How to superimpose activity filtering on US TG data: Guide to active windows, usage order and list stratification

Obtaining high-quality US tg data is only the first step in acquiring customers overseas. The key to truly determining the conversion rate is whether these users are still actively using Telegram. Although a large number of American numbers have opened Telegram, they may not have logged in for months or even a year. Contacting them will not only waste their balance, but also reduce the trust score of the sender. This article explains in detail how to use the activity detection function of KK-DATA to superimpose activity judgment in the process of US TG screening data. By setting the active window, optimizing the screen number sequence and list stratification, each screen number budget can be spent on living people.

What is activity filtering in US TG data? Why focus alone?

Activity filtering refers to further determining whether the user is still using Telegram (logging in, sending and receiving messages, group interactions, etc.) within the specified time range on the basis that the number has been confirmed to have Telegram activated. It is essentially different from simple activation detection:

• Activation detection: It only verifies whether the number is registered with Telegram. It cannot distinguish between “abandoned just after registration” and “used every day”.
• Activity Detection: Detect whether the user has been active recently to help you target the currently reachable people.

For B2B SaaS, cross-border e-commerce, social e-commerce and other businesses targeting the US market, activity is more important than activation status:

• Avoid contacting abandoned accounts: Many American users will change their accounts or abandon them after using them for a short period of time. Simply activating the detection will contain a large number of “zombie accounts”.
• Save time and balance: Focus on active users first, and the inactive list can be postponed or retested later.
• Improve reach: Telegram may have restrictions on frequently sending messages to inactive accounts. Active users open the client more frequently.

KK-DATA’s tg active detection allows you to customize the “activity window”, which determines how many days the user has been active in the past few days. The following details how to set up and use it.

What is the active window? How to set it up?

Activity Window is the core parameter of activity detection: it defines the time span of detection. For example, if the window is set to 30 days, the platform will query whether the number has logged in to Telegram or sent and received messages in the last 30 days. The smaller the window, the more “instantly online” the filtered users are; the larger the window, the more abundant the amount of data, but the level of activity may be low.

How to set the active window in the KK-DATA console

1. Log in to Application Console and create a new screening task.
2. Select Telegram as the detection platform.
3. Check tg active in the detection type (you can also check tg activation, tg gender, etc.).
4. Fill in the number of days you need in the “Active Window” input box below (see the console prompts for the specific fillable range, usually 1 to 90 days).
5. Submit the task and view estimated costs.

The platform supports customizing the number of days. Different platforms/detection types have different unit prices. The final deduction will be based on the console display after the task is completed. For details, please see official website billing page.

The impact of active windows on data quality

• Short window (1 to 7 days): Filter out users who have recently used it frequently, suitable for immediate marketing, such as event notifications, group invitations, and private message promotions. The data volume is small but the quality is extremely high.
• Medium window (14 to 30 days): balances quantity and activity, suitable for regular contact and community acquisition. It can be covered by most normal users.
• Long window (60~90 days): Suitable for long-term cultivation or secondary contact to obtain more numbers, but it may include low active or monthly active users. Can be used for emails or follow-ups.

Recommended active window values ​​in different scenarios

Application scenarios	Recommendation window	Reasons
Community recruitment/group invitation	30 days	Cover most users who are willing to participate in the community
Private message promotion / sales contact	7 days	Find users who have been online recently to reduce the risk of being blocked
Event notifications/limited time offers	1 to 3 days	Ensure users can see the message quickly and increase response rate
Brand awareness / long-term cultivation	60 days	Collect a list of potential users and follow up in stages

How to superimpose activity filtering? Step-by-step guide

The following steps demonstrate how to integrate the activity filtering of US tg data into the task flow of KK-DATA from scratch.

Step 1: Get a list of US numbers

You have two main ways to get a US mobile phone number to be screened:

• Option A (Recommended): Use KK-DATA’s built-in “Global Number Generation” function.
  Enter the console → Number generation → select the country “United States”, you can specify the number segment (such as area code 212, 310, etc.) or generate it randomly. The generation is completely free and can be used directly for screening tasks after exporting.
• Option B: Import the existing number list yourself (CSV/TXT format).
  Make sure there is one number per line, include the country code (e.g. starting with +1), and have a well-formatted format to avoid detection failures.

Step 2: Create a screening task in the KK-DATA console

1. Enter the screen number task creation page.
2. Select the detection platform: Telegram.
3. Detection type: Check tg activated + tg active (if you want to obtain gender data at the same time, you can add tg gender).
4. Active window: Fill in the number of days according to your needs, such as 30.
5. Upload a list of numbers or select a generated number group.
6. Click “Submit Task” and the system will display the estimated cost (by number of items × platform unit price, for specific prices, see the real-time price on the console).
7. After confirmation, the task starts execution.

