The Complete Guide to U.S. Data Cost Estimation: A Budgeting Framework Based on Raw Volume, Pass Rate, and Inspection Tier

Among overseas customers, US data has always been a high-value but high-barrier track. After many teams get a batch of U.S. numbers, the first thing they care about is “how much does it cost to screen them again?” But if you only focus on the single price of a certain platform, it is easy to fall into a budget out of control dilemma - because the actual cost is determined by three variables: original number volume, estimated pass rate, and detection level. This article provides a reusable cost estimation framework to help you accurately grasp the budget before submitting a task and avoid excessive deductions or repeated testing.

Why is a cost estimating framework for U.S. data needed?

Different customer acquisition stages have completely different requirements for data quality. If your goal is “Only a Telegram number that has been opened” and “WhatsApp users who have been active in the past 7 days and are male”, the cost of the two may differ several times. Fixed unit price thinking cannot cope with this kind of elastic demand. Only dynamic calculation using variable formulas can make every penny spent wisely.

Fixed unit price vs. flexible budget: Which one is more suitable for your customer acquisition stage?

• Fixed unit price model (such as paying by the number of interfaces) is simple, but it ignores the difference in pass rates - for the same amount of money, the activation rate of Telegram’s US numbers may only be 40%, while the activation rate of iMessage may be much higher. The actual deduction base is different, and the fixed unit price cannot reflect the true cost-effectiveness.
• Flexible budget mode: First estimate the original number volume, then multiply it by the expected pass rate to get the actual detection volume, and finally multiply it by the unit price of the detection level to get the total cost. This method allows you to make a more economical decision at the selection stage: whether to optimize the original number segment or adjust the activity window.

The three core elements of cost estimation: original quantity, pass rate, and inspection level

1. Original number: The total number of numbers you plan to generate or import (including invalid numbers).
2. Pass rate: The proportion of numbers that are still valid after passing a certain test. For example, the pass rate of Telegram activation detection and the pass rate of activity detection.
3. Detection level: The detection type you choose (activated/active/sex, age, etc.), the unit price of each type is different.

Total cost formula: 总成本 = 原始号码量 × 预期通过率 × 检测层级单价. Below we expand layer by layer.

Step 1: Determine the raw US number data volume (generation or procurement scale)

You need “raw materials” before you can sift. There are two common ways to obtain an original US number:

1. Randomly generated using the number generation module: In the “Global Number Generation” function of the KK-DATA console, select the country/region as “United States” (country code + 1), and you can randomly generate a US number based on the number segment. This process is completely free and does not consume any balance.
2. Import CSV from third-party data sources: If you have obtained the number list through other channels, you can upload it directly. Be sure to make preparations for deduplication before uploading to avoid repeated deductions during subsequent testing.

Estimation Points: Don’t blindly seek to increase the original quantity. If your target market is English-speaking users in the United States, it is recommended that the number include the mainstream operator number segment (such as 310-xxx). If the target is a niche Chinese population, you can carefully select a specific number segment. It is generally recommended that the first batch of tests should be between 50,000 and 200,000, and then scale up after passing the test.

Step 2: Estimate the pass rate of US numbers (the key to affecting the actual amount of deductions)

Pass rate is the most overlooked variable in cost estimates. Suppose you have prepared 1 million US numbers. If the Telegram activation rate is only 40%, then only 400,000 numbers will actually be detected, and the deduction will be based on 400,000 numbers. If you have already done activity detection, the actual deduction amount will be further reduced. The lower the pass rate, the lower the actual deduction, but the less valid data. You need to balance quality with cost.

