tg 30-year-old data keyword map: Use Telegram’s gender and age fields to accurately locate target groups

In overseas marketing, accurate positioning of “tg 30-year-old data” is the key to effectively acquiring customers. When you need to promote your product to male or female users in their 30s, relying on a “blind” number list is expensive and low-conversion. In fact, through the age field in Telegram’s gender detection, you can filter the users in the number list by age range and gender, build your own keyword map, and spend your limited marketing budget on the people most likely to convert. This article provides you with a set of practical operation procedures from field analysis, screening steps to cost control.

What is tg 30 year old data? Telegram gender and age field analysis

“tg 30-year-old data” is not an independent product or API, but refers to the age field obtained through the “tg gender” detection type in the Telegram screening task. This field will automatically appear in the detection results and be exported together with gender (male/female), tgid and other information. You can filter this field to users who are around 30 years old (for example, 25-35 years old).

Source and credibility of age field

Age data does not come from ID cards or official certifications, but intelligent inference based on user behavior, social graphs, and public information (such as personal information, group interactions). The inference results are presented as integers or intervals (for example, a field value of “30” indicates an inferred age of approximately 30 years). Credibility is suitable for traffic stratification and is not suitable for identity verification. For marketing scenarios, the granularity of “about 30 years old” is enough to help you target the core decision-making group.

Common usage misunderstandings

• Do not treat it as precise age authentication: The 30-year-old field does not mean that the user’s actual birthday is 30 years old, it is just a probability reference.
• Apply to traffic stratification instead of identity verification: In advertising and private message promotion, stratification by age can improve the response rate; but it cannot be used for financial and compliance verification.
• Avoid using alone: It is best to filter together with activity, gender, and region fields to reduce the misjudgment rate.

How to use keyword map to filter Telegram users around 30 years old?

You can use “tg 30-year-old data” as the core coordinates of the keyword map and combine it with other dimensions (gender, active window, country) to generate an accurate target group package. The following are specific three-step operations (taking the KK-DATA console as an example).

Step 1: Set age and gender filters in the filter task

1. Log in to Application Console and create a new filter task.
2. Select tg Gender in “Detection Type” (Note: On some platforms, this type may return both the gender and age fields. The details are subject to the console options).
3. If the console supports age range input (such as 25-35), fill it in directly; if only the original fields are exported, filter by column in the subsequent export file.
4. Check “Gender” as “Male” or “Female” (optional), or leave it blank to get all genders.

Step 2: Combine the active window to optimize the filtering results

Only active users have promotion value. In the same task, it is recommended to also select the tg active detection type and specify the “Active in the past 7 days/30 days” window. The results filtered out in this way are users who are around 30 years old and have been active recently, and can be reached immediately (such as sending messages or inviting people to join a group).

Step 3: Export and analyze user data

Once the task is complete, export a CSV or TXT file. Use an Excel or Python script to sort by the age field (such as the age column) and filter out the records within the range. Then you can:

• Reconstruct keyword map: Use age + gender + country as labels, label them as “30-year-old male-Vietnam”, “30-year-old female-UAE”, etc.
• Import into CRM or promotion tools: Send welcome messages or invitation links in batches by tag.

Why is “tg 30-year-old data” crucial to acquiring customers overseas?

In overseas business, users around the age of 30 are often the main force in consumer decision-making: they have financial capabilities and have stable needs for financial management, fitness, education, social networking and other categories. Through precise age screening, you can:

• Reduce invalid delivery costs: Avoid sending promotions to users of irrelevant age groups and reduce the waste of number detection costs.
• Increase response rate: Promote beauty and maternal and infant products to 30-year-old women, and promote financial technology and gaming tools to 30-year-old men. The conversion rate is much higher than a random cast.
• Support community hierarchical operation: In Telegram groups, operate different content based on age tags to improve retention.

For example, a team working on online education in the Middle East used tg 30-year-old data + UAE + male + active in the past 30 days to filter out 5,000 accurate numbers, and the registration rate for trial classes increased three times in the first month.

