Complete Guide to Million-Level TG Number Screening: How to Efficiently Split, Submit, and Process 1 Million Telegram Number Filters

In overseas marketing, when you have a raw number list of hundreds of thousands or even millions and want to scale customer acquisition through Telegram friend adding, group importing, or private message promotions, the first step is number screening — verifying which numbers are registered on Telegram, which are active, and even determining gender. However, directly submitting million-level tasks often encounters issues like timeout interruptions, wasted balance, and unparseable result files. This article addresses such large-scale TG screening scenarios, from failure cause analysis to splitting strategies, task settings, and result processing, providing a practical end-to-end guide. It also compares the suitability of mainstream tools (including 007data, thdata, etc.) to help you run million-level Telegram screening tasks smoothly in one go.

Why Focus on Million-Level TG Screening? — Typical Scenarios and Pain Points of Large-Scale Screening

Teams that operate Telegram communities in bulk frequently encounter the following needs:

• Batch friend adding: From 1 million global numbers obtained from third-party channels, quickly identify those that have registered Telegram, then layer them by activity level for friend addition.
• Large-scale community import: Import all phone numbers from existing user data into Telegram groups, but many numbers may not be registered, leading to low join rates and wasted invitation quotas.
• Cleaning historical number databases: Millions of numbers accumulated over years, most of which are invalid, need to be screened in one go for valid numbers and deduplication.

When directly submitting a 1 million-task to traditional screening tools (such as 007data, thdata), common failure reasons include:

• Insufficient single task limit: Some tools support only a maximum of 50,000 to 100,000 per task; exceeding that results in rejection or automatic truncation.
• Long queue times for tasks: Million-level tasks take a long time; queue congestion or server timeout causes the task to fail midway with no resume mechanism, rendering previously screened portions useless.
• Pre-deducted balance trial and error: Some platforms require purchasing package bundles in advance; tasks exceeding the bundle require additional purchases, making costs uncontrollable.
• Result file too large: Exporting millions of rows at once can make CSV files exceed 100MB, causing tools to fail to parse or download to time out.

These pain points give rise to the methodology of “splitting + batch submission + merging and deduplication”. A platform with a complete pipeline of Generation → Screening → Deduplication (such as KK-DATA) can fundamentally reduce the failure rate of large-scale tasks.

Why the “Generation → Screening → Deduplication” Pipeline is Crucial for Large-Scale Tasks

• Global Number Generation (Free): If you lack a raw number library, you can first use KK-DATA’s Global Number Generation feature to randomly generate numbers for 240+ countries (free) as baseline data.
• Screening Module: Submit the generated numbers directly for screening, charged per number, pay as you go.
• Data Deduplication Warehouse: Merge results from multiple tasks into the deduplication warehouse, which automatically removes duplicate numbers to avoid wasting balance on repeated screening.

This pipeline ensures cost control and data cleanliness at every step, without manual concatenation.

Three-Step Splitting Strategy for Million-Level TG Screening Tasks

Regardless of the tool used, splitting is the first principle for ensuring success in million-level tasks. Using KK-DATA as an example (single task supports up to about 1 million numbers), the following splitting strategies are recommended:

Splitting Dimension	Recommended Practice	Description
By Country/Region	Group global numbers by country and submit each country as a separate task (e.g., US 500k, Indonesia 300k).	Screening speed depends on the target platform’s server response; separating allows parallel execution without blocking each other.
By Number Prefix	If numbers are non-consecutive, group by prefix (e.g., +86138, +86139) with about 100k–200k per group.	Follows the distribution pattern of number operators, making it easy to locate problematic batches during subsequent screening anomalies.
By Equal Parts	Simplest approach: split 1 million into 5 equal parts (200k each) and batch import via the console.	Suitable for mixed number pools without clear classification.

Operation Tip: The KK-DATA console supports “batch new task creation” — just prepare multiple CSV files (each file corresponds to one split), select all files at once, and the system will automatically queue them for execution. Each task shows its own progress independently without interference.

Key Settings When Submitting Tasks: Detection Type and Cost Estimation

In million-level tasks, the choice of detection type directly affects total cost. Common options:

• Check Registration Only (TG registered): Only checks if the number is registered on Telegram, lowest cost.
• Registration + Activity: Determines whether the account has been online in the last 7/15/30 days in addition to registration.
• Registration + Activity + Gender: Additionally identifies gender via avatar recognition, highest cost.

Best Practice: First run a small sample of 10k–20k numbers with “Check Registration Only” to evaluate number quality (i.e., registration rate). If the registration rate is below 30%, the pool is poor and can be abandoned or re-cleaned; if above 50%, proceed with the remaining volume in full. Never blindly run a million-level “Activity + Gender” directly, as more invalid numbers waste more detection fees.

