TG Active Data Refresh Guide: How to Match Re-screening Cycles with Contact Rhythm to Keep Data Fresh

In overseas marketing and Telegram community operations, the activity level of phone numbers is the core indicator determining outreach effectiveness. You may have already completed a round of Telegram number screening and obtained a list of “valid” or “recently active” numbers. But after a few days or weeks, when you use this data again, the reach rate and response rate drop significantly. This is not because you chose the wrong numbers, but because the TG active data has “expired.”

TG active data refresh refers to re-running activity detection (e.g., 7-day, 15-day, or 30-day active) on already screened Telegram active numbers to update their current activity status. Unlike the initial screening, the goal of a refresh is “update” rather than “first-time detection.” It helps you grasp user behavior changes in real time, ensuring every contact is based on the latest, most accurate data. This article will dive into the necessity of TG active data refresh, the optimal re-screening cycle settings, and how to efficiently keep data fresh using the KK-DATA platform.

What is TG Active Data Refresh?

Simply put, TG active data refresh is like giving your Telegram number list a “health check” to confirm which users are still actively using their accounts. Its core value lies in converting static “historically valid numbers” into dynamic “currently reachable numbers.”

Differences Between Active Data, Registered Data, and Valid Data

Many people confuse “registered detection,” “valid detection,” and “active detection.” On the KK-DATA platform, these three detection types correspond to different data depths:

Detection Type	What It Detects	Use Case
TG Registered (Signup Check)	Whether the number has a Telegram account	Initial screening: identify if the number is a Telegram user
TG Valid	Whether the account can be normally contacted (not banned, etc.)	Confirm account usability for general outreach
TG Active	Check the user’s last online/message time (e.g., within 7/15/30 days)	Precision outreach: ensure the user was recently online, improving response rates

Active data tells you not only that the user “exists,” but also that the user “was recently online.” This timestamp-based judgment is key to improving message delivery rates and user engagement.

Why Does Active Data “Expire”?

Telegram users’ activity status is dynamic. A user active today may become inactive a week later for reasons such as:

• The user temporarily leaves Telegram for personal reasons (work, life), leading to a longer silence period.
• The user switches to a main account and abandons the old one.
• The user’s account is temporarily or permanently banned for violating platform rules.
• The user deletes the Telegram app.

Suppose you screened a batch of 7-day active numbers last week and successfully sent promotional messages. But this week, 20% or more of those users may no longer be online. If you directly use the old list to send again, you not only waste message credits but also risk damaging your account reputation due to invalid sends. Therefore, TG active data refresh is not optional—it is a routine data maintenance task that must be performed.

When Should You Refresh TG Active Data?

Not all scenarios require high-frequency active data refreshes. Below are three typical refresh opportunities. Choose based on your situation.

Regular Outreach Scenarios (e.g., Weekly Reports, Coupon Push)

If you have a fixed messaging schedule (e.g., community weekly reports, member discount promotions) every week or month, it is recommended to refresh active data 1-2 days before each send. This brings two direct benefits:

• Improve delivery rate: Ensure messages are sent to users who were recently online, avoiding “dead number” inboxes.
• Save costs: KK-DATA charges per detection. Sending messages to inactive users wastes resources. Filtering out silent users with refreshed active data significantly improves the cost-effectiveness of each contact.

Marketing Campaign Warm-up and Sprint Phases

Large marketing campaigns (e.g., new product launches, limited-time discounts) usually involve multiple rounds of outreach. For a 7-day campaign cycle, the following refresh cadence is recommended:

• 7 days before the campaign: Refresh active data once, filter out recently active users, and add them to the warm-up list.
• 1 day before the campaign: Refresh the active list again to ensure the users reached at the start of the campaign are the most active “at that moment.”

This strategy of refreshing TG active data at key nodes maximizes campaign outreach effectiveness. Because user online rates are typically highest on the campaign day, refreshing one day in advance can capture new active users who came online just before the campaign.

A/B Testing Different Active Windows

If you need to verify which active window (7-day, 15-day, 30-day) yields higher response rates, you can run different activity checks on the same batch of numbers at different times. For example:

• On Monday, detect 15-day active numbers and send messages.
• On Thursday, detect 7-day active numbers on the same batch and send messages again.

