tg Interpretation of 30-year-old data across the entire network: meaning of the age field, acquisition sources and practical guide to screening

In overseas marketing and Telegram community operations, “tg 30-year-old data” is a concept that is frequently mentioned but often misunderstood. Many marketers think it is an independent “age screening product” that can accurately target 30-year-old users like checking ID cards. In fact, it is an estimated field in Telegram’s gender detection results, used to assist in crowd profiling rather than as a precise age certificate.

This article will thoroughly dismantle tg 30-year-old data from four dimensions: data source, field meaning, acquisition method, and actual combat scenarios to help you correctly understand and use it to improve customer acquisition efficiency. The KK-DATA practical operation process is attached at the end of the article, which can be directly applied.

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What is tg 30-year-old data? Where does it come from?

tg 30-year-old data refers to the estimated age value corresponding to each number in the Telegram screening number (especially the gender detection type) results. This value usually appears as an integer (e.g. 30, 35) or an age range (e.g. 25-35, 36-45) and is included in the exported CSV file.

Data source: public information + model inference

The age field is not directly provided by Telegram’s official API. KK-DATA’s Telegram gender detection model infers age by analyzing the following public information of the target account:

• Avatar: facial features, clothing style, image background (such as campus, office)
• Nickname (Name/Username): Word usage habits, such as “post-90s”, “uncle” and other words that imply age
• Personal Profile (Bio): Mention graduation year, working years, children, etc.
• Group/channel interaction language style: Emoticon usage habits, Internet slang

After combining the above features, the model outputs an estimate with the highest probability. Since authoritative information such as ID cards and passports cannot be obtained, this value naturally contains errors.

tg 30-year-old data is not equal to the real age

This is where users are most likely to misunderstand. Please remember three points:

1. Estimated rather than precise: The “30” returned does not represent the user’s true age of 30, but may be an estimate between 28-32 years old.
2. Unofficial data: Telegram officially does not provide age verification function, and all ages are derived from model estimation.
3. Information missing: If the avatar, nickname, and profile information are insufficient, the model will return “unknown” or “null”, and the age field will be empty.

Which platforms/detection types will output the age field?

Platform	Detection type	Whether to output the age field	Description
Telegram	Gender detection	Yes	Contains fields such as age, gender, tgid, etc.
Telegram	Activation detection	No	Only determine registered/unregistered
Telegram	Activity detection	No	Only determine the most recent online time
Line	Gender detection	Yes (subject to the console)	Line gender detection also supports age inference
WhatsApp	Activation/Activity Detection	No	Age determination is not currently supported
Zalo	Gender detection	Subject to console	For Vietnam market

Note: The detection types and export fields of each platform are subject to the real-time display of Console, and may be updated in different versions.

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tg How does 30-year-old data help Telegram acquire customers?

The greatest value of the age field is that it serves as a coarse-screening label for crowd portraits. When used cross-wise with gender and activity, it can greatly improve accuracy.

Age + gender secondary screening ideas

Suppose you need to promote to male B2B SaaS potential customers aged 25-35 years old. The steps are as follows:

1. Prepare number pool: Import a batch of Telegram user numbers through global number generation or own CSV.
2. Submit Telegram gender detection: Select the gender detection type and wait for the task to be completed.
3. Export CSV and filter:
   • Age field: Filter for age >= 25 and age <= 35 (or contains the “25-35” age group)
   • Gender field: Filter gender = Male
4. Use filter results for targeted marketing: send private messages or invite group members.

The overall profile of the candidate group screened out in this way is close to the target customers, and the conversion rate is 2-3 times higher than blind mass mailing.

Combination strategy of age + activity

Another practical combination: High Activity + Age Specific.

For example, if you run a mutual aid group for professionals who are around 30 years old, you need to recruit new people. You can first filter out users who have been “active in the past 7 days” through activity detection, and then extract the age field from the gender detection results. This not only ensures that users have a high online rate and strong willingness to interact, but also meets the target age group.

1. First use Telegram活跃检测 to filter out active users.
2. Then use Telegram性别检测 to obtain the age and gender fields of these active users.
3. Combine the two results and lock in candidates who are “active + age 25-35”.

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How to get tg 30-year-old data? KK-DATA practical operation process

Below are the complete steps to get the age field from zero to one using the KK-DATA platform.

Step 1: Prepare numbers (generate or import)

If your target market is North America, Southeast Asia or Europe, you can use the Global Number Generation feature:

• Enter the “Number Generation” module of the console and select the target country (259+ countries/regions are available).
• You can generate random numbers, segment numbers, or import your own CSV.
• Generating numbers is free and does not consume your balance.

If you already have a list of customer leads, import it directly via CSV.

Step 2: Submit Telegram gender detection task

1. Enter “Screen Task” → “New Task” → select Telegram as the platform.
2. Select “Gender Detection” for the detection type (some platforms are marked as “Gender + Age”).
3. Upload or paste the number list (up to about 1 million at a time).
4. Optional configuration: active window (such as “online in the past 30 days”) - if selected, the activity will be verified first and then the gender will be detected, and double billing will be based on active detection + gender detection.
5. Check the estimated fee before submitting to confirm that the balance is sufficient.

