How to judge the quality of US tg data? Comprehensive analysis from number segment, format, repetition rate and freshness

When overseas marketing teams purchase or build their own U.S. TG data, the most common pitfall is that “it looks like a lot of data, but only a few are actually usable.” The quality of US Telegram data (i.e., the set of Telegram user numbers in the +1 segment) directly determines the private message arrival rate, community invitation success rate, and final conversion cost. This article provides a set of implementable quality assessment methods and practical procedures from the four dimensions of number segment authenticity, format specification, repetition rate control and active freshness to help you spend less money when screening US TG data.

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What is US tg data? Why does data quality determine the success or failure of customer acquisition?

The US tg data refers to a collection of Telegram user phone numbers located in the United States** and is usually available for download or import in CSV/TXT format. The core uses of this data include: adding contacts in batches, inviting groups, sending private messages, community operations and other marketing actions. If the data quality is poor - such as a large number of invalid numbers, high duplication rates or long periods of inactivity - it can lead to:

• Waste of testing costs (fees will also be deducted for each invalid test);
• Increased account risk (frequently adding invalid numbers may trigger risk control);
• The marketing effect will be reduced to zero (sending it to inactive users is equivalent to nothing).

Therefore, before investing money, the data must be physically examined from the following four dimensions.

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How to judge the authenticity of US TG data from the number segment?

Basic rules of North American number segments and mainstream operator fields

U.S. phone numbers follow the North American Numbering Plan (NANP) and are in the format +1 NXX NXX-XXXX, where NXX is the area code (the first three digits). Common real number segments are:

Area code (NXX)	Examples of corresponding regions/operators
212	New York City (Verizon/AT&T)
310	Los Angeles (T-Mobile/Sprint)
415	San Francisco (AT&T/Verizon)
214	Dallas (AT&T)
305	Miami (T-Mobile)

Judgment Skills:

• In a large batch of data, if the first three digits are concentrated in a few number segments (such as all 555, 456, etc.), it is likely to be a test number segment or a virtual number.
• Pay attention to excluding all 0/all 1 and other non-real allocated number segments (such as +1 000-xxx-xxxx).
• Some virtual operators (such as Google Voice, TextNow) also have real number segments, but the activity is usually lower than that of physical operator numbers.

How to use the number generation tool to verify the validity of number segments in batches

Manually checking the number range is unrealistic. A more efficient approach is to first use a number generation tool to generate samples according to the target number range, and then use the number screening platform to detect the activation rate**. For example, in the global number generation module of KK-DATA, select “United States” and specify a first three-digit number segment (such as 212), generate 500-1000 numbers, and then submit them for activation testing. If the activation rate is lower than 5%, it means that the quality of the number segment itself is questionable, and large quantities of purchases are not recommended.

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Number format specification - the basic threshold of US TG data

Common types of format errors and cleaning methods

Regardless of the data source, the first step must be in a unified format of E.164 standard: +1XXXXXXXXXX. Typical errors include:

• Lack of international prefix code (such as writing 2125551234 directly);
• Contains spaces, brackets, and dashes (such as (212) 555-1234);
• Insufficient or multiple digits (such as 212555123, +121255512345);
• Mix in non-numeric characters (eg +1 212-555-1234 ext. 0).

Cleaning method: Use regular replacement to remove non-numeric characters, and then complete the +1 prefix. For example, convert 212-555-1234 to +12125551234. If the amount of data is large, it is recommended to use programming scripts or automatically repair it through the format detection function of the screening platform.

Tool ideas for batch verification number format

• Use Excel formula =IF(LEN(A1)=10,"+1"&A1,"") to quickly complete;
• Use online CSV cleaning tools to remove blank lines and illegal characters;
• Before submitting the number screening task, upload a small batch of tests to the KK-DATA console. The system will automatically mark the numbers with incorrect formats (no fees will be charged).

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Repetition rate: the invisible consumption of efficient screening of US tg data

Typical sources of repeat rates: multiple purchases, mixed use by different sellers

Many teams purchase US TG data in batches from multiple channels, resulting in number duplication rates as high as 30%–50%. Duplicate numbers mean that the same number is tested and deducted multiple times, but only one valid result is produced. This not only wastes budget, but also creates data redundancy and interferes with marketing prioritization.

How to use data deduplication warehouse to achieve cross-task deduplication

KK-DATA provides a built-in data deduplication warehouse, which is based on number normalization matching and supports cross-task deduplication. Operation process:

1. Upload the number list (after unified format) to the deduplication warehouse;
2. The system automatically compares the numbers in all historical tasks and marks duplicates;
3. Select “Keep only unique numbers” to generate a new list;
4. Submit the unique list to the screening task.

