How to judge the data quality of US TG numbers? Full analysis of number segments, formats, repetition rates and freshness

When acquiring customers in batches, the data quality of the US TG number directly determines the conversion efficiency. Many teams spend a lot of money to purchase number lists, only to find that a large number of numbers cannot be activated on Telegram, have extremely low activity, and even cause users to complain about account suspension due to repeated contact. This article breaks down in detail how to judge the quality of American Telegram numbers from the four dimensions of number segment, format, repetition rate, and freshness, helping you avoid the trap of low-quality data and improve the effectiveness of tg followers and community operations.

Why data quality is the key to success or failure in customer acquisition?

Low-quality US TG numbers will bring about a series of chain problems:

• High Inefficiency: A large number of numbers are not registered with Telegram, and the detection budget is wasted.
• Account Banning Risk: Frequently sending messages to invalid or silent numbers may be easily judged as harassment by Telegram.
• Waste of budget: Duplicate numbers will be deducted on a per-item basis when screening numbers, making you pay more than you deserve.
• Data Distortion: Activity and gender proportion based on low-quality number statistics have no reference value, and subsequent decisions will be off-center.

To judge the quality of US TG numbers, we mainly look at four dimensions: number segment (operator affiliation), format (country code and digits), repetition rate (within and across lists), and freshness (number generation or collection time). Only through control one by one can we ensure that every penny is spent on reachable real users.

What is the standard format of US TG numbers? How to quickly identify invalid numbers?

The standard format of US Telegram numbers is: +1 followed by 10 digits. The complete number consists of +1 (country code) and 10 digits of the local number, with a total length of 11 digits. For example: +1 (212) 555-1234 should be cleaned to +12125551234.

Country code and digit verification

• Country code: The United States is +1 (this code is shared by Canada and some Caribbean regions, but Telegram activity varies greatly, so it is usually marked separately).
• Number of digits: The local number must be 10 digits. After removing all non-numeric characters (spaces, brackets, and dashes), the total length should be 11 digits (including +1).
• Quick judgment: If the number does not start with +1, or the total number of digits is not equal to 11, it is most likely not a standard US TG number.

正确示例：+12125551234
错误示例：
- +86...（中国号码混入）
- +1 212-555-1234（含横线，需清洗）
- +1212555123（少一位）
- 2125551234（缺少+1）

Common format problems and cleaning methods

Common format issues when users import CSV/Excel data:

Problem Types	Examples	Cleaning Methods
Contains brackets/hyphens/spaces	+1 (212) 555-1234	Regularly delete non-numeric characters, leaving only + and numbers
Missing country code	2125551234	Add +1 in front
Mix in international numbers	+8613912345678	Filter by country, only keep numbers starting with +1
Multiple digits/small digits	+121255512345	Truncate the first 11 digits or discard them

It is recommended to clean the format of the number list before submitting the number screening task. If the source of the number pool is confusing, you can directly use KK-DATA’s [Global Number Generation Module] (https://docs.kkdata.cc/) to generate numbers in a standard format based on the US number segment to avoid format errors from the source.

How to judge the reliability of a US TG number based on the number segment?

The number segment (NPA-NXX) corresponds to the operator to which the number belongs. The numbers of mainstream US operators (Verizon, AT&T, T-Mobile) usually come from real-name users and are highly active; while some virtual operators (such as Google Voice, Ting) or fixed phone number segments may have low Telegram registration rates or be used for marketing harassment, and the quality varies.

Distribution of mainstream number segments in the United States

• Traditional Carriers: Verizon (NXX range such as 212-xxx, 917-xxx, etc.), AT&T (310-xxx, 512-xxx, etc.), T-Mobile (410-xxx, 610-xxx, etc.). These number segments have a large user base and high activity.
• Virtual Operator: Google Voice (the numbers are mostly from old number ranges, such as 415-xxx, 213-xxx, etc.). Some users only use it for one-time verification, and the activity is unstable.
• Landline number: If you have a landline number in your residence (usually a local number), the Telegram registration rate is extremely low and is not recommended for customer acquisition.

How to use number segment for preliminary screening?

If you have a list of U.S. numbers, you can count the number distribution of each number segment based on the first 6 digits (NPA-NXX). If the proportion of a certain number segment is too high (for example, more than 20%), you may need to question whether it is a batch-generated or virtual operator number segment. At this point, you can:

• Use KK-DATA’s global number segment generation function to generate numbers based on mainstream operator number segments and obtain the first round of quality filtered lists.
• For existing lists, use number segment analysis to eliminate obviously inefficient number segments (such as fixed phone number segments) before screening numbers.

Duplication rate control: Why does your US TG number always contain duplicate data?

The duplication rate in large batch number lists is often as high as 5%–15%. For example, two lists purchased from different sources may contain a large number of cross numbers, or the same number may be double counted due to different formats (+12125551234 starting with +1 vs. 2125551234 without +1). The dangers of duplicate numbers:

• Double deduction: Screen numbers are billed on a per-item basis. Duplicate numbers will be detected multiple times, wasting balance.
• User disgust: Repeatedly sending content to the same number will easily be reported as spam.
• Statistical deviation: Indicators such as activity rate and gender proportion are distorted due to repeated data.

How to solve the duplication rate problem?

1. Remove duplicates before submission: Use scripts or tools to remove duplicates from the number list (pay attention to the unified format before removing duplicates).
2. Cross-task duplication removal: If number screening tasks are submitted multiple times, numbers that already have test results should not be tested again. KK-DATA provides the data deduplication warehouse function, which automatically records all detected numbers and automatically skips duplicate items when submitting new tasks to avoid repeated deductions.

