tg 30-year-old data checklist: A complete how-to guide for targeting people in their 30s before an event

#tg 30-Year-Old Data Checklist: A complete how-to guide for targeting people in their 30s before an event

Before doing Telegram community promotion or private messaging to acquire customers, how to quickly filter out those target users who may be interested in the “tg 30-year-old data”? Many operators get a bunch of numbers and send them directly to the group. The result is that the numbers are either invalid or the age groups of the users do not match at all. The key step here is to use the age field in gender detection before the event to find people around 30 years old - this is the tg 30-year-old data checklist that we will dismantle today.

This checklist, from number preparation, detection settings, task execution to result export, helps you step by step to avoid repeated deductions and improve orientation accuracy. The following operations take the KK-DATA platform as an example (if you need relevant tools, you can go to [Application Console] (https://app.kkdata.cc/) to experience it), but you can also migrate the methodology to other compliance screening services.

What is tg 30-year-old data? It can tell you the real situation

Many people ask: “Is the tg age data accurate?” Let’s first explain the origin of this field.

Source and accuracy of tg 30-year-old data

The Telegram platform itself does not directly disclose users’ birth dates or precise ages. The so-called “tg 30-year-old data” actually comes from the Gender Detection process of screening tools such as KK-DATA, which analyzes the user’s public information (such as avatar, user name, profile text, etc.) through algorithms to estimate the age range to which the user belongs. Common output is a range value like “25-34 years old” instead of “30 years old”.

Accuracy: It is an interval estimate in a statistical sense, not ID card level accurate. Suitable as a reference for crowd orientation, but not suitable for scenarios that require precise age verification.
Field meaning: In the export results, the age field usually displays the ranges such as “25-34” and “35-44”. You can select “people around 30 years old” through the filter conditions (for example, select the 25-34 range).
Don’t get me wrong: Don’t trust any screening service that claims to provide “accurate date of birth.” All compliance tools can only be speculative based on publicly available information.

Which scenarios are suitable for: Pre-event crowd targeting example

Scenario	Why the tg age field is needed
Promote online courses to working people around 30 years old	The age range can help you exclude obviously younger or older users
Promote financial management/insurance products to middle-aged groups	You can choose the 35-44 or 45-54 range
Promote games/social apps to young users	You can choose the 18-24 range
Local life promotion for ordinary consumers	The 25-34 range often covers the most active users

Actual Case: A cross-border independent website team is preparing to promote fitness products to male users in their 30s in Southeast Asia. They first generated mobile phone numbers in countries such as Thailand and the Philippines through the global number generation module, then submitted the Telegram screening task and checked “Gender: Male + Age: 25-34 years old”. Finally, about 12,000 qualifying TGIDs were exported, and the private message response rate increased by 60% compared to untargeted groups.

What do I need to prepare before the event? Material and Account Checklist

Before submitting the screening task, be sure to check the following items to avoid getting stuck midway:

Number List: Determine the original number (mobile phone number or Telegram ID) you want to filter. The source can be your own user registration data, the output of a number generator, or a custom number segment imported from CSV.
Telegram account: The number screening task requires you to have an available Telegram account to receive task notifications (not required, but highly recommended). It is recommended to use a trumpet dedicated to operations.
KK-DATA Account Balance: There is a fee for performing screening. The recharge method is USDT (TRC20), with a minimum of about 50 USDT. Before submitting the task, the console will estimate the cost to ensure that the balance is sufficient.
Duplication Warehouse: If you have filtered some numbers before, it is strongly recommended to query in the “Data Deduplication Warehouse” first to avoid wasting balances through repeated detection.
Network environment: Although KK-DATA runs in the cloud, your own device needs to be able to access the console normally (https://app.kkdata.cc/）。建议使用稳定的梯子（如果所在地区网络限制）。
Multi-format export preparation: Make it clear whether you need CSV or TXT export. CSV facilitates subsequent analysis using Excel or database.

hint

If you are not sure whether the number format you have is compliant, you can first check the number format description in the official document KK-DATA Usage Document.

Step-by-step operation of using KK-DATA to filter tg 30-year-old data

The following are the complete practical steps. We assume that you have already registered and logged into the console and have sufficient balance.

Step 1: Enter the console and create a Telegram filtering task

Open the Application Console and select “Filter Tasks” from the left menu.
Click “Create Task” and select “Telegram” for the platform.
Select a combination of detection types: You need to check at least “Enable detection” (Telegram registration detection) and “Gender detection”. Because the age field is included in the gender detection result.

Step 2: Select the detection type - activated, active, gender (including age field)

In the “Detection Type” area:

Open detection: required. Confirm whether the number is registered with Telegram.
Activity Detection: Optional. You can specify active windows such as “Last 7 Days”, “Last 30 Days”, etc. If your activity is extremely time-sensitive (such as a limited-time sale), it is recommended to select the activity in the near future.
Gender detection (including age field): required (in order to obtain tg 30-year-old data). Note: The unit price of gender testing is higher than the simple activation test. The specific price can be seen in the real-time display on the console.
Other fields: tgid exports are usually included by default for subsequent private messages.

