When importing Telegram numbers in batches, which ones are active? How can I accurately identify them?

Many people encounter a common problem when filtering Telegram numbers: they have a batch of phone numbers but can't distinguish which ones are registered on Telegram and which are inactive. Manually adding friends or searching for each number is not only time-consuming and laborious but also extremely inefficient, especially when dealing with hundreds or thousands of numbers. Effective Telegram number filtering is actually the first step in any subsequent effective outreach and a crucial factor in determining the return on investment.

Why do thousands of messages disappear without a trace? It's very likely that only a few of these numbers actually have Telegram accounts active. So, is there any way to quickly and accurately identify the "active" accounts from a large number of numbers?

I. Why is it becoming increasingly "difficult" to manage a private domain on Telegram?

If you worked on Telegram private domains in the early days, you might think it was an era where "adding people guarantees feedback." But now, most teams face similar problems:

• Registration and activity levels have been checked, but the response rate remains very low.

• The same message received a reply from number A, but no response from number B.

• There are quite a few people in the group, but very few people participate in regular discussions.

This is not accidental, but an inevitable result of Telegram's private domain entering a more complex phase.

In the past, the selection logic was: "Can this account be used?" Now, the selection logic must be upgraded to: "Is this account worth using?" And "worth using" essentially means: Is there a real person behind this account?

II. How do you determine whether a number is "activated" or "activated and genuine"?

Simply checking if the number is activated is no longer sufficient. We need to analyze the number in three tiers:

• First tier: Empty or unregistered
  numbers These numbers are completely useless and should be removed.
• Second layer: Registered but potentially inactive accounts
  The detection results show that the account is active, but it might be a verification code receiving account, a secondary account, or an account that hasn't been logged in for a long time. Messages sent by these accounts will go unread, which is a waste of resources.
• Third tier: Registered and appearing real
  Accounts with profile pictures, usernames, signatures, and relatively short recent online time. These are the accounts worth reaching out to.
  
  

III. What indicators can help you identify "real accounts"?

To determine whether an account is backed by a real person, you can't just look at the account's activation status; you need to combine several key indicators:

• Is the profile picture a real person or a normal image?
• Is the username correct?
• Was your last online time recent?
• Have you joined any groups or channels?
  
  

IV. How to quickly filter out numbers that are "worth using" manually?

If you don't have many numbers, less than a few dozen, you can use manual methods combined with the indicators mentioned above to make a judgment:

Step 1: Search the number to check its status
Enter the full phone number, including the international country code, into the Telegram search box and see if the account can be found. Eliminate accounts that cannot be found.

Step 2: Click to view information
After searching, click into the profile page and check if there is an avatar, username, and signature. If there is no avatar, you can leave it aside for now.

Step 3: Check shared groups (if any).
If you and this account are in the same group, you can see which shared groups you have. The more shared groups, the more active the account is.

This method is only suitable for a small number of numbers; a few dozen is acceptable, but a few hundred would be too tiring.

V. How to quickly identify "real user accounts" in batches?

There are now some professional detection tools on the market, such as ITG full-domain screening , which can combine batch recognition and deep analysis:

Step 1: Data Import and Preprocessing
Simply import the Excel or TXT document into the tool. The tool will automatically recognize the number format and remove incorrectly formatted entries, saving processing time.

Step Two: Multi-Dimensional Batch Detection
The tool not only checks whether a number is registered, but also captures the account's public information:

• Basic status : Distinguish between valid accounts, empty accounts, and abnormal accounts.

• Profile picture status : Does the profile picture exist or not?

• Username settings : Should the username be a standard name or a string of random characters?

• Language code : The language used by the account, which helps determine the region.

• Activity estimation : Provides an activity score based on behavioral patterns.

Step 3: Result Filtering and Export
After the detection is complete, high-quality accounts can be filtered out and exported separately based on the combination of "avatar + username + high activity".

Using this method, you can accurately select hundreds of "worth using" real numbers from thousands of numbers at once.

VI. Conclusion

Identifying whether imported Telegram numbers are active is only the first step. Modern private domain operations require knowing which active numbers are backed by real people. Manual verification is suitable for sporadic operations, while tool-based filtering is better for batch processing. Choosing the right method based on the number of numbers and your specific needs is crucial for effective subsequent outreach.