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tg filtering topic navigation: from activation detection to active filtering and export, one article covers the entire process

For teams that rely on Telegram for overseas marketing, community operations, or private message promotion, tg filtering is basic work that cannot be avoided. You have a batch of numbers on hand, and you need to know which ones are registered on Telegram, which ones have been online recently, and which ones are real active users—this process is tg filtering. But if there is only one isolated concept, it will be difficult for you to efficiently complete a set of screening pipelines.

This article is the thematic navigation hub on Telegram filter and TG filter in the KK-DATA blog. We will break down every key link of the entire pipeline from activation detection, active screening, gender recognition, data deduplication to result export, and index each topic article for your in-depth study. Whether you are new to Telegram number filtering or an experienced operator who needs to improve efficiency, this article can help you quickly locate what you need.

What is tg filtering? Why do you need to systematically understand every link?

The so-called tg filter is the process of batch verification and classification of a batch of Telegram numbers to be detected. Its core is not to “delete invalid numbers”, but to label numbers in multiple dimensions based on your business goals, such as:

• Whether Telegram is registered (activation detection)
• Have you been online recently (active filtering)
• User’s gender, age and other public data (gender identification)
• Whether it has been detected in other tasks (data deduplication)

These links are not isolated, but have strong dependencies:

号段生成或导入 → 开通检测（基础过滤） → 活跃筛选（质量提升） → 性别/年龄定向 → 数据去重 → 导出可用名单

If you skip a certain link and proceed directly to follow-up operations, such as sending batches of private messages without active screening, it may result in a large number of invalid numbers, a waste of time and cost. Therefore, the system understands the principles and best practices of each link and can help you build a stable and repeatable customer acquisition pipeline.

Below, we will break down each step in order and provide you with an index of corresponding feature articles.

Step One: Telegram Number Activation Detection - Your Screening Foundation

The starting point of any tg filter process is open detection. The so-called “activation” means verifying whether the target number has registered a Telegram account. Only after this step can you ensure that subsequent operations such as active filtering and gender identification are performed on real Telegram users.

What is activation detection? Why is it more important than simply “number segment generation”?

Typical application scenarios for activation detection include:

• Basic cleaning before batch private messages: Make sure that the messages you send reach real people’s registered Telegram accounts, not unregistered or abandoned numbers.
• Industry targeted screening: In the activation test results, you can see which countries and number segments have higher registration rates, providing data support for subsequent number generation strategies.
• Anti-repetitive waste: Many overseas teams will import the same batch of numbers repeatedly. The activation detection can ensure that you only mark the activated numbers when importing them for the first time to avoid subsequent misjudgments as unregistered.

Common misunderstandings about activation detection: the difference between being logged out, being kicked out of the group, and not being activated.

In actual operation, novices are easily confused by several states:

Status	Description	Effect on filtering
Activated (registered)	This number has a Telegram account, even if it has not logged in for a long time	It can pass the activation test, but it may not be an active user
Logged out	The user actively or passively deleted the account	It cannot pass the activation test and is regarded as an invalid number
Not activated	The number has not been registered with Telegram, or has just been registered but has not been verified as a device	Some detection tools may mark it as “not activated”
Kicked out of the group	It has nothing to do with whether the number is activated, it is the group member status	Activation detection does not involve group data

Related topic articles: Detailed explanation of tg activation detection: How to quickly filter numbers registered for Telegram

How to filter Telegram active users? From “online” to “coming online soon”

For most marketing scenarios, the core requirement of TG screening is to find real and active users. Although an account has been opened, if you have not logged in in the past year, there is a high probability that you will not get a reply to your private messages in the past. That’s why Activity Filtering is an unskippable step in telegram number filtering.

How to choose the active window? Different time ranges correspond to different scenarios

KK-DATA’s activity detection supports setting the active window, which allows you to select users who have been online within the “last 7 days/30 days/90 days”. The choice of this window directly affects the quality of the filtering results:

• Active within 7 days: Most suitable for instant marketing, flash events, and limited-time notifications. These users use it more frequently and have higher private message opening rates.
• Active within 30 days: Suitable for regular community operations, content push, and long-term follow-up. Taking into account user activity and coverage.
• Active within 90 days: Suitable for brand exposure and awakening of silent users. If you only want “ever registered”, this window is enough.
• Unlimited: Testing is enabled immediately (all registered accounts). It is not recommended to be used directly for marketing unless you have extremely low timeliness requirements.

What are the fields returned by activity detection? Does it support exporting “last online time”?

The result of the activity detection will not only tell you “whether the number is active”, but also return its last online timestamp (accurate to the minute level). You can judge whether it belongs to your target window based on this timestamp.

In addition, the fields returned typically include:

• Last online time -Activity level (eg: 7 days/30 days/90 days active)
• Online status indicator

These fields are viewable in the exported CSV/TXT file and support filtering by time range.

Related special articles: [Telegram active screening practice: how to accurately extract highly active users in batches] (https://kkdata.cc/blog/tg-active-users-filter)

Telegram gender and age data: advanced dimensions for tg filtering

When TG screening reaches a certain stage, you may need more refined targeting capabilities, such as only wanting to send specific marketing content to users whose gender is male** or who are about 30 years old. This is what gender and age testing is all about.

