How to Choose Telegram Screening Active Window: 7-Day/15-Day/30-Day Selection Guide & A/B Testing Plan

Almost everyone doing Telegram customer acquisition faces a core issue: how many of the numbers I get are actually being used by real people? Simply checking if a number is “registered” (i.e., registered on Telegram) isn’t enough, because many numbers could be zombie accounts, secondary accounts, or silent accounts that haven’t logged in for a long time. That’s where the Telegram Screening Active Window feature comes in—it lets you filter out real active users who have been online within the last 7, 15, or 30 days. This article will walk you through how to choose different windows from definition to practice, and how to find the best parameters for your target audience through A/B testing, so you don’t waste balance by blindly filtering.

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What Is the Telegram Screening Active Window

The active window is an advanced filter in Telegram screening used to determine whether a number has been “online” within a specified time range. The platform checks the user’s public “Last Seen” time: if that time falls within your set window (e.g., within 7 days), the number is marked as “active”; if it’s beyond the window but the number is registered, it’s marked as “valid but inactive.”

• 7-day window: Filters users who have been online in the last 7 days—highest probability of immediate response.
• 15-day window: Filters users who have been online in the last 15 days—a balance between coverage and activity.
• 30-day window: Filters users who have been online in the last 30 days—broadest reach.

Note: The active window checks “Last Seen” time, not real-time online status. If a user has hidden their Last Seen, the number falls into the “undetectable” category and is not counted as active.

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Why “Active” Matters More Than “Valid”

Many people first encountering screening only care whether a number is registered on Telegram, but the actual results are often far less satisfying. For example: you get 100,000 valid numbers (registered and active), but perhaps only 30% are really active within the last 7 days. If you directly send bulk messages or invite those 100,000 numbers to groups, the results will be:

• Lots of messages sent to users who haven’t logged in for a long time—no response.
• If the target numbers are secondary or zombie accounts, you not only waste message costs but also risk triggering Telegram’s anti-spam restrictions.
• Very low marketing conversion rates—not worth the effort.

By using the active window filter, you only reach genuinely active users, significantly improving response rates and group join rates. For scenarios like private messaging promotions, community growth, or event notifications, activity level is far more valuable than mere registration.

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How to Choose the Active Window for Different Scenarios

Community Operations & Instant Interaction – Recommended: 7-day Window

If you run Telegram communities and need to quickly invite people into groups, participate in discussions, or attend events, the 7-day window is the best choice. In such scenarios, users who have “just been online” are likely actively using Telegram and will respond faster to invitations. The 7-day window produces the fewest numbers but the highest quality—group join rates and activity are significantly better than other windows.

Private Message Promotion & Lead Follow-up – Recommended: 15-day Window

When doing one-on-one private message promotions (e.g., B2B inquiries, product introductions), you can’t focus only on people who were “online yesterday” because potential customers might check messages every few days. The 15-day window is a good balance: it covers users active within the last two weeks, ensuring most target audiences aren’t missed while not mixing in too many silent accounts that haven’t logged in for more than two weeks. For longer follow-up cycles, the 15-day window helps you find the sweet spot between “breadth” and “efficiency.”

Brand Promotion & Cold Start – Recommended: 30-day Window

If you’re doing brand exposure, event warm-up, or project cold start, the core goal is to maximize reach—even if the user doesn’t reply immediately, it counts as an exposure once they see the message. The 30-day window filters out all users who have been active in the last month, suitable for multi-round follow-ups (e.g., send a teaser first, then refine based on responses). However, note that among the 30-day window numbers, a significant portion may not have been online in the last day or two, so response speed will be slower. It’s recommended to pair with a secondary 7-day or 15-day filter.

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How to Find the Best Active Window Through A/B Testing

No window is universally best, because different industries and audiences have different online habits. The most reliable method is A/B testing—let the data speak.

A/B Test Design Steps (Three Groups)

1. Prepare a number pool from the same source: Ideally, numbers obtained from the same channel (e.g., generated by a global number generator or imported from the same batch) to ensure consistent initial quality.
2. Divide into three groups, filter with 7-day, 15-day, and 30-day windows respectively: Use equal sample sizes for each group—for example, 5,000 numbers per group.
3. Record output quantity: Submit tasks in the KK-DATA console separately, then record the number of “active numbers” filtered by each window after exporting results.
4. Perform the same operation on each window’s active numbers: For example, send the same message content, invite to the same group, then track metrics like group join rate, reply rate, and click-through rate.
5. Compare data and choose the best-performing window: If the 7-day window’s group join rate is twice that of the 15-day window but the quantity is 30% less, you need to balance based on your goal (pursuing conversion rate vs. reach). It’s usually recommended to prioritize higher conversion rate and then compensate for coverage by sourcing more numbers.

