How to judge the quality of data detection results? 3-Step Guide to Assessing Lot Availability

When you get a batch of number test results from the number screening platform, your first reaction may be “What is the activation rate?” - but this is far from enough. The true quality of the data detection results depends on whether the number can actually be used for your specific customer acquisition scenario. This article starts from actual practice and teaches you 3 steps to evaluate the data quality of Telegram, WhatsApp, Line and other platforms to avoid getting a bunch of “fake valid” numbers and wasting detection budget and subsequent contact costs.

What are “usable” data detection results?

Many overseas teams equate “activation” with “availability”. This is a common misunderstanding. A number is registered (activated) on Telegram, but if the other party has not been online for 3 months, has a default avatar, and has no group interaction, your private message will most likely go nowhere, and may even be reported.

“Usable” data detection results should meet three conditions at the same time:

1. Valid registration - the number does exist on the platform (not an abandoned number segment).
2. Reasonably active - The number has online behavior in the recent past (such as within 7 days), or it falls within your target active window.
3. Attribute matching - fields such as gender and age are consistent with your target group, and the field confidence is acceptable.

Just looking at the “opening rate” is like looking at whether there are kitchen knives in the kitchen, but not caring whether the kitchen knives are rusty - you may not be able to cut vegetables in the end.

Three core dimensions for judging the quality of data detection results

Dimension 1: Effectiveness test results - activation rate and false detection identification

Effectiveness is the most basic dimension, but it is not the whole story. The detection platform usually determines whether the number has been registered by sending a simulated registration request or querying the platform API. But please note:

• Source of false detection: Some old number segments may have been recycled by the platform but the database has not been updated, resulting in a detection result of “unregistered” that is actually still valid; or conversely, the number itself has been logged out but the cache has not been cleared, and is falsely reported as “activated”.
• Quality Assessment Method: Extract the “activated” numbers in the test results, randomly select dozens of them and manually send a test message (pay attention to compliance) to confirm that the other party can receive it normally. If the false detection rate exceeds 5%, it means there is a problem with the batch number segment or the detection configuration. It is recommended to regenerate or replace the number segment.

Dimension 2: Activity detection results - activity window and frequency

Activity is the key to measuring the “value” of a number. KK-DATA supports specifying active windows (such as the last 7 days, 30 days), and the detection results will return the number’s last online time or activity mark.

• Why is it important: A number that was activated a year ago but is not used now will receive almost zero response during group push, and may also cause the number to be flagged by the platform.
• Quality Judgment: In the same batch of numbers, the higher the proportion of active numbers, the better the data quality. If the activity rate is less than 10%, these numbers can basically only be used for “padding” or low-frequency verification, and are not suitable for immediate contact.
• Tip: Don’t just look at the “Active” tag, look at the specific timestamp when it was active. If the results show “Active in the last 7 days”, it is usually more valuable than “Active in the last 30 days.”

Dimension 3: Attribute detection results—confidence of gender, age and other fields

For platforms such as Line, Zalo, and Telegram that support attribute detection, information such as gender, age, and avatar can help you achieve more precise targeting. But please note:

• Gender data: Inferred based on platform public information or behavioral models, not an official certification field. The accuracy is usually between 70%–85%, and varies widely between platforms. For example, Telegram’s gender detection refers to the name, avatar style and group behavior in the profile, while Line relies more on registration information.
• Age field: The age in the test results is an estimate range, such as “about 30 years old”, not the exact date of birth. Don’t treat it as accurate data like an ID card.
• Quality Judgment: If the filling rate of the gender/age field in the test results is very low (for example, only 20% of the numbers return attributes), or there is a large amount of obviously contradictory data (such as a male number showing “female”), it is recommended to reduce the trust in the attribute fields of this batch of numbers and use them only as an auxiliary reference.