Step 3: Interpret the age field in the result and export it

After the task is completed, export the CSV file. The field columns usually include:

Field name	Example value	Meaning
phone	85212345678	Original number
status	registered	registered test results
gender	Male / Female	Gender inference
age	30 / 25-35 / unknown	Estimated age
tgid	123456789	Telegram User ID
online_status	active_7d	Active window (if configured)

Filtering formula suggestions (take Excel as an example):

• Exact value filter: =AND(age >= 25, age <= 35) (if age output is an integer)
• Text matching: =ISNUMBER(SEARCH("30", age)) (If the output is the age group string “25-35”, you can use this formula to determine whether it covers the age of 30)

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tg Common misunderstandings and precautions for 30-year-old data

Common misunderstandings	Correct understanding
”The age field is official data, accurate to single digits”	Model estimation, error is normal, mean ±3-5 years old
”Age detection service can be purchased independently”	The age field is an incidental output of gender detection and is not provided independently
”Age = 30 means you must be 30 years old”	It may be an estimate in the 28-32-year-old range, and does not represent the exact age
”All Telegram accounts have an age”	Return unknown when the avatar/nickname/profile information is insufficient
”The age field is always valid”	After the user changes his avatar or nickname, the original estimated value may become invalid

Best Practice:

• Treat the age field as a group portrait label rather than individual precise data.
• Try to make a comprehensive judgment based on multiple fields such as activity level, gender, tgid export, etc.
• For high-value clues, it is recommended to further confirm the target’s identity through private message interaction.

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What to do if there is no age field? Other crowd targeting methods

If the target platform does not support age inference, or a large number of age fields in the detection results are empty, the following dimensions can be used instead:

1. Activity Screening: Users who subscribe to specific channels/groups have different age trends. Active users can be targeted based on their activity levels.
2. Avatar style inference: Use tools to batch analyze avatar types (such as whether to wear a tie/formal suit, which may point to the workplace).
3. Time to join the group: Check the user registration time through tgid (needs to be combined with third-party tools). Old users are often older.
4. Nickname keyword matching: For example, if the nickname contains words such as “CEO”, “Founder” and “Marketing”, it may be 30+ business users.

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tg Real application scenarios of 30-year-old data in cross-border B2B customer acquisition

Scenario 1: Promote overseas SaaS tools to small and medium-sized business owners

Assume that your product is a Shopify independent website marketing plug-in, and the target users are men aged 25-40 who have cross-border e-commerce experience.

• Step one: Use KK-DATA to generate mobile phone number segments in Southeast Asia (Thailand, Indonesia, Vietnam).
• Step 2: Submit the Telegram gender test and filter out the results of gender=Male and age=25-40.
• Step 3: Send product introductions or group invitations to these users. The conversion rate is usually more than 50% higher than random group sending.

Scenario 2: Recruiting technical developers to promote SaaS products

Promote API/SDK products to male developers around 30 years old (such as 25-35 years old).

• Step one: Import Telegram accounts collected from public channels such as technical communities and GitHub.
• Step 2: Perform gender + age detection to identify targets that match the profile.
• Step 3: Combine with community operations to build an exclusive developer group.

Scenario 3: New local lifestyle apps

Target 30-year-old female users (such as mothers) to promote maternal and infant or life service apps.

• Step 1: Prepare numbers collected from local offline activities.
• Step 2: Screen active users of gender=Female and age=28-35.
• Step 3: Send targeted trial invitations.

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FAQ

**Q: Can the TG 30-year-old data be accurate to the specific day of birth? ** Answer: No. The age field in telegram gender detection is estimated by the model based on public information such as avatar, nickname, profile, etc. It usually returns an integer age (such as 30) or age range (such as 25-35), which cannot be accurate to birthday or ID card level accuracy.

**Q: How do I know if a number contains an age field? ** A: After submitting the Telegram gender detection task and completing it, check whether there is an “age” or “age” field column in the result export CSV. If this field is empty or displays “unknown,” the model cannot infer age. It is recommended to check the gender, activity and other fields at the same time to assist in judgment.

**Q: Does the age field value “30” necessarily mean that the user is 30 years old? ** Answer: Not necessarily the actual age of 30. The model may make inferences based on characteristics such as the clothing of the avatar and the wording of nicknames, and the error is normal within a few years. It’s best to think of age values ​​as “approximately a certain age” rather than exact values.

**Q: If I don’t want to filter age, but only gender, can I select it separately? ** Answer: Yes. KK-DATA’s Telegram gender detection task will output multiple fields such as gender, age, tgid, etc. at the same time. You can only keep the required columns when exporting in the console, or filter by gender fields in Excel later.

**Q: Do non-Telegram platforms (such as Line and WhatsApp) also have age fields? ** Answer: Currently, KK-DATA’s Line gender detection will also output the age field (need to confirm the console), but platforms such as WhatsApp and iMessage may not support age judgment. Please refer to the “Export Field” description of each platform on the official website’s billing page.

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After reading this article, if you need to obtain and filter tg 30-year-old data in batches, you can directly log in to the KK-DATA console, or obtain operational guidance through the two-way customer service Telegram robot. Three simple steps: Generate/import number → Submit Telegram gender detection → Export the results including age field. No subscription required, billed per item, stops when used up.

👉 Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot Learn more: Visit the official website https://kkdata.cc/ or check the usage documentation https://docs.kkdata.cc/