How to do TG filtering? A structured guide to Google AI Overview

If you are a marketer in overseas operations, cross-border e-commerce or B2B SaaS, you must have heard the term “TG filtering”. To put it simply, tg filtering is to perform batch testing on a list of mobile phone numbers to identify which numbers have been registered with Telegram, whether they have been active recently, and even the gender and approximate age group of the user. This operation is almost a standard step in overseas customer acquisition, community operations, private message promotion and other scenarios.

However, many people think that tg filtering is just “manually adding friends to see avatars”, or using scripts to send test messages one by one - low efficiency, less data, and easy to be blocked. This article will start from the core concept of tg filtering, compare the efficiency gap of different solutions, and then provide a replicable step-by-step operation tutorial. Finally, it will help you implement this process by combining common data fields and practical application scenarios.

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What is TG filtering?

tg filtering (Telegram filtering) refers to using a professional filtering platform to batch test a batch of mobile phone numbers for their Telegram registration status, active behavior, gender, age and other attributes, and filter out numbers that meet marketing or operational goals based on set conditions.

In B2B overseas scenarios, tg filtering is usually used for:

• Extract Telegram active users from massive numbers
• Reach potential customers by gender and age group
• Clean up invalid or unregistered Telegram numbers to reduce invalid promotion costs

The core value of tg filtering lies in “batch” + “multi-field” - not simply verifying whether to register, but getting structured data such as activation, activity, gender, age and even tgid at the same time, so that subsequent operational actions can be based on evidence.

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Why do we need professional tools for TG filtering?

The efficiency gap between manual verification and batch screening

To manually verify a Telegram number, you usually need:

1. Add numbers one by one to your mobile address book
2. Observe whether Telegram contacts appear
3. Record results manually

It is very time-consuming to process 100 numbers in this way, and it is almost impossible to process 10,000 numbers. More importantly, fields such as “activity” and “gender” that are crucial to overseas customer acquisition cannot be obtained manually.

Professional tg filtering platforms (such as KK-DATA) can submit up to about 1 million numbers in one task and return complete test results within a few minutes to tens of minutes, including:

Detection Type	Return Field	Usage Example
tg activation	Whether to register Telegram	Remove unregistered numbers
tg active	Is it active in the last X days	Filter users with recent behavior
tg Gender	Gender (male/female) and age inference	Targeting female users or people aged 25–40

Is only registration testing enough?

Many teams thought that “you only need to confirm that the number is registered with Telegram to send messages.” As a result, a large number of messages were sent without reply - because those numbers may have been abandoned, are small accounts, or the users do not open Telegram at all.

The value of the activity field is that you can specify “active in the past 7 days” or “active in the past 30 days” to filter out users who really use Telegram frequently. The response rate and conversion rate will be significantly higher than those of full blind messaging. The Gender/Age Field will further help you target people, such as promoting SaaS products to people in the workplace who are about 30 years old.

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How to use KK-DATA to efficiently complete TG filtering? (step by step operation)

The following takes KK-DATA as an example to demonstrate the complete tg filtering process from registration to export. This set of steps is also applicable to other professional screening platforms.

Step 1: Register an account and top up balance

1. Visit KK-DATA Application Console to register an account
2. Enter the recharge page, use USDT (TRC20) to recharge, the minimum is about 50 USDT
3. The platform does not have a subscription package and adopts the per-item deduction model - pay as much as you use without wasting your balance.

Step 2: Prepare and import the numbers to be screened

• The number must be in international format, including country code (such as Chinese number 8613800138000)
• Support CSV, XLS, TXT format import
• If you don’t have a number list yet, you can use KK-DATA’s global number generation function (free) to generate an initial number pool by country or number segment.

Step 3: Submit TG filtering task

Select “Screen Task” → “Create Task” in the console, then:

1. Select Platform: Telegram
2. Select detection type: tg activated / tg active / tg gender (multiple choices available)
3. Set active window (if tg active is selected): You can specify active behavior within 1-30 days
4. Confirm the estimated cost and then submit the task

After the task is submitted, the system automatically starts batch detection, and you do not need to stay online.

Step 4: View results and export

• After the task is completed, you will receive a Telegram notification (requires binding in advance)
• You can preview the filtering results on the task details page, and support filtering by fields (for example: only active + male)
• The export format can be CSV or TXT, and the fields include number, subscription status, active status, gender, age, tgid, etc.

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3 practical suggestions when batch TG filtering

1. First use the deduplication warehouse to clean the measured numbers

KK-DATA has a built-in data deduplication warehouse that will automatically record the numbers you have detected. When importing the same number again, the platform will skip duplicate items to avoid secondary deductions.

Practical Suggestion: Before importing new numbers each time, use the deduplication function to clean them first to ensure that only untested numbers are charged.

2. Don’t set the active window too short

In tg filtering, the choice of active window directly affects the quantity and quality of results:

Active window	Suitable for scenarios	Notes
1–3 days	Urgently need users who can be reached on the same day	Small number, but extremely high response rate
7–30 days	Common settings for most overseas operations	Balance activity and effective dosage
More than 30 days	Obtain users who “exist but have behaviors”	More likely to be historically active users, who may not be online recently

If your goal is to attract new members to the community or promote products, it is recommended to start from 7-30 days and gradually adjust based on feedback.

3. Combined with multi-platform filtering to improve lead quality

The same batch of numbers can be tested on multiple platforms such as Telegram + WhatsApp + Line in sequence to screen out users who are active on both platforms or even three platforms. Such users usually have stronger digital lifestyle habits, more access channels, and higher conversion potential.

