US TG male data acquisition guide: Gender identification accuracy boundary and usage suggestions

In overseas marketing, accurately reaching target user groups is the key to improving conversion rates. For industries such as games, finance, and tool apps where men are the main audience, US tg male data—that is, male numbers and status information among US Telegram users—is a type of high-value clue. By identifying the gender of Telegram users through the number screening platform, you can quickly filter out numbers that meet gender expectations, and then carry out targeted promotion, private message contact or community recruitment. But can gender recognition really be 100% accurate? How to use this kind of data correctly? This article will combine the practice of KK-DATA to break down for you the acquisition methods, accuracy boundaries and best usage strategies of American Telegram male data.

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

US tg male data refers to active or registered numbers in the US time zone/number range and with male gender, inferred by detecting Telegram user public information. This type of data is not just a string of mobile phone numbers, but also usually includes additional information such as tgid (Telegram internal ID), active status, activation status, age field, etc. For overseas marketing, its value is reflected in:

• Reduce the cost of trial and error: Promote products directly to male users to avoid the waste of advertising or sending private messages to non-target groups.
• Improve conversion rate: In industries with a high proportion of male users (such as strategy games, cryptocurrency trading, fitness supplements, etc.), after using gender filtering, the reach efficiency can be increased several times.
• Supports reuse in multiple scenarios: It can be used for Telegram group invitations, private message marketing, WhatsApp targeted synchronization, etc. at the same time.

KK-DATA’s number screening function supports numbers from many countries around the world, among which American numbers are one of the most frequently used scenarios. Through the “Telegram gender detection” type, you can extract users marked with “male” from a large number of numbers, and further filter based on activity levels (such as 7 days/30 days of activity) to form a high-quality marketing list.

How is gender recognition achieved in KK-DATA? How high is the accuracy?

KK-DATA’s gender identification** is not an official real-name authentication**, but a statistical inference based on the public information of Telegram users. The algorithm combines the following fields:

• User Nicknames and Usernames: Some nicknames contain obvious gender suggestive words (such as “Jack”, “Mary”).
• Personal Profile (Bio): Titles and interest descriptions that may appear in the profile.
• Avatar picture: Assists judgment through the visual characteristics of the avatar (non-AI face recognition accuracy).
• Custom status: Some users will fill in gender-related status.

Since the data source is information actively disclosed by users, the accuracy depends on the completeness and authenticity of the user’s information. There is no 100% accurate gender detection - there will always be users who do not fill in any information, or fill in misleading content. KK-DATA clearly states in the product prompt: Gender identification results are statistical inference and are unofficial ID-level certification. It is recommended that users verify the actual accuracy through small-scale testing before deciding whether to use it on a large scale.

How to get American Telegram male data? Step-by-step guide

The following operations are based on the KK-DATA console (https://app.kkdata.cc/). No programming knowledge is required and can be completed in three steps.

Step 1: Generate or import a US number list

You have two ways to prepare the number to be tested:

1. Use the global number generation function: In the “Number Generation” module of the console, select the country “United States” to randomly generate a large number of numbers based on the number segment. Generating is completely free and does not consume your balance.
2. Upload your own number CSV: If you already have a list of US numbers (such as obtained from other data sources), directly import it into the system according to the format.

After generating or importing, the system will provide a preview of the number, and you can proceed to the next step after confirming it is correct.

Step 2: Submit the Telegram screening task and check the “Gender Detection” type

On the “Screening Task” page, select the “Telegram Screening” platform. Configure key parameters:

• Detection Type: “Telegram Gender” must be checked, otherwise the export results will not contain the gender field. It is also recommended to check “tg active” (eg active for 7 days) to improve data availability.
• Number Source: Select the US number list generated in the first step.
• Task Name: Customized for easy subsequent management.

The system will automatically calculate the estimated cost (See real-time price on the console for details), and submit the task after confirmation. The task execution time depends on the number of numbers and network conditions, and is usually completed within a few minutes to tens of minutes.

Step 3: Export CSV/TXT data containing gender field

You will receive a notification when the task is completed (it is recommended to bind the Telegram notification robot, https://t.me/kkdata_robot). Click “Export” on the task details page, select the format (CSV or TXT), be sure to check the fields including “gender”, “activity”, “tgid” and other fields. After exporting, you will get a table, in which the “Gender” column marked as “Male” is the US Telegram male data you need.

The Boundary of Gender Recognition Accuracy: 3 Key Points You May Overlook

Even if you follow the above steps to filter out “male” numbers, you must be aware of the following restrictions to avoid strategic mistakes.

1. Unable to detect when user does not fill in or hides gender information

Telegram users can set their profiles to be completely private, with no gender, bio, or even avatar displayed. In this case, KK-DATA cannot output the gender label and is marked as “unknown”. These numbers cannot be eliminated by gender filtering, but they may still be potential male users (or vice versa). If your target must strictly limit gender, it is recommended to use other fields (such as interest groups) to assist in judgment.