Data freshness: How to tell if the US Cable number you got is “outdated”?

“Data freshness” refers to the probability that the number is still in use and active in the recent period. Telegram users will log out, change their numbers, or not log in for a long time. The longer it takes for numbers to be generated or collected, the more obvious the activity rate will drop.

Three key points to judge freshness

• Generation/Collection Time: If the number source comes from a year ago, it is likely that a large number of numbers have expired.
• Active window setting: Set active windows such as “last 7 days” and “last 30 days” in the number screening tool to filter out high-quality numbers that have been online recently.
• REGULAR UPDATES: Don’t rely on one-time purchase of number lists. It is recommended to update the number source weekly or monthly and use the number screening tool to recheck the activity.

Practical suggestions

• For each batch number, record the task submission timestamp as a reference for freshness.
• In KK-DATA’s tg activity detection, select the “last 7 days” activity window to retain the most active user groups.
• Regularly generate new numbers using the same number range, compare the activity rate with old numbers, and dynamically adjust the number selection strategy.

From number segment to activity level: How to use the number screening tool to completely verify the quality of US TG numbers?

The theoretical judgment of the aforementioned four dimensions is implemented into a practical process. Taking the KK-DATA platform as an example, the complete quality inspection steps are demonstrated.

Step 1: Number segment generation and format preprocessing

• Enter KK-DATA Console and select the “Global Number Generation” module.
• Select “United States” for the country, and you can specify it by number segment (such as Verizon number segment) to generate a number list in a standard format (when TG filters to use US numbers, it is recommended to limit it to telecom operator number segments).
• If you already have your own number pool, directly upload the CSV or TXT file, and the platform will automatically perform format verification and mark abnormal numbers.

Step 2: Submit the screening task - tg activation and tg active detection

• Create a new task in the workbench, select the platform “Telegram” and the region “United States”.
• Check the detection type: tg activated (confirm whether the number is registered with Telegram), tg active (optional window of last 7 days/last 30 days).
• If you need targeted customer acquisition, you can check Gender Detection (output gender and age fields). Note that the age field is for reference only.
• Before submitting the task, the platform displays the estimated cost (see the real-time price on the console for details), and submit it after confirmation.

Step 3: Interpret export results and gender data

• After the task is completed, download the CSV export file in the historical tasks.
• Fields include: tg开通 (1/0), tg活跃 (1/0), 性别 (male/female/unknown), 年龄 (numeric value or interval), etc.
• When using the age field to filter people around 30 years old, please note that the results are not ID-level accurate and are only used as a reference for user portraits. The gender field can be used to target male/female customers.

Summary of best practices for US TG numbers and data quality

Key Actions	Practice	Tools/Methods
Number segment selection	Prioritize traditional operator number segments	Global number segment generation module
Format verification	Unify to +1+10 digits, clean non-numeric characters	Script or platform built-in verification
Repetition rate control	Cross-task automatic deduplication	Data deduplication warehouse
Freshness maintenance	Update the account source every month and set the active window	tg active detection (last 7 days/30 days)
Complete quality inspection	Activate→Active→Gender/Age Export	Complete the screening task in one step

Establish a systematic data quality management process: ** number segment generation → format cleaning → deduplication → screen number detection → directional export**. Only by controlling every aspect well can the conversion rate of US TG numbers be steadily improved.

FAQ

Q: What are the main number segments of American TG numbers? Which number segments have higher user activity?
Answer: Commonly used number segments in the United States come from mainstream operators such as Verizon, AT&T, and T-Mobile, as well as virtual operators such as Google Voice and Ting. Usually numbers from traditional carriers have higher user activity, but this is not guaranteed. It is recommended to use the number screening platform to conduct TG activity detection on the number to obtain real activity data.

Q: I have a batch of approximately 20,000 US numbers purchased from a third party, how do I quickly determine if they are worth investing in the screening budget?
Answer: First randomly select a small batch (such as 200 numbers) for TG activation testing. If the opening rate is lower than 60%, it is recommended to clean or abandon the batch first. At the same time, use number segment analysis to check whether virtual operators or fixed phone number segments are the main ones. The activity rate of such number segments is generally low.

Q: In KK-DATA, after submitting the US TG number screening task, how long will it take for the results to be available?
Answer: The time depends on the number of tasks and platform load. Generally, the activation detection is completed within a few minutes for tasks with less than 1 million items, and the active detection takes a little longer. You can check the progress on the task details page for the specific duration, and you will be notified through Telegram after completion (need to bind the notification robot).

Q: Is the data deduplication warehouse shared among all tasks? Will there be any additional charges?
Answer: Yes, the data deduplication warehouse is a global function, and all tasks will be automatically compared and deduplicated when submitted. There is no additional charge for this feature, but the deduplication operation itself does not consume your balance (only when the number is actually detected). See the console instructions for specific rules.

Q: How accurate is the gender/age data of US TG numbers? Can it be used for precision marketing?
Answer: The gender detection model is based on user public information and behavioral inference, and has a high accuracy (usually more than 80%), but it is not 100%. The age field is an estimate and can be used as a reference for crowd screening. It is not suitable for precise targeting at the ID card level. It is recommended to make a comprehensive judgment based on other dimensions (such as activity, number segment).

---

👉 Log in to KK-DATA Console to start screening numbers, or contact customer service https://t.me/kkdata_robot to get help. For more technical documentation, please visit https://docs.kkdata.cc/.