Full Analysis of Telegram Activity Detection Speed: How Long Does It Take to Batch Screen Millions of Numbers?

In the daily work of overseas user acquisition, batch detecting the activity of Telegram numbers is a key step in screening high-value users. However, many people lack a clear concept of TG activity detection speed: submitting 100,000, 500,000, or even 1 million numbers—how long do you actually have to wait? What factors affect the speed? How can you plan so it doesn’t slow down your overall acquisition pace? This article breaks down processing times from a measurement perspective, providing reference estimates and optimization strategies to help you use batch activity detection more efficiently.

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Processing Time Range for a Single TG Activity Detection Task

The speed of TG activity detection is not a fixed value; it is jointly determined by the total number of numbers, the activity window setting, the quality of the numbers, and the real-time load on the platform. Based on observations in typical scenarios:

• Small batches (up to 10,000 numbers): several minutes to under 30 minutes.
• Medium batches (around 100,000 numbers): typically 30 minutes to 2 hours.
• Large batches (million-level numbers): usually within a few hours, rarely exceeding 12 hours.

The platform supports a maximum of approximately 1 million numbers per single task. If you exceed 1 million, you need to split the numbers into multiple tasks. The “processing time” here refers to the entire period from successful task submission to when results can be exported, excluding number generation or pre-screening stages.

Single Batch vs. Multiple Batches: Where Does the Speed Difference Come From?

Submitting 1 million numbers in one go vs. splitting into two tasks of 500,000 each—the overall processing time is not exactly the same. This is because the platform processes tasks in a queue. Splitting into multiple batches means each task queues separately, but the parallelism is limited. In practice:

• Single batch of 1 million: waits in the queue once, processing time is relatively concentrated; total time ≈ queue time + processing time.
• Split into 2 × 500,000: the two tasks can be submitted consecutively, but the platform does not speed up processing by running them in parallel. The second task still needs to wait for the first to finish or be interleaved. The final total time may be close to or even slightly longer than a single batch. The advantage is that you can obtain results in stages, which is suitable for scenarios requiring batch import.

If your number count exceeds 1 million, you must split it; if within 500,000, it is recommended to keep a single batch to reduce operational complexity.

Estimated Time Formula and Practical Examples

A simple estimation logic: Total estimated time ≈ base time per 10,000 numbers × total numbers (in 10,000s) + queue waiting time (usually 1–5 minutes).

Reference values (activity window set to 15 days, numbers are pre-screened valid numbers):

Task Size	Estimated Time Range	Typical Scenario
10,000 numbers	5–15 minutes	Small team test or daily incremental
100,000 numbers	40 minutes–1.5 hours	Medium community batch screening
1,000,000 numbers	2–6 hours	Full activity detection of a large number pool

Note: These are for reference only. The actual speed depends on the progress displayed in the console task details page. Low-cost high-activity detection (e.g., 7-day activity) may be slightly faster, while 30-day activity or detection including gender identification may be slightly slower.

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3 Core Factors Affecting TG Activity Detection Speed

Understanding the reasons behind the speed helps you better control task time.

Activity Window Length and Detection Depth

The detection logic for “7-day activity,” “15-day activity,” and “30-day activity” differs: the longer the window, the greater the time span the backend needs to query, increasing data matching costs. Generally:

• 7-day activity is 10%–20% faster than 30-day activity.
• Activity detection adds an extra verification step (judging the last online time) compared to a simple “TG registration check,” so the overall time is 1.5 to 2 times that of a registration check.
• If gender identification (avatar recognition) is also selected, it adds an additional image analysis step, further reducing speed.

Impact of Number Source Quality on Speed

The source of numbers directly affects the valid rate (the proportion of numbers that actually exist and are detectable):

• Random generation or global number segment generation: lower valid rate; many numbers are non-existent or unregistered. When the detection process encounters invalid numbers, it needs to skip them quickly. Although each individual check is short, the overall task may slow down slightly due to frequent state switches.
• Custom CSV import: if your CSV contains high-quality numbers (e.g., from your own previous user data), the valid rate is high, the detection flow is more continuous, and the speed is relatively faster.
• Pre-screened numbers: first run a “TG registration check” to remove invalid numbers, then submit activity detection only for valid numbers. This reduces the total task size and significantly improves speed (see the cost-effective strategy below).