2. Gender results are statistical inferences and are not absolutely accurate.

There is a certain misjudgment rate in the algorithm’s inference based on public information. For example, a user named “Rose” might be male but use a female nickname. KK-DATA will not claim “99% accuracy” because this is untrue. As a user, you should evaluate the quality of the current batch through manual verification by sampling (such as randomly selecting 100 tgids marked as “male” and viewing their public information).

3. The age field only assists in interpreting people around 30 years old and cannot be used for ID card level verification.

The age field included in gender detection comes from the date of birth or public information filled in by the user. The platform will output a rough range (such as “25-34”), which can be used to assist in interpreting people who are about 30 years old, but this is not a precise age, and it cannot be used for fraud prevention or identity verification. Age can be used as a weighted dimension in marketing, but it should never be treated as authoritative data.

How to verify and optimize the American TG male data you obtained?

After obtaining the data, it is recommended to do the following optimization operations:

1. Small sample inspection: Randomly select 50-100 numbers marked as “male” and manually check their Telegram public information to confirm whether the gender label is consistent with intuition. Record the error rate and adjust subsequent dosage.
2. Combined with activity filtering: Prioritize numbers that are “active for 7 days” or “active for 30 days” when exporting. Active users are more likely to see private messages or open group invitations, increasing ROI.
3. Cross-task deduplication: If you filter U.S. numbers multiple times, use KK-DATA’s “data deduplication warehouse” function to automatically eliminate duplicate numbers and avoid repeated deductions.

Differences in gender identification between US TG male data and other platforms (WhatsApp, Line)

There are obvious differences in the gender identification data sources and field richness of different social platforms. The following comparison can help you decide when to prioritize US TG male data:

Comparison Dimensions	Telegram	WhatsApp	Line
Gender data source	Public information such as nickname, profile, avatar, etc.	Only inferred from number registration status and name (no clear gender field)	Gender is optional in user information, and some accounts are visible
Accuracy expected	Moderate to high (depending on the completeness of user information)	Low (no direct gender field, pure speculation)	Moderate (Asian users fill in a higher proportion, American users lower)
Attached fields	tgid, activity, age, avatar link	wsid, activity	uid, activity
Suitable scenarios	Targeted promotion for men around the world	Mainly based on status detection, gender identification is not recommended	Targeted promotion for men in the Southeast Asian market

For male user screening in the US market, Telegram is the most available choice for gender data among current mainstream platforms. WhatsApp offers little reliable gender recognition, and Line has lower penetration in the United States. Therefore, if you target male users in the United States, give priority to American TG male data.

Cost considerations: Proper budget planning using US TG male data

KK-DATA adopts the model of billing by item and zero subscription package. After recharging the USDT (TRC20) balance, the corresponding fee will be deducted from the balance after each number screening task is completed. Different platforms and different detection types have different unit prices. For specific prices, please log in to the console to view real-time quotes. The following are budget suggestions:

• Low-cost test: First use 1000-5000 numbers to do a small task to test the gender recognition accuracy and activity distribution. The fee is very low (eg only a few tens of USDT).
• Batch Volume: After confirming the data quality, you can submit tasks of 50,000-100,000 numbers. Pay attention to controlling the total cost of “gender detection” + “activity detection” (the comprehensive unit price is higher than single status detection).
• Avoid waste: Use a deduplication warehouse for historically detected numbers to prevent repeated deductions.
• Notifications and Balance Monitoring: After binding the Telegram robot, you can receive task completion notifications and export data in a timely manner to avoid accidental consumption of balances due to accumulation of tasks.

FAQ

**Q: What is the gender identification accuracy of US TG male data? ** Answer: KK-DATA makes inferences based on user public information. The accuracy is affected by the completeness of user information and is not 100%. It is recommended to evaluate the actual effect through small batch testing before using it on a large scale.

**Q: Can you ensure that each number has a gender label? ** Answer: No. Some users did not fill in their gender or had strict privacy settings, resulting in the inability to output the gender field. These numbers will be marked as “unknown” and will not affect other test results.

**Q: Can the age field be accurate to a specific age? ** Answer: The age field comes from the information filled in by the user. It can assist in interpreting the age of people around 30 years old, but it is not an accurate age and is not recommended for ID card level verification.

**Q: How to get a male Telegram number in the United States? ** Answer: You can use KK-DATA’s global number generation function to generate random US numbers by country, or you can upload your own number list, then submit the Telegram number screening task, select the gender detection type, and export male data.

**Q: What fields are included in the data export after detection? ** Answer: Supports CSV/TXT format export, including mobile phone number, Telegram ID, activation status, activity indicators, gender (male/female/unknown), age (if any) and other fields. The specific fields are subject to the console export interface.

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Now you have mastered the methods and usage boundaries of US TG male data. If you are preparing a marketing campaign for American male users, you might as well start with a small task and verify the effect before scaling up. Go to the console to experience the full screening process, or get one-on-one guidance through a two-way connection to customer service.

👉Log in to the console to start screening numbers Two-way contact customer service https://t.me/kkdata_robot For more usage tips, please refer to Official Documentation