Data source and accuracy description

The source of Telegram’s gender and age fields is based on the user’s public information (such as avatar, profile, self-filled age) and the algorithm’s inference of behavioral patterns. Please note:

Common application scenarios

• Male Targeting: Suitable for promoting games, tool apps, and financial products.
• Female Targeting: Suitable for promotion of beauty, maternal and infant, and lifestyle services.
• Age segmentation: For example, “20-30 years old” can be used to filter out young user groups and improve the accuracy of advertising.

Related feature articles: Telegram gender identification and age field analysis

Data deduplication and export: the key to doubling tg filtering efficiency

Many teams will ignore one detail when doing tg filtering: duplicate detection. If you use the same list of numbers in multiple tasks, or if the numbers overlap between batches of tasks, balance will be wasted. The data deduplication warehouse is designed to solve this problem.

How the data deduplication warehouse works

KK-DATA provides cross-task number deduplication function. You simply upload the number to the system, and the system records whether the number has been detected in a previous mission. If it has been tested and the results are available, the system will prompt “already exists” to avoid repeated charges on the same number.

Operation example:

1. Create a “Remove Duplicate Warehouse” task in the console.
2. Import a CSV file containing duplicate numbers.
3. The system automatically compares historical detection records and generates a list of unique numbers after deduplication.
4. Submit the deduplicated number to subsequent “activation” or “active” detection.

Export format and field selection

After the detection is completed, you can export the filtering results in the following formats:

• CSV: Contains all fields (mobile phone number, subscription status, activity level, gender, age, tgid, etc.), suitable for opening with Excel or Google Sheets.
• TXT: Contains only valid numbers filtered out from the number list, suitable for direct import into the private messaging tool.

When exporting, you can select the fields you need (such as only “tgid” or “last online time”) to avoid exporting too much useless data.

Related feature articles: Data Deduplication Warehouse Usage Guide | TG Filtering Results Export Tutorial

Summary of frequently asked questions about tg filtering (FAQ-style chapters for quick verification)

The following are the most common problems users encounter when using TG Screener. We have compiled short answers and directed you to special articles for in-depth reading.

How many numbers can be filtered at most in one task?

KK-DATA’s single number screening task supports up to about 1 million numbers. If you need to filter more than 1 million pieces of data, it is recommended to submit it in batches. At the same time, the data deduplication warehouse can help you avoid repeated detection during batch processing.

Do test results have an expiration date? How to manage historical tasks?

The detection results are retained in the system for a period of time (see console settings for details). You can view and re-download the results in the “Task History” module of the console, or mark historical tasks as “Archived”. It is recommended to save the results locally after exporting them.

Will the task be executed if the balance is insufficient? What are the refund rules?

will not be executed. When the balance is insufficient, new tasks cannot be submitted (the system will prompt that the balance is insufficient). For ongoing tasks, if the balance is exhausted, the task will be suspended until you recharge to continue. Completed test results will not be lost due to insufficient balance and you can download them at any time.

Refund Rules: Completed task fees are not refundable. For excessive deductions or other abnormalities caused by system errors, please handle them through the official customer service channel.

How to verify whether the test results are true?

The KK-DATA platform provides official test reports, and you can sample and verify them yourself through the exported CSV. For example, for a number that has been marked as “open”, try adding or sending a message using your own Telegram client to confirm that the results are as expected. At the same time, official documentation and customer service teams will also provide verification suggestions.

**Q: Do I need to prepare the number source myself for tg filtering? ** Answer: Yes, tg filter requires you to provide a list of numbers to be detected. You can use KK-DATA’s “Global Number Generation” module to generate a random number for the target country/region for free, or you can import it through a custom number segment CSV and then filter the numbers.

**Q: Can tg filter detect which Telegram group a number belongs to? ** Answer: No. tg filtering only detects the activation, activity, gender and other status of the number itself, and does not involve the group or chat history to which the number belongs. For group-related data, please refer to other tools.

**Q: Can all fields be exported from the filter results? ** Answer: Supported. After the task is completed, you can export the CSV or TXT format from the console. The fields include number, activation status, active status, gender, age, tgid, etc. (specific fields are subject to the actual detection type).

**Q: What is the unit price of tg filter? ** Answer: Different platforms and detection types have different unit prices. For example, the prices for Telegram activation detection and active detection are different. Please log in to the console to view real-time prices, or visit the Billing Page for an approximate range.

**Q: If I have questions about the results, how do I contact customer service? ** Answer: Please submit questions through the official two-way contact robot https://t.me/kkdata_robot, or communicate through the customer service account @kkdata_cc. Be careful not to trust fake customer service.

Summary: From tg filtering to multi-platform filter numbers, what can you do next?

tg filtering is a main line of overseas customer acquisition data screening, but the complete customer acquisition chain is much more than that. After you have mastered the entire process of activation → active → gender → deduplication → export, you can further try cross-platform screening, such as combining WhatsApp, Line, Zalo and other platforms to build a multi-platform reach matrix.

• If you are interested in single-platform in-depth screening, please refer to the above-mentioned special articles to learn.
• If you want to improve the efficiency of screening numbers, you can study the combined solution of “global number generation + multi-platform screening”.
• If you need to know the latest functions and industry trends of TG Screener in real time, you can follow our official channel https://t.me/kkdata_channel.

Now, it’s time to get your hands dirty. 👇

👉 Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot Official document: https://docs.kkdata.cc/