Difference in typical pass rates for US numbers across platforms (Telegram vs WhatsApp vs iMessage)

Platform	Typical activation pass rate for U.S. numbers (reference)	Remarks
Telegram	30%~50%	Depends on the quality of the account segment, zombie accounts account for a higher proportion
WhatsApp	60% ~ 80%	The user binding rate is high, but the activity may be lower than the activation rate
iMessage	70% to 90%	Apple has a large user base, but it is necessary to distinguish between “iOS devices” and “iMessage valid”
Line	20%~40%	There are few users in the United States and the pass rate is low
Zalo	Less than 10%	Mainly in Vietnam/Southeast Asia, the US number pass rate is extremely low

Pass rate of activity detection: If you select “Active in the past 7 days”, the pass rate will usually be 20% to 40% lower than “Active”. For example, Telegram’s activation rate is 40%. After adding the “active in the past 7 days” condition, it may only be 15% to 25%.

How to further reduce the number of valid numbers through the activity threshold

When you set a higher activity window (such as “active in the past 3 days”), the pass rate will drop off a cliff. This means that the actual amount of deductions is greatly reduced, but the quality of the remaining users is very high. If your budget is limited, you can accept a lower effective volume, and appropriately raising the activity threshold can save the total cost (because the deduction base becomes smaller). However, please note that active detection on some platforms (such as WhatsApp) may be billed together with activated detection. The specific rules are subject to the console.

Step 3: Select the detection level - enabled, active or gender/age?

Different detection levels correspond to different single prices (see real-time prices on the console for details), and the values ​​of the output data are also different. You need to build a “cost-value” decision tree based on your customer acquisition goals.

• Requires only activation certificate: The cheapest level, used to determine whether the number is registered with a certain platform. Suitable for basic cleansing before mass hair.
• Active users required: Adding activity limits based on activation can increase the reach rate, but the single price will be higher.
• Gender/Age Targeting Required: Gender identification is typically done on an open and active basis. Note that gender detection will not reduce the number of original numbers - it is based on further analysis of confirmed activated numbers, and the deduction is based on the number of numbers actually detected, not the results after screening.

Decision Suggestions:

• Initial stage: Only “opening detection” is done to collect platform coverage.
• Verification phase: Perform “activity detection” on the activated number and set the appropriate window.
• Orientation stage: conduct “gender/age” analysis of active users. The deductions are superimposed at each step, but the value of the data increases step by step.

Step 4: Substitute the cost estimation formula to calculate the total US data budget

General formula:

Total cost = Original number × Estimated pass rate × Unit price of detection level

Example (the values are for demonstration only, the actual values are subject to the console):

• You have generated 200,000 US numbers and plan to do Telegram activation test first.
• The estimated activation pass rate is 40%, then the actual detection volume = 200,000 × 40% = 80,000.
• Assume that the unit price of Telegram activation detection is X (real-time price of the console), the total cost = 80,000 × X.

If you also want to add activity detection:

• Perform activity detection on 80,000 activated numbers. Assuming the activity pass rate is 60%, the actual detection volume = 80,000 × 60% = 48,000.
• The unit price of active detection is Y, then the total cost = 80,000 × X + 48,000 × Y.

There’s no math required for the entire process—the estimated cost for each step is clearly displayed on the console when you submit a task.

How to verify your cost estimates using the KK-DATA console?

Instead of talking about it on paper, it is better to go directly to the console and run a test. The process is as follows:

1. Log in to the Application Console and enter the “New Screen Number Task”.
2. Upload or generate a batch of US numbers (at least 1,000 are recommended for testing).
3. Select the detection type: first check “Telegram activation”, then click “Detect now”.
4. Before submitting, the system will display the estimated fee, which is the actual balance you want to deduct (provided the account balance is sufficient).
5. Check the pass rate statistics: After the task is completed, the console will display the “total number of numbers”, “number of passes” and “number of failures”. You can calibrate the budget for subsequent large-scale tasks based on this.

Generate → Filter → Export: a pipeline to reduce manual estimation deviations

KK-DATA’s “Global Number Generation” and “Global Number Screening” modules are seamlessly connected. You can complete it in one task: Generate number → Select detection platform and type → Submit → View pass rate → Export valid number. The entire process is transparent, and the deductions at each step are clearly displayed.