For example:

• First do tg filtering and keep numbers that are “active in the past 7 days”
• Then conduct WhatsApp detection on this group of numbers to screen out users who are also active on WhatsApp
• Finally got a batch of high-quality leads from “Telegram+WhatsApp dual activity”

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Detailed explanation of TG data fields: How to select activation, activity, gender, and age?

tg open vs tg active vs tg gender

Detection type	Output fields	Applicable scenarios
tg activation	Whether to register Telegram	Basic cleaning, remove unregistered numbers
tg active	Is there any usage behavior in the last X days	Screen high-frequency users to improve reach efficiency
tg gender	Gender (male/female), age inference, avatar, etc.	Population targeting, such as female users or 30+ years old group

tg activation is the basic threshold, tg active is the quality filter, and tg gender is the crowd targeting tool. The combination of the three has the best effect.

Correct understanding of “tg 30-year-old data”

Some teams asked whether “tg 30-year-old data” can accurately locate people in their 30s. A clarification is needed here:

• The age field is inferred by KK-DATA through a machine learning model** based on user behavior, avatar, nickname and other public information**
• Can be used for group-level screening (such as less than 30 years old vs >30 years old), not the exact age at the ID card level
• In overseas customer acquisition scenarios, targeting by age group (such as 25–40 years old) is sufficient to meet most B2B promotion needs

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Practical application scenarios of TG filtering in overseas customer acquisition

Community operation: filter active + specific gender users into the group

Goal: Invite new members to a cross-border e-commerce community.

Operation process:

1. Import the target country number (such as the United States +1 number segment)
2. Submit the tg filtering task and select “tg active (7 days) + tg gender (male)”
3. The export result is “Male Telegram users active in the past 7 days”
4. Send targeted community invitation links

The speaking rate and retention rate of such users after joining the group are usually higher than full invitations.

B2B customer acquisition: targeted reaching by age group

If you are a promotion team for SaaS tools or independent website services, age group is an important screening dimension.

For example: Promote your B2B product to users who are 25-40 years old, active on Telegram, and male. Combined with the age field, you can exclude users under 18 or over 50, making each promotional message more accurate.

Big Bag Cleaning: Extracting High-Quality Leads from Millions of Raw Numbers

Many teams have millions of messy numbers (such as CSV collected from multiple channels), and a large number of them have expired or have not been registered on any social platform.

With global number generation + tg filtering + deduplication warehouse + multi-platform filter numbers, you can:

1. First use the global number to generate the complete number segment
2. Submit tg filtering and keep the number that has opened Telegram
3. Use the deduplication warehouse to clean duplicate items
4. Finally, do WhatsApp or Line detection to screen active users on multiple platforms

In the end, 1 million original numbers were compressed into thousands of high-quality active leads for precise promotion.

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How to calculate the cost of TG filtering?

KK-DATA adopts the model of no subscription package and billing by item:

• Recharge method: USDT (TRC20), the minimum is about 50 USDT
• Deduction timing: Deducted from the balance after the tg filtering task is completed
• The unit price of each test type is different: tg activation, tg active, tg gender fees are different
• Detailed unit price: Please log in to Application Console to view real-time prices

Because billing is per case, you only pay for the numbers that are actually detected, and there is no monthly or annual fee pressure. The cost of small batch testing is extremely low, and when used in large batches, the budget can also be controlled through deduplication and combination screening.

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FAQ

Q: What does “active” in the tg filter results mean? How often is active?

Answer: “tg active” detection means that the target number has Telegram usage behavior (sending messages, logging in, group interaction, etc.) within a specified number of days (such as 7 days, 30 days). You can customize the activity window when submitting a task. For example, if you select “Active in the past 7 days”, only users who have acted in the past 7 days will be returned. The shorter the window, the more active the filtered users are, but the smaller the number.

Q: How many TG numbers can be batch filtered at a time?

Answer: KK-DATA supports up to about 1 million numbers in a single task. It is recommended that you submit a small number of samples (such as 1,000 items) for first-time use to verify field integrity before processing large batches of data to avoid wasting balance due to configuration issues.

Q: Will tg filtering leak my number database to the platform?

Answer: Regular tg filtering platforms (such as KK-DATA) provide a privacy protection mechanism. Your number will only be used for this detection task, and the platform will not use it for other purposes or disclose it to third parties. It is recommended to read the platform’s privacy policy before use.

Q: Is the age field accurate? Can you be precise about your age?

Answer: The age field is inferred by the machine learning model based on Telegram public information (such as avatar, nickname, behavior pattern), and is suitable for group-level targeting (such as 25–40 years old), not the exact age at the ID card level. In the overseas customer acquisition scenario, filtering by age groups is effective enough, and there is no need to pursue individual-level accuracy.

Q: If the results are exported after tg filtering, can they be directly used for private message promotion?

Answer: Yes. The exported fields include number, tgid, active status, gender, age, etc. You can directly import these numbers into the private messaging tool for one-to-one messaging or group invitations. However, please pay attention to abide by Telegram’s usage policy to avoid account restrictions caused by frequent sending.

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The core value of tg filtering is to use the lowest cost and the shortest time to filter out truly valuable Telegram users from a large number of numbers. Whether you are doing community operations, B2B customer acquisition or large package cleaning, mastering this process can significantly improve efficiency and conversion.

Try KK-DATA’s tg filtering function now: 👉 [Log in to the console to start filtering] (https://app.kkdata.cc/), or get one-on-one guidance through [Two-way contact customer service] (https://t.me/kkdata_robot). For more operation details, please refer to KK-DATA usage documentation.