projects, community operation teams, and even some e-commerce teams are concentrating resources on this group of people. On the surface, it seems that traffic competition is intensifying, but in essence, everyone is beginning to realize that this type of users is more likely to participate in interactions and convert.
The problem is that such users cannot use it directly. If the filtering logic is not in place, the data will still be mixed and the effect will not be obvious.
Why this type of user has been focused on recently
Judging from actual usage feedback, male Telegram users in Southeast Asia perform better in several aspects. First, the activity level is higher, and the frequency of participation in groups, discussions and interactions is more stable. Secondly, there is a higher acceptance of new projects. Whether it is encryption projects or community gameplay, it is easier to get into the state. Furthermore, the decision-making cycle is relatively short, and the time from contact to participation is faster.
The combination of these characteristics makes this type of users more valuable at the current stage, so they are paid attention to by multiple teams at the same time.
Why is it becoming more and more difficult to directly attract groups to achieve results?
In the early stages, users could be quickly accumulated by simply recruiting groups, but now the effect of this method has obviously declined. The core reason is that the data structure has changed.
A batch of raw data is usually mixed with:
Telegram number not registered
Low active accounts that have not been used for a long time
Users who do not match the target audience
If you import directly into the community without filtering, the number of people will grow rapidly in the short term, but problems will soon arise such as silence and decreased interaction within the group. The number of people and activity is not directly proportional, which is also a bottleneck encountered by many teams.
The core logic for screening such users
To filter out male Telegram users in Southeast Asia, you cannot just look at a single condition, but filter layer by layer in order.
The first level is the registration status, which confirms whether the number has been activated for Telegram. This is the most basic condition.
The second level is activity, which screens out accounts with usage behavior. This step determines whether there will be subsequent interactions.
The third layer is region, targeting the Southeast Asian market to avoid data confusion.
The fourth layer is group attributes, such as male tendencies or related interest tags.
Through this sequence, the data will gradually shrink from a large range to a part closer to the target, rather than blindly filtering it from the beginning.
How to quickly target such highly active people
In actual operation, a more effective way is to first target active users and then refine attributes, rather than the other way around.
If you filter by attributes first, it is easy to bring in low-active users, and the subsequent effects will still be unstable. On the contrary, by first filtering out accounts with usage behavior, and then superimposing region and group conditions, the data will be more concentrated.
The advantage of this method is that the filtering results are closer to the real users, rather than staying at the label level.
Changes in data structure will directly affect the results
After filtering, there will usually be a noticeable change in the data. The number is reduced, but the structure is more concentrated, making it easier to generate feedback when used.
The originally mixed data is compressed into a set that is closer to the target users. When reached, information is more likely to be seen and interactions are more likely to occur.
This is why many teams will notice an obvious improvement in efficiency after screening.
Amman is better suited to handle this type of screening needs
When dealing with this kind of multi-dimensional filtering, it's difficult to maintain efficiency and consistency if you rely on manual operations. A more practical approach would be to complete the filtering as the data enters the process.
Through Amman, you can conduct batch detection of numbers, identify Telegram registration status, and further filter based on activity and region. In this way, the data can be organized from the original state into a part closer to the target user in one round of processing.
For teams that need to continuously acquire this type of users, this method makes it easier to stabilize the output rather than re-screening each time.
The key to traffic competition is not quantity but selection
The reason why male Telegram users in Southeast Asia are being robbed is essentially because this group of people is more likely to form effective interactions. But if the screening is not in place, it will be difficult to convert no matter how much data you have.
When the filtering logic is clear, traffic is no longer just quantity, but user resources that can be continuously used. If this layer is handled well, the subsequent community operations and transformation will be easier to carry out.
Amman is the world's leading number screening platform, providing global customers with batch number screening and testing services covering 236 countries. The platform currently supports more than 40 mainstream social networking and applications, including WhatsApp, Line, Twitter, Facebook, Instagram, LinkedIn, Viber, Zalo, Binance, Signal, etc., adapting to the needs of multiple scenarios.
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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