If you check multiple detection types in one task, the platform will return all fields at once, eliminating the need for two detections, which saves time.

Step 3: View the results and export the hierarchical list

After the task is completed, enter the task details page and the results table will contain the following key fields:

• Number: Original mobile phone number
• tg activation status: yes/no (or not detected)
• tg active status: yes/no (based on the window you set)
• tgid: Telegram unique ID (can be used for subsequent API operations)
• Activity Time: Last active timestamp (if provided by the platform)

You can stratify your list based on active status:

• Active List (status is “Yes”) → Immediately used for outbound calls and community invitations.
• Inactive List (status is “No”) → Stage to separate file, or retest with wider window after some time (e.g. after 30 days).

The export format supports CSV and TXT, which facilitates subsequent import into CRM or mass sending tools.

Usage order and list stratification: from raw data to precise customer acquisition

In actual operations, when faced with a large number of original numbers, how to arrange the detection sequence and list management directly affects cost and efficiency.

Recommended filter order: activated → active → gender (optional)

KK-DATA allows one task to detect “activation + activity + gender” at the same time, so the best practice is to submit it all at once to get all fields. But if your budget is strictly limited, you can do it in steps:

1. First round: only tg activation Filter out all US numbers registered with Telegram and eliminate invalid numbers.
2. Second round: do tg active on valid numbers At this time, a new task needs to be created, and the number list comes from the results of the first round. Note: If the first round of task results already contains tgid, the second round of detection can be accelerated using tgid (platform automatic matching). However, both tasks will incur fees and may be deducted repeatedly (repeated detection of the same number will consume the balance, but KK-DATA has a data deduplication function, see the console for details).
3. The third round: superimpose tg gender on the active list (optional) If the business needs to target gender (for example, male), gender testing can be done on the basis of the active list to achieve a double screening of “active + male”.

Recommendation: Check all detection types directly in one task, which not only saves time, but also avoids repeated billing. The task design of KK-DATA supports multiple types of parallel detection, and the result fields are complete.

List tiering strategy example

The filtered US TG numbers are divided into three levels, corresponding to different reach rhythms:

Hierarchy	Definition (Active Window)	Reach Strategy
High activity	≤7 days	Instant access: private messages, group invitations, event notifications. The highest response rate, priority investment costs.
Generally active	30 days	Regular follow-up: Cooperate with emails and social content to attract traffic. You can schedule a weekly private message or push.
Inactive	>30 days inactive	No contact yet: Store in the standby library, and recheck with a long window every 1 to 2 months to avoid wasting balance.

FAQ

**Q: What is the minimum number of days that can be set for an active window? ** Answer: KK-DATA’s tg activity detection supports setting a minimum period of 1 day (that is, judging whether there is active behavior in the past 24 hours) and a maximum period of 90 days. The specific optional range is subject to the actual display on the console.

**Q: When testing “activation + activity + gender” at the same time, is the fee calculated cumulatively or is it only charged once? ** Answer: The cost is calculated based on the actual number of tests and the unit price corresponding to each test type. For example, if the same number is tested for activation, activity, and gender at the same time, three testing fees will be charged. For specific prices, please check the console’s real-time price or official website billing page.

**Q: If you have done an activation test before and do an active test now, will the same number be deducted repeatedly? ** Answer: Yes. Each inspection task is billed independently. It is recommended to use KK-DATA’s data deduplication warehouse to avoid wasting balance by repeatedly detecting the same batch of numbers. You can upload the detected number in the “Remove Duplicate Warehouse” function of the console, and subsequent tasks will be automatically skipped.

**Q: Is the age field of tg gender detection accurate? Can it be used to screen people around 30 years old? ** Answer: The age field in gender detection is inferred based on public data models and can be used for group trend analysis. It is not an accurate value at the ID card level. You can use it as a reference to filter for a general age range (such as 25-35 years old), but it should not be used as the only basis for judgment.

**Q: What is the use of tgid in the export results? ** Answer: tgid is the unique identifier of a Telegram user. You can use it to perform more sophisticated operations through the Telegram API, such as sending messages directly to the specified tgid, joining groups, etc., without being restricted by mobile phone numbers.

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Mastering activity screening skills is a key step to improve the customer acquisition effect of US tg data. By setting a reasonable active window, optimizing the filter order and list stratification, you can target truly active American Telegram users within a limited budget, significantly increase the response rate, and reduce ineffective costs.

Start your journey to accurate screening now: 👉Log in to the console to start screening numbers If you have any questions, please feel free to contact customer service in both directions: https://t.me/kkdata_robot More usage tips and documentation reference: https://docs.kkdata.cc/