How to prepare the number source before screening numbers? Global number generation and import

You don’t need to find the number yourself. KK-DATA provides global number generation function, supports random number generation in 240+ countries/regions, and can also import custom number segment CSV. The generation steps are completely free, and charges are deducted only when using screen number detection.

• Randomly generated: Select the target country (such as Saudi Arabia, Thailand), enter the quantity, and generate it directly.
• Number segment import: If you already have a specific mobile phone number segment (such as 86-138…), you can organize it into a CSV and upload it.
• Free Preview: After generation, you can preview it in the console and then decide whether to use it for screening.

After the generation is completed, directly transfer to the filter task module and filter the tg age and active fields according to the above steps.

Screening task execution steps and best practices

Below is a standard operating SOP (Standard Operating Procedure) for reference when working as a team:

1. Prepare number source: Generate or upload CSV using global numbers, ensuring the number is within 1 million.
2. Create screening task: Select the detection type - tg gender + tg active (it is recommended to include an active window).
3. Set age and gender: Fill in the age range (such as 25-35) in the conditions, and the gender can be “male” or “female”.
4. Estimated fee: Before submitting the task, the console will display the estimated deduction amount. The specific unit price is subject to the real-time price of the console. The unit prices are different for different platforms and different detection types.
5. Submit and wait for notification: The task will be executed automatically after submission. Once completed, you can receive the results via Telegram Notification.
6. Export data: Download the result file in CSV format. The fields include tgid, gender, age, activity, whether it is activated, etc.
7. Data Archiving and Reuse: Import the results into the data deduplication warehouse (see below) to avoid repeated detection.

How to use data deduplication warehouse to save screening costs?

During multiple number screening processes, the same batch of numbers may be submitted repeatedly, resulting in repeated deductions from the balance. KK-DATA’s Data Deduplication Warehouse can automatically record the detected numbers. If the same number is encountered in a new task, the detection will be skipped and no fees will be deducted.

Startup and configuration of deduplication warehouse

Enable the function on the “Deduplication Warehouse” page of the console and set “Cross-task deduplication” or “Per-task deduplication”. It is recommended to select “Cross-task deduplication” so that the detection records of the entire account will be shared.

Actual cost savings from deduplication

Suppose you initially detected 100,000 numbers (100,000 were deducted), and one month later you want to check the activity of 30,000 of them again - if there is no deduplication, the fee for 30,000 will be deducted repeatedly; after deduplication is turned on, the system automatically identifies duplicate numbers and only deducts fees for new or undetected numbers. After long-term use, it can save 20%-40% of the screen size budget.

FAQ

**Q: How accurate is the age field for the tg 30 year old data? ** Answer: The age field is based on user behavior and social graph inference, and is not ID card level accurate. It is recommended to regard it as a screening basis for “people aged about 30 years old” and should not be used for identity verification.

**Q: When screening users around 30 years old, can I specify gender at the same time? ** Answer: Yes. In the KK-DATA screening task, select the “tg gender” detection type to obtain the gender and age fields at the same time, supporting targeted screening.

**Q: After the screening is completed, how to export the data containing the age field? ** Answer: After the task is completed, select “CSV” or “TXT” format to export in the console. The results will include fields such as age and gender. The specific fields are subject to the console export column.

**Q: How many numbers can be processed at most in a single screening task? ** Answer: A maximum of approximately 1 million numbers can be submitted for a single task. It is recommended to process in batches according to target areas to avoid task timeout or mixed results.

**Q: How to generate a large number of target country mobile phone numbers before screening? ** Answer: Use KK-DATA’s “Global Number Generation” function, which supports random generation in 240+ countries/regions, and you can also import custom number segments CSV. The generation steps are free, and the screen numbers are deducted per item.

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Now you have mastered the method of using tg 30-year-old data to build a keyword map and accurately filter target users based on gender and activity. Log in to the console immediately to start your first batch of screening tasks, or get help from the two-way customer service robot.

👉Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot For detailed usage guidelines, please refer to the official documentation: https://docs.kkdata.cc/