tg filtering Ultimate Guide: How to efficiently filter Telegram active numbers based on search intent (2025 practical version)

#tgfiltering The ultimate guide: How to efficiently filter Telegram active numbers based on search intent (2025 practical version)

When you search for “tg filter” on Google, there may be completely different needs hidden behind it: some people just want to verify whether a batch of numbers are registered with Telegram, some want to filter out “real users” who have been active recently, and some want to accurately reach specific gender and age groups - such as “men around 30 years old.” This article starts from the search intention, dismantles the real scenarios behind these needs, and provides practical tg filtering operation steps to help B2B overseas teams, e-commerce operators, and social traders efficiently complete Telegram number screening.

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What do users really want when they search for “tg filter” on Google?

Through observation of a large number of search behaviors, there are mainly four typical intentions behind “tg filtering”. Understanding which category you belong to can greatly improve screening efficiency.

Intent 1: “Whether the number can be used” - Telegram activation test

This is the most basic tg filtering requirement. The so-called “tg activation” is to detect whether a mobile phone number has been registered on Telegram. If you have collected a bunch of international numbers from trade shows, B2B platforms or LinkedIn, the first step is to eliminate invalid numbers that are not registered with Telegram at all. Only performing activation detection can quickly compress the number pool into the available range.

Intent 2: “Is anyone using the number?” - Telegram activity filtering

Open does not mean active. Many users have not logged in for a long time after registering, or their accounts have been abandoned. Sending messages to such numbers will not only waste your credit, but may also trigger Telegram’s current limiting mechanism. The “activity detection” in tg filtering can specify a time window (such as the last 7 days, 30 days), and only filter out users with recent login/message behavior. This directly determines the real effect of marketing reach.

Intent 3: “Is the number the target group?” - Telegram gender/age filtering

When it comes to acquiring customers overseas, especially in B2B scenarios, gender and age often determine conversion. The gender detection filtered by tg will return the gender and age fields predicted by the model. Although it is unofficial data, it has a strong reference value for targeted advertising (for example, for male business people around 30 years old). Note: The age field is used to interpret people “about 30 years old”, not accurate to the ID card level.

Intent 4: Export structured fields - tgid, wsid, etc.

Some operators need to import the filtering results into CRM or automation tools, which requires exporting fields such as tgid (Telegram internal user ID), wsid (if WhatsApp is also filtered). After tg filtering is completed, you can choose to export it in CSV or TXT format, including various test results to facilitate subsequent secondary processing.

What is “tg filtering”? (Quick definition and technical boundaries)

tg filtering refers to the process of using technical means to quickly determine the status of a batch of mobile phone numbers on the Telegram platform - whether they have been registered (activated), whether they have been active recently (activity), the gender and age predicted by the model (gender detection), and export the results as structured data.

Clear technical boundaries are needed:

• The detection is based on public interfaces and model inference, and cannot achieve 100% accuracy. In particular, the age field is probabilistic inference and is not officially certified.
• Unable to read user chat content, private messages or background data.
• Gender detection results are for reference only and are not guaranteed to match the user’s true identity.

How to use tg filter to find the target group of “men around 30 years old”? (Practical process)

The following takes the KK-DATA platform as an example to demonstrate the complete operation from the number list to exporting “male about 30 years old”. All steps are available in the console (https://app.kkdata.cc/）完成。

Step one: Obtain the number to be filtered - global number generation and custom import

If you don’t have a ready-made number on hand, you can use KK-DATA’s “Global Number Generation” module. Supports random generation of numbers in 240+ countries/regions, and can also generate numbers in batches based on number segments (such as the United States +1, Indonesia +62, etc.). The generation is completely free, and charges will be deducted only when the number is screened. If you already have a list of numbers (such as a CSV file collected from an exhibition), just import it directly. Supports custom number segment CSV import, which is convenient and flexible.

Step 2: Submit Telegram detection task - activation + activity + gender

Select the country (such as the United States, Indonesia, Malaysia, etc.) in the “New Task” in the console, select “Telegram” as the platform, and check the following detection types:

• Activation Test: Make sure the number is registered.
• Activity Detection: Select an active window (such as “Last 30 Days”) to filter out users with recent behavior.
• Gender Detection: When turned on, task results will include gender and age fields.

Set the task name (such as “B2B Test-30 Years Old Man”) and click Submit. After the task is completed, you can see the age field of each number in the results, which can be used to filter out people around 30 years old - the age field is usually displayed as a range value (such as “25-35”), which can be interpreted as “a group of about 30 years old”.

