tg 30-year-old data’s implementation guide in e-commerce promotion: Ideas for matching e-commerce categories and crowds

If you are doing cross-border e-commerce, independent website promotion, or operating a Telegram community for overseas users, you must be familiar with the term “crowd profiling”. But the question is: **In the list of mobile phone numbers you got, which users are around 30 years old, have a strong willingness to consume, and are suitable for pushing your e-commerce products? **

This is the value of tg 30-year-old data - it is not a mysterious black technology, but uses the age field in Telegram’s gender detection function to help you filter out number holders who are about 30 years old. Combined with specific e-commerce categories, you can accurately target your promotion resources to this group of golden users.

This article will focus on:

• tg What is the 30-year-old data and where does it come from?
• Why 30-year-olds are the “bullseye” for e-commerce promotion
• How to use the KK-DATA platform to obtain this batch of data
• Matching ideas and implementation steps for three types of e-commerce core categories

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tg What is the data for 30 years old? Where does it come from?

When many operators hear “tg 30-year-old data” for the first time, they think it is a separate filter switch. Actually, it comes from a combination of features of Telegram Gender Detection.

In the screening task of the KK-DATA platform, when you select “Telegram Gender Detection”, in addition to seeing the gender (male/female), an age field will also be returned (the field name can be seen in the console export CSV). This age field is used to determine whether the number holder is approximately 30 years old. **Note: It is not an ID-level precise age, but an estimated range based on social public data, but sufficient for population stratification. **

Field	Meaning	Typical uses
tg_active	Whether it is active	Filter dead numbers
gender	gender	oriented to men and women
age_range	Age range (such as 25-35)	Determine people around 30 years old

Superimpose the three conditions of “active + male/female + age about 30 years old”, and you will get a list of tg 30-year-old data - behind each number are real users who fit the profile.

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Why is the e-commerce category highly matched with the TG 30-year-old crowd?

The age of 30 is a “watershed in consumption”:

1. Strong purchasing power: Most people in their 30s already have a stable income, and their monthly consumption budget is often higher than that of people in their early 20s.
2. Focus on quality: No longer just pursue low prices, but also value product durability, brand sense, and after-sales service.
3. Family consumers: Many 30-year-olds are married or have stable partners and will buy maternal and infant products, home appliances, home decoration and other categories for their families.
4. Decision-making rationality: Willing to pay for “saving time”, such as smart hardware, subscription services, and DTC brands.

These characteristics are almost perfectly aligned with the core categories of e-commerce: high customer unit price (electronics, home appliances), high repurchase (maternal and infant, personal care), and new brands (DTC blue ocean).

If you are using Telegram for private domain backstreaming or cold messaging, post your product link on tg 30-year-old data, the conversion rate is usually 2~3 times higher than random mass messaging (based on industry experience, non-fictional data).

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How to get tg 30-year-old data? Accurate pose detection for age field with gender

With the KK-DATA platform (https://kkdata.cc/）为例，完整步骤如下：

Filter “tg active + gender age field” in the console

1. Log in to the console https://app.kkdata.cc/.
2. Click “New Screen Number Task”.
3. Select the platform “Telegram”.
4. In Detection Type, check:
   • tg开通 (required, confirm the number is registered with Telegram)
   • tg活跃 (optional, recommended, exclude inactive accounts)
   • Telegram 性别检测 (Core! Only in this way can the age field be output)
5. Select the gender (male/female/any) according to your needs, and the age field will automatically appear in the test results.
6. Set the task name and click “Next”.

Register, import numbers and submit number screening tasks

• If you don’t have an account yet, register on the official website (free) first, and then deposit USDT (minimum of about 50 USDT). **The balance will be deducted on a per-item basis, and there is no subscription package. **
• Prepare your list of numbers: can be in CSV or TXT format, one number per line, international format (e.g. 8613800138000).
• Import numbers: Upload a file on the task page, or paste a list of numbers.
• Submit the task: The system will display the estimated cost (For specific unit prices, please see the real-time price on the console), submit after confirmation.
• Wait for the task to complete (usually a few minutes to a few hours, depending on the size of the number).
• When exporting results, select CSV Include all fields and you will be able to see the age_range columns (e.g. “25_35” “30_40”).

Filter out the numbers where age_range is equal to or contains 25_35 and 30_40, and you’ll get tg 30-year-old data.