By comparing response rates across different windows, you can find the re-screening cycle that best suits your business model. The KK-DATA platform allows you to set a specific active window in a single task, making such granular testing convenient.

How to Set the Re-screening Cycle for TG Active Data?

There is no one-size-fits-all answer for the re-screening cycle. It should be adjusted based on your industry characteristics, user base size, and contact rhythm. Below are two practical approaches.

Adjust Based on User Activity Lifecycle

Not all numbers require the same refresh frequency. You can classify users into different tiers based on the timestamps from historical active data:

• High-activity users (online daily or every 2-3 days): Their activity status is relatively stable; the refresh cycle can be extended to 15-30 days.
• Medium-activity users (online 1-2 times per week): Recommended refresh cycle is 7-15 days.
• Low-activity users (online once every two weeks or longer): Their activity fluctuates greatly; the refresh cycle should be shortened to 7 days, or even every 3-5 days.

In practice, you can export TG active detection results containing the last online timestamp during the first screening. Based on this timestamp, group the numbers and set different refresh frequencies for each group. KK-DATA supports importing up to approximately 1 million numbers per single task, so you can easily manage large user groups.

Choose Refresh Window Based on Contact Rhythm

The most straightforward strategy: Your outreach frequency determines your refresh frequency.

• Daily outreach: Refresh active data every day or every 2 days. Ensure that each time you send, the user is in a “recently online” state.
• Weekly outreach: Refresh once a week, then immediately use the new data for sending.
• Bi-weekly or monthly outreach: Refresh 3-5 days before sending; no need for frequent operations.

Such a matching strategy maximizes the cost-effectiveness of each contact. If you contact daily but refresh only every two weeks, the effectiveness in the second week will drop significantly, wasting sending opportunities. Conversely, if you contact weekly but refresh daily, you will accelerate balance consumption without commensurate benefits.

Best Practices for Keeping TG Active Data Fresh

To make data refresh more efficient and cost-saving, consider the following three best practices.

Use a Data Deduplication Repository to Avoid Repeated Detection

This is the most overlooked but cost-saving tip. KK-DATA provides a data deduplication repository feature that can identify numbers already detected across tasks. When you perform multiple TG active data refreshes on the same batch of numbers, the deduplication repository automatically recognizes “numbers whose status hasn’t changed from historical results in this task” and avoids duplicate charges.

• How to do it: Before submitting each new task, first import historical detection results into the deduplication repository (CSV/TXT format). After automatic deduplication, the platform only charges for numbers that are new or were not detected last time.
• Practical value: For regular refresh tasks with a large user base (e.g., 100,000+), you can save 30%-60% of your balance each time.

Combine Multiple Detection Types to Save Costs

If in one refresh task you need both active data and gender data or valid status, it is recommended to select multiple detection types in one task (e.g., TG Registered + TG Active + Gender Identification). KK-DATA performs batch detection on the same number, and the final result is billed as a “combined detection,” which is usually cheaper than submitting multiple separate tasks.

• Operation example: When creating a task, select “TG Valid,” “TG Active (choose 7 days),” and “TG Gender (avatar recognition)” in the detection type field. One task, three results.
• Advantages: Reduces the number of task submissions, shortens wait time (all detections run in parallel), and lowers overall cost.

Split Very Large Sources into Batches

A single task supports up to approximately 1 million numbers. If you need to process over 1 million numbers, it is recommended to split them into multiple tasks submitted in batches. You can segment by the first digit of the number or country code. This way, even if one batch fails, it does not affect others. Additionally, by submitting in batches, each batch can independently set different active windows for greater flexibility.

What to Watch Out for When Refreshing TG Active Data?

Although TG active data refresh is a routine operation, improper handling of the following details can affect final results or even cause losses.