Step 3: Export data - CSV/TXT format, including tgid

After the task is completed, enter the task details page. Set conditions in the filter: 年龄 Select “25-35” or greater, 活跃状态 select “Active (last 30 days)”, 性别 select “Male”. Then click “Export” and choose CSV or TXT format. The exported fields include mobile phone number, tgid, gender, age, activity status, detection time, etc., which can be directly used in subsequent private messaging tools or CRM systems.

Three key settings that are easily overlooked when TG screening

Novices are prone to the following misoperations when filtering tg, which directly affects the effect and cost:

1. Active window setting is too short or too long

   • If it is a private message promotion (such as first contact), it is recommended to select “last 7 days” to avoid disturbing long-term inactive users.
   • If it is a community invitation or one-way broadcast, select “last 30 days” to expand the reach.
   • The shorter the window, the higher the cost but the more accurate the crowd. The balance point needs to be tested according to the scenario.

2. Data deduplication warehouse is not enabled Submitting the same number repeatedly will result in wasted balance. KK-DATA provides a “data deduplication warehouse” function, which automatically compares historical records before submitting a task and skips already detected numbers. Highly recommended to enable.

3. Two-way customer service contact is not used Some users are accustomed to sending emails and other responses when encountering task lags, abnormal balances, or questions about result interpretation. But the best customer service channel for the Telegram screening platform is the official Telegram robot (https://t.me/kkdata_robot），支持双向沟通，响应速度远超传统工单。

Common usage scenarios of Telegram number filtering (B2B overseas and community operations)

Scenario 1: Southeast Asia e-commerce dual platform customer acquisition Suppose you sell beauty products in Vietnam, and your target audience is women aged 25-40. You also need to use Telegram and WhatsApp for message push. Operation process: First use tg filter to filter out Vietnamese numbers that have Telegram activated and are female, then submit these numbers to WhatsApp activation test, and finally get a list of users that are valid on both platforms. Cross-validation can significantly reduce the failure rate.

Scenario 2: Independent station EDM/IM multi-channel reach If you operate an independent website targeting European and American young people, in addition to email, you also want to use iMessage or RCS to reach it. You can first filter out Telegram active users through tg filtering, and then import these numbers into iMessage detection (only for iOS devices and iMessage is turned on) to achieve double coverage of “Telegram + Apple official messages”.

How to balance cost and effect when using tg filtering?

KK-DATA adopts per-item billing, no subscription package, and you pay for what you use. Core strategies for cost control:

• Step-by-step filtering: Prioritize the detection (cheapest), filter out the registered numbers, and then conduct targeted activity detection and gender detection. If all types are purchased directly, the cost will be much higher.
• Small-scale test: First test different active windows and gender parameters with 500-1000 numbers, and then find the optimal combination before executing it on a large scale.
• Enable data deduplication: avoid repeated deductions.

For the specific price of each test, please refer to the real-time display on the console. Before submitting the task, the system will display the estimated cost and confirm it is correct before executing it.

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FAQ

**Q: Can tg filtering 100% determine whether a number is a real user? ** Answer: No. tg filtering can detect whether the number has been registered with Telegram and its recent active status, but it cannot confirm the authenticity of the registrant’s identity. The test results are recommended as a screening reference, not the only basis for judgment.

**Q: How many numbers can be filtered at one time? ** Answer: KK-DATA supports up to about 1 million numbers in a single task. It is recommended to submit a small number of numbers (for example, within 5,000) to test the detection effect, and then adjust the parameters based on the results before executing large-scale tasks.

**Q: Is the age and gender data filtered by tg accurate? ** Answer: The age field in the gender detection results can be used to interpret/screen people around 30 years old, but the model is based on user behavior inference and unofficial certification data, and the accuracy cannot reach the ID card level.

**Q: How to export the results after filtering is completed? ** Answer: After the task is completed, you can choose to export it in CSV or TXT format on the task details page of the console. The export fields include tgid, age, gender, active status, etc. The details are subject to the export page display.

**Q: How to use data deduplication warehouse to avoid repeated deductions? ** Answer: In the “Data Deduplication” module of the console, you can upload a list of previously detected numbers. When subsequent new tasks are submitted, the system will automatically skip these numbers and only deduct the detection fees for the new numbers from the balance. It is recommended to enable this function before each large-scale screening.

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If you have a batch of Telegram numbers that need to be filtered, or want to accurately reach specific groups (active users, men/women, about 30 years old, etc.), you are welcome to try KK-DATA.

👉 Log in to the console to start filtering Complete your first tg filtering task Two-way contact customer service: https://t.me/kkdata_robot (If you encounter any problems, you can communicate directly) Product official website: https://kkdata.cc/ Complete usage documentation: https://docs.kkdata.cc/