How to accurately screen American TG male data? Complete tutorial on overlaying active windows and list layering

If you are doing Telegram private message promotion in the US market, you will definitely encounter a practical problem: you have a bunch of US numbers, but you don’t know which ones are real Telegram users, let alone which ones are male users. American TG male data - that is, numbers that have opened Telegram and the gender field is marked as “male” - are high-value target groups in overseas marketing. But gender screening alone is not enough. Zombie accounts and offline accounts will greatly reduce your reach efficiency. This tutorial will explain in detail how to obtain truly usable high-quality American Telegram male numbers through the combined screening of KK-DATA’s gender detection and activity detection (active window), and give the list stratification strategy and the best order of use.

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What is US TG male data? Why is it needed for overseas marketing?

US TG Male Data refers to mobile phone numbers that meet the following conditions:

• Registered with Telegram (i.e. “activated”)
• Determined to be male by the platform’s gender recognition module (based on public information such as nickname, avatar, personal profile, etc.)
• The country/region of origin is the United States (can be determined based on the country code prefix or the location of the number)

This type of data has obvious value in overseas customer acquisition: male users have a higher response rate for categories such as finance, technology, tools, games, and cross-border e-commerce; and the U.S. market has strong spending power, and accurately reaching male users can effectively reduce promotion costs. But gender tags alone are not enough - if a number has not been logged in for two years, no matter how many messages you send, it will not be seen. Therefore, Activity Detection must be superimposed to ensure that what you find is “active” American TG male data.

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Activity detection and activity window: the key to screening high-quality data

KK-DATA provides two core detection capabilities: Gender Detection and Activity Detection. Activity detection will determine whether the target number has logged into Telegram in the recent period. This time period is the active window.

What is an active window?

The active window is a configurable time range, such as “7 days”, “14 days”, “30 days”, etc. When you submit a liveness detection task, you can select a window. The system will return whether the number has logged in within the specified window.

Active window	Meaning	Applicable scenarios
24 hours	Logged in within the past day	Very short-term activities, emergency notifications
7 days	Logged in within the past 7 days	Regular private message promotion, event invitations
30 days	Logged in within the past 30 days	Brand cultivation, long-term reach
90 days	Logged in within the past 90 days	Long-term retained users

The shorter the window, the smaller the amount of remaining data, but the activity is extremely high; the longer the window, the larger the amount of data, but some numbers may have become silent users. You need to choose based on the promotion time. For example, if you are doing a limited-time discount, it is recommended to be active for 7 days; if you are doing a combination of brand emails and private messages, you can use it for 30 days.

Complementarity of activity and gender data

If you simply screen for gender without considering activity level, the list you get may have a large number of numbers that are “activated but offline for a long time.” Messages sent from these numbers may not necessarily result in errors, but users will not see them at all. On the contrary, if you only screen activity but not gender, you will not be able to target male users. Gender + activity double screening can get the most accurate US TG male data.

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How to filter American TG male data on KK-DATA and superimpose activity detection?

The following operations can be completed on the KK-DATA console without programming. Please log in to the Application Console in advance to ensure that the account balance is sufficient (see Billing Instructions for details).

Step 1: Generate or import US TG number

You have two ways to get the list of numbers to be tested:

1. Global Number Generation: Select “Global Number Generation” on the console, and select “United States” as the country. You can generate a batch of numbers by number segment or randomly. Generation is free, billing by item only occurs during the screening stage.
2. Custom Import: If you already have your own U.S. number library (for example, from a placement form or third-party leads), you can organize it into a CSV file and upload it. Note that the number format needs to be in international format (such as +1XXXXXXXXXX).

It is recommended to generate a batch of test numbers first, and then import the real list after becoming familiar with the process.

Step 2: Submit gender detection task

• Enter the “Telegram Screen ID” module
• Upload or paste your US number list (up to about 1 million per time)
• Check the detection type “Gender” (including fields such as gender, age, avatar, etc.)
• If you need to check the activation status and activity at the same time, you can check both in this step (but it is recommended to follow the strategy in the next section to batch)
• Submit tasks and wait for completion

After the task is completed, export the results. You will see a CSV with the 开通状态, 性别, 年龄, tgid fields for each number. Filter out the numbers 性别 == 男性 to get the preliminary list of “US TG male data”.

Step 3: Add activity detection based on gender tasks

After obtaining the gender list, import the list, submit the “Telegram Screening” task again, this time only check “Activity Detection”, and select the active window you want (such as 7 days). The system will only detect the active status of these numbers and will not repeatedly detect activation and gender.