Key Action: In the age filter section, you can manually enter a range, such as “25-34.” The age tags on different platforms may be slightly different, and the actual interface of the console shall prevail.

Step 3: Submit the task and wait for notification to confirm age data

Confirm that the number list has been uploaded (up to about 1 million entries/single task).
Click “Submit Task” and the system will display the estimated cost. Submit after confirmation.
The task execution time depends on the combination of number number and detection type, ranging from a few minutes to tens of minutes. After the execution is completed, the system will remind you through the Telegram robot (if you have bound notifications) or console message.

Checklist after filtering: verification, deduplication and export

After the task is completed, please complete the following checks before exporting:

View statistical overview: The console will display “number of activations”, “number of actives”, “number of gender detection”, etc. Focus on the “successful gender detection” numbers - only these numbers will have an age field.
Preview sample data: Download the first 100 CSV preview items before exporting, and confirm that the age field exists and the value is reasonable (such as “25-34”).
Duplication removal: If you have screened a batch of numbers before, you can use the “Data Deduplication Warehouse” to compare the current results with historical tasks to eliminate duplicate mobile phone numbers. This avoids wasting balances on repeated tests.
Select export format:
- CSV: suitable for subsequent processing with Excel or programming, including all fields (tgid, age, gender, active status, etc.).
- TXT: Contains only phone number or tgid, suitable for quick import into mass sending tools.
File download: It is recommended to back up immediately after downloading to local area.

Common mistakes and precautions (avoid wasting balance)

❌ Error: Repeated detection of the same batch of numbers A fee will be deducted for each test. Submitting numbers that have been screened previously will waste your balance. Be sure to remove the weight first.
❌ Error: Single task limit exceeded The maximum number of entries per transaction is about 1 million. If your number exceeds 1 million, please submit it in batches (such as 500,000 per batch). The console will automatically prompt.
❌ Error: Misunderstanding age field as exact value The age field is an interval estimate, not precise data like “born in 1992”. It’s more than adequate for crowd targeting, but don’t use it where legal credentials are required.
❌ ERROR: Relying on fictitious functions Please be wary of some service providers claiming to provide “accurate birth dates”. KK-DATA only provides age ranges and will not fictionalize unavailable abilities.
✅ Best Practice: Please take 1,000 samples for a test run first to observe whether the age distribution is reasonable before submitting in batches. For details, please refer to the “Testing” suggestions on Official Website Billing Page.

Comparative advantages of tg 30-year-old data and screen size data of other platforms

Why is there special emphasis on the age field of tg? Because the screening function of many other social platforms (such as WhatsApp, Line) does not provide age information. The following is a comparison of age data availability on common platforms:

Platform	Whether to provide age field	Applicable targeting scenarios
Telegram	✅ Yes (included in gender detection)	Orientation for people around 30 years old, workplace, games, education
WhatsApp	❌ No (currently only open/active detection)	Unable to do age targeting
Line	✅ Available in some areas (gender includes age)	Japan, Taiwan, Thailand market
Zalo	✅ Some fields contain age	Vietnam market
iMessage/RCS	❌ No	Pure number validity check

It can be seen that tg 30-year-old data has unique value in the direction of crowd targeting - especially when you want to reach the 25-34 year old group with the strongest purchasing power.

FAQ

**Q: Can the TG 30-year-old data be accurate to the specific year of birth? ** Answer: No. The age field comes from the interval estimation of the gender detection algorithm. It is recommended as a reference for people “about 30 years old” and cannot be regarded as accurate data at the ID card level.

**Q: Is there any additional fee or subscription required to filter tg 30-year-old data? ** Answer: No need. Gender detection (including age field) is deducted based on the number of messages filtered by Telegram. There is no subscription package. For specific unit prices, please see the real-time price on the console.

**Q: How many numbers can be processed at most in one task? ** Answer: The maximum number of single tasks is about 1 million, which is enough to cover the screening needs of most event crowds. If there are more numbers, they can be submitted in batches.

**Q: How to prevent the same batch of numbers from being tested repeatedly? ** Answer: When using KK-DATA, before submitting a task, you can use the “Data Deduplication Warehouse” to import the number list, compare it with historical tasks, and remove duplicates before submitting.

**Q: How accurate is the age field? ** Answer: It depends on the data source and algorithm model. The general range accuracy is between 70-85%, which is sufficient for market orientation. It is recommended to sample and verify the results.

Now you have your complete TG 30 data checklist. Whether you are preparing for a large-scale private message campaign or a refined community recruitment, following the above steps can help you save a lot of trial and error costs. Want to start screening numbers immediately?
👉 Log in to the console to start screening numbers Two-way customer service contact (recommended): https://t.me/kkdata_robot For more operation details, please see Official Documentation.