Result Processing During and After Task Execution

Real-Time Monitoring and Notifications

• Telegram Bot Notification: Check the “Task Completion Notification” option when submitting. Once screening is done, a push will be sent to the bound Telegram account, including the number of valid/active numbers.
• Console Progress: Each task displays the number processed, remaining, and estimated remaining time, viewable at any time.

Exporting Results

After completion, results are exported in CSV or TXT format, with each line containing the following fields (depending on the selected detection type):

• Whether TG is registered
• Days since last activity
• Gender (only when gender recognition is selected)
• TGID (optional; can be used directly for Telegram API operations after export)

How to Merge Multiple Batch Results into a Final Clean Number Library?

1. Export the valid number results from all tasks to the same directory.
2. Use KK-DATA’s Data Deduplication Warehouse: Import multiple CSV files into a deduplication task; the system automatically identifies and removes duplicate numbers (keeping only one copy), generating a unique list of valid/active numbers.
3. Finally, export the deduplicated numbers to form a high-quality clean number library, avoiding repeated contact during subsequent friend adding or private messaging.

How to Use the Exported Numbers?

• Import into Telegram friend-adding tools: Import the list of active numbers in batches according to daily limits into private tools, with random delays and message templates to avoid triggering Telegram risk controls.
• Private message broadcasting: Prioritize numbers “active in the last 7 days” — these users have the highest response rates. Users active for 30 consecutive days may already be immune to ads, so reduce contact frequency.

Million-Level TG Screening Tool Comparison: KK-DATA vs. Other Solutions

Below is an objective comparison from several key dimensions of common Telegram screening tools on the market (007data, thdata, etc., collectively referred to as “other solutions”). All prices are subject to real-time rates on each platform’s console; this article does not fabricate specific numbers.

Dimension	KK-DATA	Other Solutions (e.g., 007data, thdata)
Single task limit	~1 million numbers	Typically 50k–200k; exceeding requires batching or additional payment
Pricing model	Pay-per-number, no subscription packages, pay as you go	Package bundles (100k package/1M package); exceeding requires additional purchase
Deduplication capability	Built-in data deduplication warehouse, automatic cross-task deduplication	Most lack deduplication; manual Excel handling required
Export format	CSV, TXT with custom fields	Mainly CSV, few support TXT
Task notification	Telegram Bot push for completion	Some have email notifications, most do not push
Global number generation	Free generation for 240+ countries	A few offer paid generation services

Conclusion Summary: For million-level TG screening, the pay-per-number model is clearly superior to package bundles because large-scale task costs scale linearly with usage, avoiding waste. Additionally, tools with data deduplication warehouse and task notifications significantly reduce repetitive work and waiting time. KK-DATA has been optimized for elastic needs in these dimensions, making it suitable for overseas teams with fluctuating task volumes.

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Frequently Asked Questions

Q: How much does screening 1 million Telegram numbers cost?
A: The cost depends on the selected detection type (registration only / registration+activity / registration+activity+gender) and the platform’s unit price. Using KK-DATA as an example, the console displays an estimated cost before submission. For exact pricing, refer to the console’s real-time rates. It’s recommended to test with a 10k sample first to estimate per-number cost.

Q: Between 007data and KK-DATA, which is better for million-level screening?
A: Both support Telegram screening, but KK-DATA uses a pay-per-number model with no subscription packages, suitable for scenarios with fluctuating single-task volumes; 007data typically requires purchasing package bundles. If a million-level task exceeds the bundle, additional packages may be needed. Please check each platform’s official website for specific billing. Additionally, KK-DATA provides a data deduplication warehouse for cross-task deduplication to avoid repeated charges.

Q: How many numbers can a single task handle? Can I submit 1 million at once?
A: KK-DATA’s single task supports up to ~1 million numbers. However, for task stability and progress observability, it is recommended to split 1 million into multiple tasks (e.g., 100k–200k each) and submit in batches. The console supports batch new task creation, allowing you to import multiple files at once and automatically queue them.

Q: After screening, how do I know which numbers are active?
A: When submitting the task, select the detection types “TG valid” and “TG active (specified days)”. The exported CSV file will include an “activity” field. KK-DATA supports custom activity windows like 7/15/30 days, allowing you to align with your community posting pace.

Q: Can I directly send private messages to screened numbers? What should I be careful about?
A: Yes, but it is recommended to combine random delays and batch delivery. High-frequency contact with millions of numbers at once can easily trigger Telegram’s account banning mechanism. It is advisable to layer results by activity level, prioritizing private messages to numbers “active in the last 7 days,” and control daily sending volume.

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Experience Million-Level TG Screening Now: Log in to KK-DATA Console to generate global numbers for free and submit test tasks. For batch submission advice, contact customer service @kkdata_cc for technical support. For more operational details, refer to the Documentation.