How to quickly filter out high-quality data detection results? (Practical steps)

Step 1: Do a small sample quality inspection first - take 5% samples to verify data consistency

Specific methods:

• Randomly select 5% of the numbers from the target number pool and submit the detection task.
• After the detection is completed, manually check 10-20 “activated and active” numbers and try to send a simple test message (it is recommended to use “Hi” or “Hello” and do not contain marketing content).
• If the manual verification pass rate is ≥90%, you can continue.

Step 2: Use the deduplication warehouse to eliminate duplicate detection records

Most overseas teams will obtain number databases from different channels multiple times, and these numbers are likely to be repeated. Repeated submissions for detection not only waste balance, but also lead to statistical bias (the same number is counted multiple times).

Use KK-DATA’s data deduplication warehouse function to upload or directly connect historically detected numbers, and the system will automatically mark the detected numbers to avoid repeated deductions. Suggestions:

• After each export result, import the number list into the deduplication warehouse.
• Before submitting a new task, check for duplication in the warehouse first, and only conduct new tasks for unchecked numbers.
• Regularly clean up expired data in the warehouse (records older than 3 months can be removed).

Step 3: Filter the required fields (such as activity, gender) based on the target scenario

Different scenarios require different combinations of fields to be filtered. For example:

• Telegram Group Promotion: Priority will be given to numbers that are “activated + active in the last 7 days + tgid”.
• WhatsApp Private Message: Give priority to keeping numbers that are “open + active + no timeout records” to avoid being reported.
• Line/Zalo Targeted Customer Acquisition: Select the number that is “activated + gender male/female + age 25–40”.

When creating a task in the KK-DATA console, you can check the fields you need in the “Detection Type”. Select CSV format when exporting to facilitate subsequent secondary screening using Excel or scripts.

What are the different quality requirements for data detection results in different customer acquisition scenarios?

Scenario	Core concerns	Acceptable sub-optimal data	Bottom line of quality
Telegram group promotion	Activity + tgid export	Only activated numbers can be used for “padding”	At least activation rate ≥ 40% and activity rate ≥ 20%
WhatsApp private message	Activation + Active (avoid silent accounts)	Only activated numbers can be used for low-frequency verification	Activation rate ≥50%, activity rate ≥15%
Line/Zalo targeted customer acquisition	Gender + age + active	Only opened numbers can be used for general investment	Attribute field filling rate ≥ 60%, gender accuracy rate ≥ 70%
iOS/iMessage	Device type + iMessage activation	Only activated iMessage numbers can be used for group sending	Activation rate ≥30% (largely affected by region)

Scenario 1: Telegram group promotion - pay more attention to activity and tgid export

The core of Telegram group promotion is “someone can watch + click on the link”. If the number is only activated but not active, no matter how many messages you send, no one will respond. In addition, tgid (Telegram user’s unique ID) can be used for more refined targeting (such as excluding bot accounts). It is recommended to check “Export tgid” during detection.

Scenario 2: WhatsApp private message - follow the activation + avoid being reported

WhatsApp cracks down hard on spam messages. If you use a long-term inactive number to send a large number of unread messages, your account will easily be marked as spam and banned. Therefore, in addition to “activated” in the test results, you should also pay attention to the “recent online time”. If a large number of numbers in a batch show “Online 30 days ago”, it is recommended to filter them directly.

Scenario 3: Line/Zalo targeted customer acquisition - gender + age field support is required

In markets such as Vietnam, Taiwan, and Southeast Asia, Line and Zalo are the main social tools. When targeting marketing, gender and age fields can significantly increase click-through rates. If the filling rate of the gender field in the detection results is less than 50%, you can consider doing a round of small tasks of “detecting attributes only” first, and then run them in batches after confirming that the data is available.