You can also directly combine gender + activity detection in the first step to get the results in one go. But please note: **If you do the gender first and then the activity, you can keep the gender result and avoid submitting the activity test again. **The actual order of use depends on your list size and budget strategy (see next section for details).

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Usage order and list stratification: Gender first or active first?

Faced with tens of thousands or even hundreds of thousands of American numbers, should you do gender testing or activity testing first? This is directly related to detection cost and work efficiency.

Strategy 1: Gender first, then active (high precision, high budget)

• Operation: Submit the gender detection task first → filter males from the results → submit activity detection only to the male list
• Advantages: The final list is extremely accurate - all male and active
• Disadvantages: The cost of gender testing is relatively high, and a large part of the numbers may be female or the gender is unknown, so the money is wasted
• Suitable: Sufficient budget, small list size (within a few thousand items), pursuit of ultimate conversion

Strategy 2: Active first, then gender (recommended, cost controllable)

• Operation: Submit the activity detection task first (select a wider window, such as 30 days) → filter out the “active” numbers → then submit the gender detection for the active list
• Advantages: The unit price of activity detection is usually lower than gender detection (see console real-time price for details). First use low-cost activity detection to filter out a large number of zombie accounts. The number of remaining active accounts may only be 1/3~1/2 of the original number. Then perform gender detection on them, and the total cost will be significantly reduced.
• Disadvantages: Male users within the active window are included in the final list, but those “inactive (not logged in within 30 days)” male users cannot be known - however, such users have low value, so there is no harm in discarding them.
• Suitable: large-scale cleaning (tens of thousands of items or more), budget control, and certain requirements for conversion efficiency

List hierarchical management

Regardless of which strategy you use, you’ll get multiple batches of results. It is recommended to use KK-DATA’s data deduplication warehouse:

• Import the export results of each task into the deduplication warehouse
• Add tags such as US_Male_7dActive, US_Male_30dActive
• Next time a new number comes, compare it with the warehouse first to avoid repeated detection of the same number.

This way you can save your balance and build your own hierarchical list system.

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Common mistakes and precautions

1. Ignore active window configurability: Using the default value (perhaps 7 days) may not suit your promotion cadence. It takes 7 days for event notification and 30 days for long-term cultivation. Please take the initiative to modify it.
2. Number format error: KK-DATA requires international format (starting with +1) without spaces or brackets. If it is CSV import, please note that the column names must be strictly consistent with the document (see Using Documentation for details).
3. Submit large tasks directly without checking the balance: The estimated cost will be displayed before the task is submitted. If the balance is insufficient, it cannot be submitted. It is recommended to recharge USDT in advance to avoid getting stuck.
4. Do not use the deduplication warehouse: Repeatedly detecting the same number will waste money. Be sure to exclude the detected records before importing a new list each time.
5. Treat the gender detection results as the absolute truth: Telegram does not disclose the official gender field. KK-DATA’s gender analysis is based on public characteristics, and the accuracy is high but not 100%. It is recommended to combine the age field (such as about 30 years old) to assist in judgment, or perform manual verification in small batches.

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FAQ

**Q: What is the gender accuracy of US TG male data? ** Answer: KK-DATA gender detection is based on the analysis of Telegram users’ public information (such as nicknames, avatars, personal information, etc.) and is not an official gender field. The accuracy is high but cannot be 100% accurate. It is recommended to combine other fields (such as age) to assist in judgment.

**Q: How long is the appropriate time to choose the active window? ** Answer: It depends on the promotion time. It is recommended that short-term private messages (such as event notifications) be active for 7 days; for brand cultivation or long-term contact, this can be relaxed to 30 days. It is recommended to test different windows in small batches first, and then adjust according to the response rate.

**Q: Which one saves more money: sex first and then activeness, or first activeness and then sex? ** Answer: It is usually more economical to be active first and then gender - first use low-cost activity detection to screen out invalid/offline numbers, and then perform gender testing on the remaining numbers, which reduces the number of gender tests. But the final choice needs to be a combination of budget and list size.

**Q: How many US TG numbers can KK-DATA detect at one time? ** Answer: The maximum number of items in a single task is about 1 million; if the list is larger, it is recommended to submit it in batches and use the data deduplication warehouse to merge the results to avoid repeated detection.

**Q: In addition to gender and activity, can other fields be detected? ** Answer: Yes. KK-DATA also supports tgid export, age field (can interpret people around 30 years old), avatar recognition, etc. If you need more granularity, you can customize the detection type in the console.

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Through the above steps, you have learned how to obtain high-quality American TG male data from zero to one, and optimize customer acquisition efficiency through activity windows and list stratification. You can start screening in just a few simple steps and flexibly add the test types you need. Log in to the console now and try combining gender and activity detection!

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