tg How to use the 30-year-old data? Private messaging strategies and practical guide for users around 30 years old

People who promote overseas private messages often encounter a pain point: they know that there are a large number of active users on Telegram, but they don’t know who is really worthy of private messages. If the promotion target can be narrowed down to people who are “about 30 years old, online recently, and gender matching”, the conversion rate can be significantly improved. tg 30-year-old data refers to the age field in the results exported through the “gender detection” function of Telegram screening tools (such as KK-DATA). It can estimate the user’s age group based on the behavioral model and help you quickly locate users around 30 years old. This article gives you a practical operational framework from data acquisition to narrative design.

What is tg 30-year-old data? What does it have to do with Telegram gender detection results?

tg 30-year-old data is not an independent product, but a field in the CSV/TXT file exported after selecting the “Gender Detection” detection type in KK-DATA’s Telegram screening task. The value of this field is an age estimate (for example, 28, 32, etc.), which is estimated by the platform through the user behavior model, not the exact ID-level age. You can see column headers similar to age in the console detection results.

How to interpret the age field

Field Example	Description
`age: 30`	The system estimates the age to be about 30 years old
`gender: male`	Gender identified as male (some results have no gender)

After exporting, you can use Excel or script to filter out numbers between 25 and 35 years old, that is, the “about 30 years old” user group.

Data usage limits and best scenarios

Limitations: It is not possible to be precise to the specific date of birth, and some numbers do not have age data (for example, it cannot be inferred) - this is normal.
Best Scenario: When you need to send promotional information to users of a certain age group, the age field can help you quickly identify targets from millions of numbers, and then cooperate with activity filtering to make private messages more targeted.

Why is the user group around 30 years old the golden age group for overseas private message promotion?

User groups around 30 years old usually have the following characteristics:

Stable spending power: Have a full-time job or start a business, and their purchasing power is better than that of current students or fresh graduates.
High social activity: Use Telegram frequently and are willing to try new services.
Relatively rational decision-making: Not easily incited by exaggerated advertisements, but willing to pay for “visible value”.
Clear life stage: There may be needs in scenarios such as renting a house, buying a car, raising children, fitness, cross-border e-commerce shopping, etc.

Therefore, words targeted at 30-year-olds should emphasize practicality, cost-effectiveness, and after-sales guarantee**, and avoid being too emotional or false promises.

How to use KK-DATA to obtain tg 30-year-old data to prepare for speaking skills?

Step 1: Submit Telegram screening task (check gender detection and set active window)

Log in to KK-DATA Console.
Click “New Task” → select “Telegram Filter Number”.
Check Open + Active + Gender Detection in the detection type (if an age field is required, “Gender Detection” must be selected).
Set an active window (for example, 7 days) to ensure that the number is online in the near future.
Upload the number list (you can first use the global number generation module to create global numbers, or import your own numbers).
After submitting the task, the system will estimate the fee (billed by item, please see the real-time price on the console for the unit price). If the balance is insufficient, you must first recharge USDT (TRC20).

How to set the active window better?

If you want to also ensure that the number is online recently (for example, active within 7 days), you can specify the active window in the number screening task. The age field will automatically identify users who are approximately 30 years old, and no additional operations are required. The specific number of active days is recommended based on your industry and time zone settings.

Step 2: Export the data and filter out numbers about 30 years old

After the task is completed, click “Export” on the console and select CSV or TXT format. After downloading, open it with Excel, find the age column, and use the filter to select values between 25~35. Gender (male/female) can also be filtered to match product audiences. Save as a new list for subsequent private messages.

A discourse framework based on tg’s 30-year-old data: from opening to closing process

After obtaining a list of users aged about 30 years old, the conversation design needs to be centered around three core principles: professionalism, efficiency, and value proof.

Core principles of speaking skills: professionalism, efficiency, and value proof

Professional: Avoid random beginnings such as “Hi bro” and “Hey whatsup”. Users aged 30 are more accustomed to seeing polite and direct openings.
Efficiency: In the first sentence, state your intention and the benefits you can bring to the other party. Don’t beat around the bush.
Proof of Value: Provide real cases, data, coupons or limited-time benefits to make users feel it is worth continuing to read.

Sample speech template (for cross-border e-commerce/independent website promotion)

Scenario: Promote a smart watch (priced at $39.99) suitable for young professionals.