Data deduplication warehouse: avoid additional deductions caused by repeated detection

If you have multiple batches of numbers, it is recommended to use the “Data Deduplication Warehouse” function to automatically exclude numbers that have been detected. This can prevent waste caused by repeatedly submitting the same number, and is especially suitable for teams that operate for a long time. The deduplication operation is free and does not consume your balance.

US Data Cost Optimization Best Practices (Five Common Pitfalls)

1. Trap 1: Directly multiply the original number by the unit price Countermeasure: Be sure to estimate the pass rate first. 1 million items × unit price = seems huge, but after the actual pass rate is 40%, the deduction is only 400,000 items, and the budget may be completely within control. On the contrary, if the pass rate is underestimated, a sudden deduction of a bunch of balances will also catch people off guard.

2. Trap 2: Ignore the secondary compression of pass rate by activity detection Countermeasures: When planning the budget, consider both the activation pass rate and the active pass rate. Multiplying the two is the final deduction base.

3. Trap 3: All numbers without semicolons are detected Countermeasures: First use a small number of test samples to determine the pass rates of different code segments, and then concentrate resources to screen high-quality code segments. For example, virtual numbers in the US number band (such as the 900 number band) have a very low pass rate and can be eliminated directly.

4. Trap 4: Checking too many detection types in the same task Countermeasure: Take it step by step. Do the activation first and export the passed number; then do the activity or gender to avoid balance loss caused by one-time failure.

5. Trap 5: Unused data deduplication warehouse Countermeasures: Import detected numbers into the deduplication database regularly, and automatically exclude duplicates when generating new numbers to avoid waste.

FAQ

**Q: What is the most overlooked variable when estimating U.S. data costs? ** Answer: The most commonly ignored thing is the “pass rate of activity detection”. Many people directly use the original number × unit price to calculate, but the actual number of detected numbers is the original number multiplied by the pass rate (for example, if there are 1 million original US numbers, the Telegram activation rate may be only 40%, then the actual deduction will be based on 400,000). The activity threshold will further reduce the deduction base, making the budget easier to control.

**Q: Is there a big difference in the unit price of US screen sizes on different platforms? ** Answer: Yes. The detection unit prices of platforms such as Telegram, WhatsApp, iMessage, Line, and Zalo vary due to different technical costs, and the prices of activation detection, activity detection, and gender recognition detection within the same platform are also different. For specific prices, please refer to the “estimated cost” displayed on the console before submitting the task.

**Q: I want to get a male number that is active on Telegram in the United States. How can I estimate the cost most accurately? ** Answer: Suggested steps: ① Determine the number of original US numbers through global number generation or importing CSV; ② Use “Telegram activation detection” to estimate the activation rate; ③ Do “Telegram activity detection” for activated numbers and set the activity window; ④ Perform “gender identification” for active numbers. The deduction coefficients of each step are superimposed, and the final total cost = original amount × activation pass rate × active pass rate × (activation unit price + active unit price + gender unit price). When you submit a task using the console, the estimated costs for each tier will be displayed in sequence.

**Q: I only have a small number of US numbers (for example, less than 5,000), do I need a cost estimate? ** Answer: Yes. Even if the quantity is small, it is necessary to confirm the detection level and corresponding unit price to avoid excessive single cost due to choosing a more expensive detection type (such as gender and age identification). It is recommended to check the real-time price on the console first, or contact customer service for advice.

**Q: Why can’t I write the specific unit price in the article? ** Answer: Because the platform price will be adjusted according to the operating strategy and market environment, hard-coding the numbers may lead to outdated information. KK-DATA adopts billing by item and real-time price display mode. All unit prices are based on the estimated cost displayed on the console before submitting the task as the only authoritative basis.

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**Start your first US data screening mission now! ** 👉 Log in to the console Submit your number and view estimated costs to get a complete picture of your costs in minutes.
If you need manual assistance in estimating the budget or obtaining number segment suggestions, you can communicate in real time through two-way contact customer service https://t.me/kkdata_robot.
For more instructions, please refer to Document Center and Official Website.