Why do we need to run a small sample test first for active TG screening in the United States? — A practical guide to using data to decide whether to expand your mission

For a team that acquires customers for Telegram in the United States, whether it is community operations, private message promotion or cross-border e-commerce marketing, the first step is often to screen out a batch of US active TG numbers. But many people directly submit hundreds of thousands of tasks, only to see the results when they come back: the activity rate is less than 10%, and the balance of tens of thousands of dollars has been wasted. The cost of screening numbers for US Active TG is concentrated in the testing process - number generation is free, but a fee will be deducted for each test. The correct approach is to run a small sample test first, use hundreds to thousands of data to evaluate the number quality, and then decide whether to expand. This article takes you through the complete process of “small sample testing → result analysis → expanded decision-making” from concept to practical operation.

What is the US active TG screen number? Why do we need to understand this basic concept first?

On the KK-DATA platform, “US active tg” is a clearly defined detection type: targeting Telegram numbers in the US region (country code + 1), detecting whether they have had any active behavior (such as sending and receiving messages, going online, etc.) within the specified time window. This is different from the simple “tg activation detection” - activation only verifies whether the account exists, while active means that the account has indeed been used recently.

The difference between American TG active number and TG activated number

Detection Type	Meaning	Customer Acquisition Value
tg activation	Account exists (Telegram registered)	Low: many zombie accounts and abandoned accounts
tg active	The account is active within the specified window	High: It may still be used and there is a chance of reaching it

For example: If you screen 100,000 US numbers, maybe 50,000 of them are registration numbers from a few years ago and are no longer active. Although the number of active TG numbers in the United States is smaller, behind each number are real users who have acted recently, and the private message reply rate and community joining rate are significantly higher.

3 common application scenarios for active data on Telegram in the United States

1. American community operation: Invite active users into brand communities (such as e-commerce discount groups, cryptocurrency exchange groups), and active users are more likely to retain and interact.
2. Private message promotion: Send targeted marketing content (such as independent website new product notifications, cross-border logistics services) to active numbers to reduce the probability of being blacklisted and reported.
3. Cross-border e-commerce research: Analyze the target market population portrait through the gender and age fields of active users to assist product selection and pricing decisions.

If you need users who can really talk to each other, US Active TG is the goal, rather than simply opening a number.

Why do we need to do a small sample test first? 5 reasons why you can’t say no

The risk of jumping into high-volume tasks may be higher than you think. Here are 5 reasons, each of which can help you save real money.

Cost control - avoid invalid numbers draining the budget

Screen numbers are deducted on a per-item basis. For specific unit prices, see the real-time price on the console. Suppose you generate 1 million random American numbers and submit them directly for TG activity detection. If the activity rate of this batch of numbers is only 5%, then the detection fee for 950,000 numbers will be wasted. If you first run a small sample of 5,000 items and find that the activity rate is extremely low, you only need to spend the detection fee of 5,000 items to avoid the subsequent waste of 995,000 items.

Data quality verification - number activity rates vary greatly in different countries

The United States has a vast territory and complex carrier number segments. For example, the activity rate of mobile phone number blocks in some areas (such as the +1 808 Hawaii number block) may be less than 5% due to sparse population, while the activity rate of the number blocks in New York and Los Angeles may exceed 30%. A small sample can quickly help you identify the “bad number segment” and avoid it when generating subsequent numbers.

Other 3 reasons: risk control, decision-making efficiency, data availability

• Risk Control: Could batch testing trigger platform risk control? Test the water first with a small sample to ensure that the task is performed normally.
• Decision Efficiency: It takes dozens of minutes to get results, which is much faster than waiting for hours or even a day for large tasks.
• Data Availability: The coverage of gender and age fields in the test results may be insufficient. If you find out in advance, you can adjust the filtering conditions.

How to use KK-DATA to conduct a small sample test of active TG in the United States? (step by step operation)

The following operations can be completed in KK-DATA Console. The whole process takes about 10-30 minutes.