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Data freshness - how to determine whether US tg users are still active?

The difference between active detection and tg activation/logout

• Activation detection: Only determine whether the number has registered a Telegram account (regardless of the last login time).
• Activity Detection: Further determine whether the number has logged in within the specified time window (such as 7 days/30 days/90 days).

For example, if a number was registered two years ago and has not been logged in again, the activation test will show “Active”, but the active test (7-day window) will show “Inactive”. For marketing campaigns, prioritizing numbers active within 7 or 30 days works best.

How to specify the active window to match the marketing time point

In the Telegram screening task of KK-DATA, you can select “Activity Detection” and set the time window. Suggestions:

• Instant push type (such as flash sale) → Select active within 7 days;
• Community Invitation/Long-term Incubation → Choose to be active within 30 days;
• Supplementary Expansion → Choose to be active within 90 days.

Note: The deduction for active detection is usually higher than that for active detection, but the ROI is higher. For specific fees, please refer to Console Real-time Price.

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Practical process of American tg data screening: from generation to export

The following is a complete pipeline using KK-DATA as an example. Each step is controlled for the above quality dimensions:

1. Number generation (free) Select the country “United States” and you can specify the first three number segments or generate them randomly to quickly obtain the North American number pool.

2. Format Cleaning Convert generated numbers or imported external data to E.164 format, and automatically identify format problems when uploading to the console.

3. Remove duplicates Submit it to the “Data Deduplication Warehouse” to merge historical tasks and remove duplicate numbers.

4. Screen number Select the detection type (activated/active/gender, etc.), set the active window (such as 30 days), and submit the task. After the task is completed, the system will automatically notify you and deduct fees based on the number of tests.

5. Export The filtering results can be exported to CSV or TXT, including fields such as tgid, active status, gender, etc.

Through this process, you can ensure the authenticity of the number segment, standard format, low repetition rate and activity of the US TG data from the source, ensuring that every piece of exported data is a reachable marketing resource.

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Common mistakes and pitfall avoidance guide: Things to note when purchasing/using US tg data

Common Mistakes	Consequences	Suggestions
Only look at activation, not activity	A large number of numbers have been abandoned and marketing is invalid	Be sure to enable activity detection and specify the window
Ignore format cleaning and submit directly	Invalid detection fees will be deducted, and the results are inaccurate	Convert to E.164 format before uploading
Repeated submission of the same number	Repeated deductions, waste of budget	Use deduplication warehouses to merge and then filter
Believe in low-priced data sources	Fake number segments (such as using test number segments), and the activation rate is extremely low	Use samples to test the activation rate first, and give up if it is less than 15%
Don’t pay attention to the distribution of number segments	The data is concentrated in a few areas and has narrow coverage	Check the distribution of the top three number segments and spread them out as much as possible

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FAQ

**Q: What is the criterion for “active” in the US TG data? ** Answer: Activity detection is based on whether the number has online behavior within the specified time window. Usually the platform will provide optional windows (such as 7 days/30 days/90 days). You need to pay attention to how the active field is defined to avoid confusion with “activated” (only registered but not logged in for a long time).

**Q: How to judge whether the number segment of a US TG data is of good quality? ** Answer: It can be judged by checking whether the first three digits of the number match the real US operator allocation table, whether there are a large number of repeated bits (such as invalid number segments such as all 0s and all 1s), and whether the number segment coverage is concentrated in a few first three digits. It is recommended to use a small number of samples to test the activation first.

**Q: At what level must the repetition rate be controlled to be considered qualified? ** Answer: For a single purchase of U.S. TG data, the internal duplication rate should be less than 5%; if purchased from multiple channels, it is recommended to perform cross-task deduplication first and reduce the overall duplication rate to less than 10% before submitting the screening task to save budget.

**Q: What detection types are supported when filtering US tg data through KK-DATA? ** Answer: Supports activation detection, activity detection (window can be specified), gender recognition (including age, race and other fields), tgid export, etc. For specific detection types and unit prices, please refer to the real-time price of the console. Currently, it also supports multiple platforms such as Telegram, WhatsApp, Line, and Zalo.

**Q: Can US virtual operator numbers (such as Google Voice) be effectively screened? ** Answer: Some virtual operator numbers can also be registered and used on Telegram, but their activity may be low. KK-DATA’s screening number is based on the number itself and does not distinguish between physical operators and virtual operators. The detection results are based on the status returned by the platform.

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Want to further shorten the trial and error cycle? Try it now: 👉 Log in to the console to start screening numbers to start generating US number segments and batch screening numbers. If you have any questions about data quality assessment, you can contact customer service https://t.me/kkdata_robot in both directions for one-on-one guidance. See https://docs.kkdata.cc/ for more documentation.