Sample Size & Testing Cycle Recommendations

• At least 5,000 numbers per group: Too small a sample leads to large statistical errors. 5,000–10,000 per group is recommended.
• Testing cycle: 3–7 days: Give enough time for users to respond. Too short may miss weekend logins; too long may cause some numbers to become inactive.
• Control variables: Keep message content, sending time, and channel consistent; only vary the active window.

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Key Notes for Active Filtering

• Windows cannot be stacked: Only one active window can be selected per screening task. To compare, run separate tasks for A/B testing.
• Custom date range not supported: The active window uses a unified “relative time” (e.g., the last 7 days up to now); absolute dates like “from the 1st to the 15th of this month” are not supported.
• Privacy settings affect results: Users who hide their Last Seen will not be counted as active, but will be marked as “undetectable” in exported results. If you find a high proportion of numbers in this category, try first using “valid check” to confirm registration, then refine with other dimensions (e.g., gender, nationality).
• Avoid duplicate checks: KK-DATA provides a data deduplication repository. Before submitting a task, the system automatically checks already screened numbers to avoid duplicate charges. Make full use of this feature.

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How to Set Active Window Filtering in KK-DATA

The process is intuitive and requires no programming:

1. Log in to the console: Visit https://app.kkdata.cc/.
2. Import numbers: Supports CSV or TXT upload, or use the “Global Number Generation” module to create numbers.
3. Select TG screening task: Click “New Task,” then choose “Telegram Screening.”
4. Check “TG Active Detection” and select days: Under detection type, check “TG Active,” then choose 7, 15, or 30 days in the pop-up window. You can simultaneously check “TG Valid Detection” to complete both active and valid checks in one task.
5. View estimated cost: Before submission, the system shows the estimated charge for the task (charged per number; see real-time prices in the console).
6. Submit task: Wait a few minutes to a few hours (depending on the number size); you’ll receive a Telegram notification when the task completes.
7. Export results: Download CSV/TXT files from the task details page, containing each number’s active status (active/valid but inactive/undetectable).

Tip: If you’re unsure which active window to choose for your current numbers, first run a small test task with a few hundred numbers to observe each window’s output ratio.

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Data Application Suggestions After Active Filtering

After obtaining the filtered results, process them as follows:

• Active numbers: Use directly for private message promotions, group invitations, and event notifications. If you need further segmentation by gender or nationality, add another screening task in KK-DATA (e.g., select Telegram gender identification).
• Valid but inactive numbers: Save these and mark them as “waiting for secondary follow-up.” After some time (e.g., a week), re-screen them to see if some become active again. Alternatively, use them for non-urgent marketing (e.g., broadcast messages that users will see when they next log in).
• Undetectable active status numbers: If the proportion of such numbers is high, it means the target audience has strict privacy settings. Consider dropping active filtering and only using “valid detection” combined with other dimensions (e.g., country, number segment) to optimize.
• Avoid duplicate checks: Already-screened numbers automatically enter the KK-DATA deduplication repository. Re-importing the same batch won’t incur duplicate charges. Use this feature to first do a 30-day window initial screen, then run a secondary 7-day window filter on the active numbers, achieving “coverage first, refinement later.”

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Frequently Asked Questions

Q: Can active windows be stacked? For example, first filter with 7 days, then filter those results again with 30 days?
A: Not recommended. Only one active window can be selected per screening task. To compare different windows, run separate A/B test tasks. If you want “broad then refined,” first use the 30-day window to get active numbers, then use the 7-day window on those active numbers for a secondary filter.

Q: I want to filter users active between the 15th and 30th of this month. Can the active window achieve this?
A: No. The active window uses a unified “relative time” (e.g., the last 7 days up to now); absolute start/end dates are not supported. The platform checks whether the user’s last online time falls within the selected number of days. Custom date ranges are currently not available.

Q: What’s the accuracy of active detection? Could it miss the same person?
A: Detection accuracy is high but limited by user privacy settings. If a user has hidden “Last Seen,” the number falls into the “undetectable active status” category and is not counted as active. The platform marks these undetectable numbers in the exported results. For users who publicly display Last Seen, the detection results are accurate and reliable.

Q: Can I immediately invite or message numbers from the 7-day active window?
A: Yes, but it’s recommended to also run “Telegram valid detection” first to verify that the numbers are registered (i.e., have Telegram accounts). KK-DATA supports simultaneous “valid + active” checks in one task, preventing you from treating invalid numbers as active.

Q: Do I need to deposit a lot of balance for A/B testing?
A: Testing cost depends on total number volume. For example, 3 groups of 5,000 numbers each = 15,000 detections. At the platform’s unit price (see console for real-time rates), this usually costs a few tens of USDT. It’s recommended to start with a small test to confirm window differences before scaling up.

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With this guide, you now understand the logic of choosing Telegram screening active windows and the A/B testing method. Start testing with the 7-day and 15-day windows, use data to find the optimal window for your target audience, and you’ll take a key step toward improving TG customer acquisition efficiency.

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