Step 1: Prepare test numbers - global number generation or CSV import

Enter the “Global Number Generation” module:

• Select country: United States (country code +1)
• Number of settings: 500-5000 is recommended (start with 500, if the activity rate is low, add 2000)
• Click to generate: the number is generated for free and exported to CSV or TXT after completion

If you already have a target number segment (such as the mobile phone number prefix of a certain city), you can also directly import the CSV to avoid the inefficiency of generating random numbers.

Step 2: Submit the test task—select tg active detection and set the active window

1. Enter “New Filtering Task” and select the “Telegram” platform.
2. Set the detection type to “tg active” and select the active window:
   • Last 7 days: Suitable for marketing activities that urgently need to be reached, and the crowd is the most “hot”.
   • Last 30 days: Suitable for general community invitations with wider coverage.
   • (Optional) During testing, you can run two windows with 500 entries each at the same time and compare the results.
3. If you need to filter by gender/age, you can uncheck it first and check the coverage of this field in the test results before making a decision.

Step 3: Check the estimated cost and confirm submission

Before submission, the system will display the estimated deduction amount. Click Confirm after confirming that the balance is sufficient. It is recommended to turn on “Telegram task notification” in the console (bind through @kkdata_robot), and the results will be pushed after the task is completed.

Tasks are usually completed within a few minutes, and if there are less than 5,000 items, it usually takes no more than 5 minutes.

What do you think of the small sample test results? ——Interpretation of key indicators and decision-making framework

After the task is completed, export the CSV results file, focusing on the following metrics.

Core indicator 1: Active Rate

Activity rate = number of active numbers ÷ total number of detections. For example, out of 5,000 items, 1,800 are active, and the activity rate is 36%.

• ≥30%: high-quality number segment, which can be expanded boldly.
• 10%-30%: medium quality, can be expanded but it is recommended to control the scale (such as 50,000-100,000), or consider changing the number segment.
• Less than 10%: The quality is very poor. It is recommended to abandon the number segment and regenerate or import numbers from other sources.

Core indicator 2: Effective activation rate (Registered Rate)

Opening rate = number of opened numbers ÷ total number of detections. A high activation rate (≥80%) but a low activity rate (less than 10%) indicates that there are many zombie accounts in this account segment and it is not worth investing in.

How to determine the availability of gender and age fields?

TG activity detection comes with gender and age data (based on public information and behavioral model inference, not 100% accurate). Check out the test results:

• Coverage: How many active numbers have gender/age fields attached? If it is lower than 60%, it is not recommended to enable gender filtering in the expansion task, otherwise a large number of valid numbers will be filtered out.
• Distribution: Suppose your target is “men around 30 years old”, observe whether the proportion of men aged 30-39 is significant in the test results. If it only accounts for 5%, you need to adjust the target period or switch to other platforms.

After passing the small sample test, how to expand the task to the complete goal?

If the test results are satisfactory (activity rate ≥ 30%, gender/age coverage reaches standard), you can enter the expansion stage. The following are 3 must-do checks.

3 Checklists Before Expanding Tasks

1. Is the account balance sufficient: Log in to the console to check the balance. If it is not enough, recharge via USDT (TRC20), the minimum is about 50 USDT. Please see Billing Page for unit price details.
2. Whether the target number range has been generated: Use the “Global Number Segment Generation” or “Custom Number Segment Import” function to generate the required number of numbers. It is recommended to generate 20% more as backup.
3. Whether the data deduplication warehouse has been turned on: Turn on “data deduplication” in the console, and the system will automatically skip numbers that have been detected before to avoid repeated deductions.

Batch submission strategy: avoid excessive single task affecting efficiency

Although KK-DATA supports up to about 1 million items in a single task, it is recommended to split it into 100,000 items per batch. Reason:

• Submit in batches to observe the activity rate of each batch in real time. If there is an abnormality (such as a sudden drop in the activity rate of a certain batch of numbers), you can pause and adjust the generation rules midway.
• With the data deduplication warehouse, duplicate numbers in different batches will not be repeatedly detected.

Common misunderstandings and precautions for active TG screening numbers in the United States

We will help you avoid pitfalls that are easy to step on in practice.