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tg Matching ideas between 30-year-old data and three core categories of e-commerce

After getting the data, the key is how to use it. The following three directions have been verified to be effective by many overseas e-commerce teams (based on public industry discussions, non-customer cases).

High customer unit price categories: consumer electronics, home appliances

Population Characteristics: Mainly 30-year-old males, with purchasing needs for digital products and smart home appliances, and willing to pay a premium for quality. They usually already follow tech channels or groups on Telegram.

Matching ideas:

• Use tg 30岁数据 + Gender=Male to filter out people.
• Combined with tg活跃 detection, make sure you don’t send messages to dead people.
• The promotion content focuses on “parameter comparison”, “cost-effectiveness”, and “practical evaluation”, and is coordinated with Telegram private messages or group messages.

Implementation: Import the filtered numbers into your CRM or Telegram mass messaging tool, and push new product launch or discount information in batches. Pay attention to the frequency, 1-2 times a week.

Highly repurchased categories: maternal and infant products, personal care

Population Characteristics: 30-year-old women (+ some married men), the main household consumers, have stable demand for diapers, milk powder, skin care, and health care products. They trust recommendations from acquaintances and word-of-mouth more.

Matching ideas:

• Use tg 30岁数据 + gender=female to filter.
• Can be further stacked tg活跃 (recently active users are more likely to open messages).
• Promotion strategy: Keywords can include “family outfits”, “hoarding discounts” and “trial outfits”.

Implementation: Create an exclusive Telegram channel or group, attract this group of users, and issue coupons regularly. Due to the high frequency of repurchases, an LTV model can be established to continue conversions.

New brands/emerging categories: DTC brands, cross-border blue ocean categories

Crowd characteristics: 30-year-olds are still highly receptive to new things and are willing to try DTC brands with stories and designs (such as environmentally friendly shoes, niche snacks, smart home gadgets). Their decision-making links are shorter and they are easily impressed by social media content.

Matching ideas:

• Use tg 30岁数据 + Gender is not limited, but you can filter the “active + age field”.
• Combine with Line/Zalo/RCS and other platform filters to expand coverage (KK-DATA supports multiple platforms).
• The promotion content highlights the “brand story” and “limited sale”, and uses Telegram to send group pictures and videos.

Implementation: First run 1,000 pieces of data for A/B testing to see which age sub-range (25-30 vs 30-35) has a higher response rate to your product, and then scale it up.

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FAQ

Question: Is the age field in tg 30-year-old data accurate? Is it accurate to the specific age?

Answer: It is not the exact ID card age, but an estimated range based on Telegram account public data and social network information, such as “25-35 years old” and “30-40 years old”. It is enough for crowd stratification, but it cannot achieve the accuracy of “Zhang San is 30 years old this year”. **Please do not place undue reliance on this being criminal level evidence. **

Question: If I want to screen the “25-30 years old” group separately, can I do it?

Answer: Yes. In the detection results of the KK-DATA platform, the age_range field will return multiple intervals. You can only keep the rows containing 25-30 during post-processing. But please note: the platform does not support filtering by precise age range. You need to download the full results and filter in CSV.

Question: I only checked “tg activation test”, why don’t I see the age field?

A: The age field is part of the “Telegram Gender Detection” feature and is not provided by default. You must also check “Telegram Gender Detection” in the detection type to get age data. Only selecting “tg activation” can only tell whether the number is registered with Telegram.

Question: Can tg 30-year-old data be used in conjunction with Line and Zalo data?

Answer: Yes. KK-DATA supports multiple platforms (Telegram, WhatsApp, Line, Zalo, etc.). You can submit the same batch of numbers to detection tasks on different platforms, and then perform cross-analysis. For example, filter out users who are “active on Telegram and about 30 years old + active on Line” and target them across platforms.

Question: How many numbers can be detected at most in one task?

Answer: The current upper limit for a single task is about 1 million. If the number is larger, it can be submitted in batches. Each test is charged on a per-time basis, For specific unit prices, please see the real-time price on the console.

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**Want to get your tg 30-year-old data immediately and apply it to e-commerce promotion? **

👉 Log in to the console to start filtering: https://app.kkdata.cc/ If you have any operational problems, you can contact customer service in both directions: https://t.me/kkdata_robot For more function details, please refer to the document: https://docs.kkdata.cc/

**The key to improving efficiency is often not to burn more money, but to be more precise. **