Platform Concurrency and Task Scheduling Strategy

The platform processes tasks using a queue; tasks submitted by different users are queued in order of submission. Even if multiple tasks from the same user are submitted simultaneously, they are not truly processed in parallel but follow the queue order. Therefore:

• Avoid submitting large batches during global weekday peak hours (e.g., UTC+8 8–11 PM), when the queue may be longer.
• Small batch tasks have shorter queue times; large batch tasks may also have longer queue times.

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How to Improve the Processing Efficiency of Batch Activity Detection?

The following operations are speed optimization measures that users can actively control. It is recommended to combine them as needed.

1. Pre-screen with “Empty Number/Carrier Detection” or “TG Registration Check” first
   This is the most cost-effective approach. Spend a small amount to remove invalid numbers first, then submit activity detection only for valid numbers. The total cost and total time are usually lower than directly detecting all numbers, because activity detection is priced higher than registration checks, and activity detection on invalid numbers is wasted entirely.

2. Split very large tasks into several smaller batches and submit different detection types in parallel
   For example, split 500,000 numbers into 3 tasks: one for 7-day activity, one for 15-day activity, and one for 30-day activity. Of course, this depends on business needs, but you can interleave queue times.

3. Schedule task submission wisely
   Avoid platform peak hours (usually UTC+8 8–11 PM). Prefer early morning or morning hours when the queue is shorter and processing is faster.

4. Use the platform’s “Data Deduplication Repository” feature
   If you repeatedly test the same number pool (e.g., first registration check, then activity detection, then export), the dedup repository can automatically identify numbers that have already been tested, avoiding duplicate charges and duplicate checks. This saves significant time, especially when re-testing after batch import.

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Real-World Scenario: Full Time Estimate from Number Generation to Activity Export

Suppose an overseas acquisition team needs to obtain 100,000 active TG users, starting from scratch:

1. Global number generation: Use the platform to generate 300,000 random numbers (covering target countries). Time: about 2 minutes (generation is free).
2. TG registration check: Submit these 300,000 numbers for registration check. Time: about 20–30 minutes, filtering out 150,000 valid numbers.
3. TG activity detection: Submit the 150,000 valid numbers for 15-day activity detection. Time: about 1–2 hours, filtering out 80,000 active numbers.
4. Result export: Export as CSV, takes 1 minute.

Total time: approximately 2–3 hours, with activity detection taking the longest. If you skip pre-screening and directly run activity detection on 300,000 numbers, the time could reach 3–5 hours, and the cost would be higher.

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TG Activity Detection Speed vs. Other Detection Types

Detection Type	Average Speed (Relative)	Explanation
TG Registration Check	Fastest	Only checks whether the number is registered on Telegram; no deep queries.
TG Activity Detection	Medium to slow	Adds a query for last online time; takes about 1.5–2 times longer than registration check.
WhatsApp Validity Check	Medium	Similar speed to TG registration check, but limited by WhatsApp API.
iMessage Detection	Slower	Depends on Apple server response; stability is lower.
Empty Number/Carrier Check	Medium	Some carrier queries have higher latency.

Horizontally, activity detection is the “heaviest” step in the number screening process. Pre-screening can minimize its bottleneck impact on the overall workflow.

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Frequently Asked Questions

Q: How long does it usually take to run TG activity detection on 10,000 numbers?
A: Typically from several minutes to under 30 minutes. It is affected by the activity window setting, platform real-time load, and number quality. Refer to the actual progress on the console task details page.

Q: Will an activity detection task for 1 million numbers run for a whole day?
A: Million-level tasks usually take a few hours, rarely exceeding 12 hours. If it’s too slow, contact customer service @kkdata_cc to inquire about platform status or task-level optimization.

Q: Can I cancel a submitted task? Will the balance be refunded?
A: For tasks already submitted but not yet started, you can contact customer service to attempt cancellation; numbers already processed are charged per piece, and unprocessed parts are not charged. For detailed refund rules, please refer to Platform Documentation.

Q: Can I first test 100 numbers to see the speed?
A: Yes. The platform supports any number of submissions (no minimum task size limit). It is recommended to first use a small test task to observe actual time and result quality before planning large batches.

Q: Will I be notified after the activity detection task is completed?
A: Yes. You can enable Telegram notification for task completion. You can bind your Telegram account in the console and turn on push notifications.

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Further Reading: To learn more about the difference between TG activity detection and registration check, and cost-benefit analysis, please refer to KK-DATA Documentation. Log in to Application Console to submit a test task immediately. If you have any suggestions for task optimization, feel free to contact customer service @kkdata_cc.