• Ignore the area code segment selection when generating numbers: There are a large number of virtual operator number segments in the United States (such as certain prefixes of +1 206), and their activity rate may be extremely low. It is recommended to check “Prefer using mainstream operator number segments” when generating or manually specify the state code.
• Ignore active window timeliness: If the “active in the last 30 days” numbers in the export results are used after a week, some numbers have become inactive. It is recommended to retest within 7 days before acquiring customers or use a shorter window.
• Mistakenly believe that gender data can be accurate to an individual: Gender/age data are model inferences, not real-name authentication. Do not use it for accurate identity judgment, only use it as a reference for crowd portraits.

Small sample testing vs direct large batch screening - cost and risk comparison

Strategy	Assumed detection volume	Detection fee (unit price per thousand)	Number of valid numbers (assuming activity rate 20%)	Cost per valid number
Small sample test → expansion	Test 5,000 + expand 100,000 = 105,000	Based on unit price	20,000 + test results ≈ 21,000	Low
Direct large batch	Direct detection of 1 million pieces	Based on unit price	200,000 pieces	High (including invalid testing expenses)

Note: The unit price varies depending on the detection type. For details, see the real-time price on the console. However, no matter the unit price, the small sample strategy can reduce the proportion of invalid detection from 80% to less than 5%.

FAQ

**Q: What is the recommended minimum quantity for small sample testing? **

Answer: It is recommended to start with 500 numbers, and the maximum number is 5,000. If the number is too small, the statistical significance will be insufficient (for example, if 2 out of 10 items are tested and active, it cannot be judged to be luck), and if the number is too large, the cost-saving significance of “small samples” will be lost. The effective activity rate of US area codes is usually between 5% and 40%, and 500 is enough to evaluate the trend.

**Q: The activity rate in the test results is very low, can I still continue to expand the task? **

Answer: Not recommended. If the small sample activity rate is less than 10%, continuing to expand will only continue to obtain a large number of invalid numbers. It is recommended to change the number range (such as changing from a US mobile phone number range to a landline number range, or adjusting the generation rules), or switching to other platforms (such as WhatsApp, Line) to acquire customers. You can also try changing the country from the United States to Canada, the United Kingdom and other regions with higher activity rates in the KK-DATA console.

**Q: How to choose the “active window” for tg active detection? **

Answer: The active window refers to whether the number has any Telegram activity within the specified number of days. The “last 7 days” active window is recommended for customer acquisition scenarios, and the “near 30 days” is available if the urgency is low. The shorter the window, the “hotter” the population obtained, but the detection volume will be reduced. If you need enough numbers to try at the same time, you can first test 500 numbers for the past 7 days + 500 numbers for the past 30 days, and then make a choice.

**Q: Is the gender/age data derived from the small sample test accurate? **

Answer: Not accurate. KK-DATA’s gender/age data is based on account public information or behavioral model inference, and is not accurate at the ID card level. It is recommended to use it as a reference dimension for crowd screening, and do not rely on a single value for precise positioning. For example, “about 30 years old” means that the model predicts that the age is between 25 and 35 years old. If the gender field coverage in the test results is less than 50%, it is recommended to abandon gender screening in the expansion task to avoid excessive filtering.

**Q: If the small sample test results are very good, can I submit 1 million tasks directly? **

Answer: Yes, but it is recommended to do it in batches. A single task supports up to about 1 million numbers, but by submitting in batches (for example, 100,000 numbers per batch), the progress of the task can be observed in a timely manner, and the filtering conditions can be fine-tuned based on the effect along the way. At the same time, enable the data deduplication warehouse to avoid repeated deductions for duplicate numbers in different batches.

Summary

To do the US Active TG screening, running a small sample test first is not an elective course, it is a required course. It helps you verify number quality with minimal cost, avoid budget waste, and obtain key data to optimize subsequent batches. If you haven’t tried this “test first and then expand” strategy, you can log in to [KK-DATA Console] (https://app.kkdata.cc/) now to start your first small sample test.

If you encounter any problems, you can get real-time help through two-way contact customer service https://t.me/kkdata_robot. For detailed functional documentation, please refer to https://docs.kkdata.cc/.

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*Warm reminder: All functions are subject to the actual display on the console. For specific detection unit prices, please check the real-time price on the console. *