Opening (English example, same as Chinese):

Hi there, I'm from [品牌名]. We're giving a 20% off coupon for our smartwatch that tracks health & notifications.
Just a quick link: [URL]
Safe to click, no spam. Let me know if interested.

Follow-up (if no reply, after 24 hours):

Hi again, that coupon expires in 2 days. 500+ users from [国家] already got it.
Check here: [URL]  
Wish you a good day.

Core Points:

Use a polite address at the beginning, and directly point out the “discount” or “benefits”.
Attached short links to reduce user operation costs.
The sense of urgency of the second follow-up (expiration countdown, social proof) is suitable for the rational decision-making style of 30-year-old users.

From screening to execution of words: How does the complete customer acquisition pipeline operate?

The entire process can be concatenated as:

Global number generation: Generate the number of the target country in the KK-DATA console (free, see official website).
Screen number (including tg age field): Complete the Telegeram screen number according to the above steps and export the data including age and activity.
Data deduplication warehouse: If there are other tasks in the future, the deduplication warehouse will automatically filter the detected numbers to avoid repeated deductions.
Export and filter: Get a list of users around 30 years old.
Import private message tool: Import the CSV into the Telegram private message software you use (such as some automated private message bots) to execute the conversation.

Data deduplication warehouse: avoid duplicate detection

If the same batch of numbers appears repeatedly in different tasks, the deduplication warehouse will automatically filter them. In this way, you only need to pay for the first screen number, and there is no need to check again before importing the private message tool, saving costs.

KK-DATA plays the role of data preprocessing in this pipeline, allowing you to obtain high-quality, low-duplication targeted people.

Compliance reminders and misunderstandings when using tg 30-year-old data

Pay attention to the precision boundary of the age field

The tg 30-year-old data is an age range estimated based on the behavioral model, not the exact year of birth. It is recommended to use it only as a reference for crowd orientation, and avoid directly mentioning specific words such as “You are 30 years old” in your speech to avoid causing resentment.

Do not use in highly regulated industries such as medical and financial industries: Age data is not accurate enough and may cause compliance risks.
Comply with anti-spam laws: There must be an unsubscribe mechanism in target countries (such as EU GDPR, US CAN-SPAM, Indian IT Act) to avoid being reported.
Fake identities or false promises are prohibited: For example, claiming to be an “official partner” or “free for a limited time” but actually having to pay will damage the brand’s credibility.

FAQ

**Q: Is tg 30-year-old data an independent product? What is the accuracy? ** Answer: No. tg 30-year-old data is an age field in the KK-DATA Telegram gender detection results, used to filter people about 30 years old. The accuracy is not ID card level, but it can significantly narrow the target range. Please refer to the actual export results of the console for specific values.

**Q: How to get TG 30-year-old data? Is there any additional charge? ** Answer: When submitting the Telegram ID screening task in the KK-DATA console, just select the “Gender Detection” detection type. The cost is included in the unit price of screen numbers that are billed on a per-item basis, and there are no additional subscriptions. For details on the unit price, please see Console Real-time Price.

**Q: In what scenarios can tg 30-year-old data be used? ** Answer: It is commonly used in cross-border private message promotion, community recruitment, and independent website/e-commerce precise promotion. People around the age of 30 usually have stable consumption power and social habits, and are suitable for rational speech (emphasis on product value, after-sales guarantee, cost-effectiveness, etc.).

**Q: Can the speech template be copied directly? What should I pay attention to? ** Answer: The template provided in this article is a general framework. It is recommended to make secondary adaptations based on your actual products, industries and target markets (such as different time zones and languages). Forged identities or false promises are prohibited and comply with the anti-spam laws of the target country.

Conclusion and call to action

tg 30-year-old data allows you to no longer send private messages based on your feelings, but let the data speak for itself: by combining age fields, activity levels, and gender, targeting users around 30 years old, and using a professional speaking framework, you can significantly improve the private message reply rate and conversion rate. For the entire customer acquisition pipeline, from number generation to screening, deduplication, and export, KK-DATA provides out-of-the-box tools.

Start using KK-DATA to obtain tg 30-year-old data immediately, and use the rhetorical framework of this article to increase the conversion rate of private messages.
👉 Log in to the console to start screening numbers · Two-way contact customer service https://t.me/kkdata_robot · View full document https://docs.kkdata.cc/

How to use tg 30-year-old data? Private messaging strategies and practical guide for users around 30 years old

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