A Practical Guide to Effective Telegram Filtering: How to Quickly Identify Active, Real Users
Effective filtering on Telegram is a fundamental step in community operations and private domain outreach, and a crucial factor determining subsequent conversion efficiency. In practice, many operators find that even with a large amount of group data, the proportion of truly active users reached is often lower than expected without effective Telegram filtering methods. Based on three years of frontline experience in community data operations, this article breaks down the core logic of effective Telegram filtering from five practical dimensions to help you build a reusable filtering system.
I. Why is account activity level the first hurdle for Telegram's effective screening?
In the Telegram ecosystem, account activity directly determines message read and interaction rates. We conducted a sample test on 100,000 group messages and found that over 35% of accounts were in a "silent state"—meaning they hadn't posted anything, updated their profile picture, or changed their status in the past 90 days. Typical characteristics of these accounts include:
The last time it was released was several months or even years ago.
The profile page shows no signs of being updated.
I have never participated in any discussions since joining the group.
The profile picture is the system default or has not been changed for a long time.
The first step in effective filtering on Telegram is establishing an activity assessment model. It's recommended to use "online presence within the last 30 days" as the basic threshold, combined with "completeness of profile information" for secondary filtering. The value of activity filtering lies in its ability to concentrate limited operational resources on real users, rather than wasting them on "digital zombies."
II. How to determine the authenticity of an account by examining the profile picture and the completeness of the information?
Profile picture and completeness of information are intuitive indicators of a Telegram account's authenticity. Based on our testing data, there are significant differences in profile information between genuine users and mass-registered accounts:
Real users typically set personalized avatars, have semantically meaningful nicknames, and their profiles contain specific information.
Low-quality accounts : Profile picture is a system default or duplicate image, nickname is a random combination of letters and numbers, and bio is blank.
Marketing accounts : Their profile pictures are mostly online images or product photos, their bios are full of promotional links, and the number of groups they join is abnormally high.
For effective filtering on Telegram, it is recommended to use "non-default profile picture + readable nickname + non-empty bio" as basic scoring criteria, assigning weight to each criterion to form an account quality score. It should be noted that this method is not absolute—some genuine users may also use default profile pictures for privacy reasons, so it is necessary to combine it with other dimensions for cross-verification to avoid false positives.
III. Group Chat Behavior Analysis: Identifying "Lurking Users" and "Active Users"
Group chat activity is one of the most valuable dynamic metrics for effective filtering on Telegram. We tracked data from 200 vertical industry groups and found that active users and inactive users exhibit drastically different behavioral patterns:
Active users : They post frequently, their content stays on topic, and they use emoticons and quotes in their replies.
Lurking users : Those who join the group but do not speak, or only send a system notification upon joining the group.
Robot characteristics : Highly regular speaking times, high repetition of content, and no ability to interact with context.
In actual screening, a user's posting history over the past 30 days can be extracted, and the ratio of "posting frequency/number of days joined" can be calculated. Accounts with a ratio below 0.1 can be marked as inactive, while accounts with a ratio above 0.5 and whose content is not advertising are considered high-value targets. The advantage of this method lies in dynamic tracking—behavioral data is more difficult to fake than static data, resulting in higher screening accuracy.
IV. Cross-verification of account registration time and device fingerprint
Registration time and device information are often overlooked but extremely valuable dimensions in Telegram's effective filtering process. Newly registered accounts (within 30 days) and older accounts (over 1 year) have completely different risk characteristics:
A large number of newly registered accounts appearing : This may indicate bot registration or account farming activities; the response rate is typically below 2%.
An old account that has recently become unusually active : It may be a dormant account that has been taken over or reactivated.
Multiple accounts sharing device fingerprints : A large number of accounts are registered on the same device, showing obvious signs of batch operations.
We recommend creating a cross-matrix using the registration time, last active time, and device type. For example, accounts registered more than 180 days ago with active records within the last 30 days should have a significantly higher authenticity score than newly registered accounts with no active records. This filtering logic is particularly effective in e-commerce and financial services communities, significantly reducing the risk of reaching users.
V. Data Deduplication and Construction of Multi-Dimensional Scoring Model
The final step in effective Telegram filtering is establishing a systematic scoring model. Single-dimensional filtering is prone to misjudgment; multi-dimensional weighted scoring is a sustainable solution. Our scoring framework in practice comprises four levels:
Base score (30%) : Activity indicators, including last online time and data completeness.
Behavioral score (40%) : Quality of group chat messages, depth of interaction, and relevance of content.
Risk score (20%) : Registration time, abnormal device fingerprints, and multiple account associations.
Adjustment score (10%) : Industry-specific rules, such as language matching degree and regional relevance.
Each account ultimately receives a quality score from 0 to 100, and the operations team can set an outreach threshold based on business needs. For example, a B2B business could set the threshold at 75 points to ensure accurate reach to decision-makers; a mass consumer goods business could lower it to 60 points to broaden coverage. The core advantage of this model lies in its iterability—as data accumulates, the weights can be dynamically adjusted, and the filtering accuracy will be continuously optimized.
Effective Telegram filtering is essentially a data quality control project, not simply number filtering. From activity detection to behavioral analysis, from static data verification to dynamic scoring models, each step requires establishing judgment criteria based on real data. For teams looking to improve community operation efficiency, building a quantifiable, reproducible, and iterative filtering system is far more valuable in the long run than pursuing a "one-time cleanup." With tools like ITG's comprehensive filtering, operators can distill their experience into automated rules, upgrading effective Telegram filtering from manual operation to a system capability. This allows them to free up more energy to focus on content strategy and user relationship maintenance while ensuring accuracy.
ITG Global Screening is a leading global number screening platform that combines global number range selection, number generation, deduplication, and comparison. It offers bulk number screening and detection for 236 countries and supports 20+ social and app platforms such as WhatsApp, Line, Zalo, Facebook, Telegram, Instagram, Signal, Amazon, Microsoft and more. The platform provides activation screening, activity screening, engagement screening, gender/avatar/age/online/precision/duration/power-on/empty-number and device screening, with self-screening, proxy-screening, fine-screening, and custom modes to suit different needs. Its strength is integrating major global social and app platforms for one-stop, real-time, efficient number screening to support your global digital growth. Get more on the official channel t.me/itgink and verify business contacts on the official site. Official business contact: Telegram: @cheeseye (Tip: when searching for official support on Telegram, use the username cheeseye to confirm you are talking to ITG official.)