1. Balance check: Before submitting a task, confirm that your balance is sufficient. The platform deducts fees after the task completes. If the balance is insufficient at the time of deduction, the task may be interrupted or fail. It is recommended to keep at least twice the balance needed for the current batch.
2. Number format: The uploaded number file must include the country code (e.g., China +86, USA +1), with one number per line. Incorrect formatting will cause the system to recognize the number as invalid, skipping detection and wasting quota.
3. Result fluctuation is normal: The same batch of numbers may show a 5%-15% fluctuation in activity ratio when refreshed at different times. This is normal because user behavior has randomness. If two consecutive refreshes show a huge difference (e.g., activity rate drops from 80% to 20%), check whether the source contains a large number of fake registrations or spam numbers.
4. Export format selection: When exporting results, CSV format includes all metadata (e.g., activity timestamp, country, TGID), suitable for subsequent data analysis and user segmentation; TXT format only retains numbers and detection results, suitable for direct import into bulk messaging tools.

Complete Steps for TG Active Data Refresh Using KK-DATA

Taking the KK-DATA console as an example, here are the practical steps from preparing data to exporting results to help you get started quickly.

Step 1: Prepare the Numbers to Be Refreshed (CSV/TXT)

Export the “TG Active” results from your previous successful screening task as a CSV or TXT file. The file should contain only the numbers you need to re-detect, one per line, in the format 8613800112233 (with country code; ”+” is optional but consistency is recommended). If you are starting from scratch with new number generation, first complete the “Global Number Generation” feature (free) and then perform screening.

Step 2: Create a Screening Task in the Console

1. Log in to the KK-DATA App Console.
2. Click “Create Task” and upload the number file prepared in Step 1.
3. In the detection type, select “TG Active,” and choose an active window (7 days, 15 days, or 30 days) based on your outreach rhythm. If you also need to detect gender or valid status, you can select them together. The platform will automatically combine billing.
4. In the “Data Deduplication” options, it is recommended to enable “Deduplicate from historical results” (if the option exists). If there is no separate deduplication option, first import historical data into the “Deduplication Repository” module before starting the task.
5. Click “Submit Task.” The system will display an estimated cost (based on current unit price and number count). Confirm and submit.

Step 3: Export the Refresh Results After Task Completion

After submission, the platform will asynchronously perform detection. You can obtain results through the following methods:

• Telegram notification: Bind your Telegram account (@kkdata_cc) when creating the task. You will receive real-time notifications upon completion.
• Console view: Log in to the console, find the task in “Task History,” and click “Results” for details.
• Data export: Choose export format (CSV recommended) and download the result file. Compare the “Last Online Time” field in the new results with the old results to see the activity status update directly.

After exporting, it is recommended to immediately import the new results into your deduplication repository or CRM system to prepare for the next refresh.

Frequently Asked Questions

Q: Can I still use the old data after a TG active data refresh?
A: You can keep the old data for historical comparison, but for outreach, priority should be given to the latest refreshed active data. Old data may include numbers that have become inactive. Continued use will reduce message delivery rates and may affect account health due to invalid sends.

Q: Is more frequent TG active data refresh always better?
A: No. The refresh frequency should be reasonably set based on your outreach rhythm and target users’ activity cycle. Refreshing multiple times daily will accelerate balance consumption, and active user status usually does not change significantly in a short time. Generally, keep the refresh cycle consistent with your outreach cycle, e.g., every 3 days or weekly.

Q: Why are my refreshed active data results very different from before?
A: This could be due to fluctuations in the target user group’s activity behavior (e.g., users offline during holidays, account bans) or network delays during detection. It is recommended to perform multiple detections in the same time period for comparison or check the source quality. If the difference between two consecutive results exceeds 20%, be wary of low-quality or fake accounts in the source.

Q: What is a reasonable re-screening cycle?
A: There is no uniform standard. If your user group is marketing or business-oriented (high activity, online daily), refresh every 1-2 weeks. If it is social-oriented (high activity fluctuation), refresh every 3-7 days. You can also A/B test different cycles to find the best value for your business by comparing final conversion rates.

Q: What if my number count exceeds the single task limit?
A: Split the number file into multiple batches and submit each batch with no more than 800,000 to 1 million entries. You can segment by the first digit of the number (0-9) or by country code. Note: Each batch task requires independent detection parameter settings and will be charged separately.

For further information, please visit the KK-DATA official website, refer to the documentation, or contact customer service at @kkdata_cc.