Common data detection result “pits” and avoidance methods

Pitfalls	Phenomenon	Avoidance methods
Data expired	Check the number segment half a year ago, the activation rate is very low	Use the latest global number segment generator (KK-DATA supports 240+ countries), or update the number pool regularly
Number segment interference	The molecule numbers in the same number segment are abandoned by the platform	Split the number segments before detection, submit small tasks separately for each sub-number segment, and observe the activation rate distribution
Gender field misunderstandings	Treat gender detection results as official data	Combined with secondary verification such as avatar and user name, or only as an auxiliary reference
The active time is inaccurate	There is a 1-3 day delay in activity detection on some platforms	Please refer to the timestamp in the detection results, do not rely on the “active” label itself
Waste of account balance	Repeated detection of the same number	Use deduplication warehouse to avoid repeated deductions; for balance view, please see the real-time price of the console

How to use platform tools to improve the usability of data detection results?

KK-DATA provides a series of auxiliary functions to help you manage and utilize data detection results more efficiently:

• Duplicate Warehouse: Remove duplicates across tasks, avoid duplicate detection, and save balance. Each time before importing a new number, compare it with the warehouse.
• Multi-format export: CSV, TXT and other formats, convenient for docking with self-built CRM or automatic mass sending tools.
• Task Notification: Automatically send notifications through Telegram Bot after the detection is completed to avoid waiting in the console.
• Global Number Generation: Generate 240+ national number segments for free, including operator prefixes to ensure the freshness of the number segments. Submit for detection directly after generation, pipeline operation.

Summary: Establish your data inspection results quality review process

Finally, it is recommended that each merchant formulate a set of standard operating procedures (SOP):

1. Generate sample: Use KK-DATA to generate or import a number pool for free, and select 5% for small-scale testing.
2. Quality Inspection: Manually verify a small number of numbers to confirm whether the activation rate, activity rate, and attribute filling rate are reasonable.
3. Deduplication: Import the checked numbers into the deduplication warehouse to avoid subsequent duplication.
4. Filter: Select a field combination based on the target scenario (group promotion/private message/targeted) and submit tasks in batches.
5. Export for use: Complete the contact within 30 days, and re-sample after the expiration date.

**The quality of data detection results determines customer acquisition efficiency. ** Instead of spending a lot of time cleaning invalid data, establish the above review process from the beginning. As a data screening platform, KK-DATA provides a closed loop of number generation → detection → deduplication → export, which can help you complete quality control in one stop. All detection types and prices are displayed in real time on the console, and billing is done on a per-item basis without the pressure of a package.

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FAQ

**Q: What is the difference between “open” and “active” in the data detection results? ** Answer: “Activated” only means that the number has registered with the corresponding platform; “Active” means that the number has online behavior within the specified time window (such as the last 7 days or 30 days). When doing group promotion, it is recommended to give priority to using “active” numbers instead of only “activated” numbers.

**Q: How accurate is the gender data returned by the platform? ** Answer: Gender data is based on platform public information or behavioral model inference, and is an unofficial certification field. The accuracy is usually between 70% and 85%, depending on the platform and region. It is recommended to cross-reference with the age field instead of relying on the gender field alone to make decisions.

**Q: Why do many of the batch numbers I tested show “unregistered”? ** Answer: Common reasons include: the number segment has been abandoned by the platform, the number generator uses an expired number segment, or the platform has low coverage in the area. It is recommended to obtain the latest number segment through the global number generation function before testing.

**Q: How to reduce testing costs while ensuring the quality of data testing results? ** Answer: Use a data deduplication warehouse to avoid repeated detection of the same number; prioritize detection of activity (fee charged per item) rather than full fields; first use a small sample to verify quality, and then submit large tasks in batches. See the real-time display on the console for detailed prices.

**Q: After the data detection results are exported, can they be used directly for mass distribution? ** Answer: Yes, but it is recommended to do a second verification first: select 1%–5% of the numbers to manually send a test message to confirm that the other party can receive it normally. At the same time, pay attention to abide by the platform’s anti-spam policy and use compliant frequency for sending.

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Now, start improving the quality of your data detection results!
👉Log in to the console to create a screening task If you have any questions or need customized solutions, please contact two-way customer service: https://t.me/kkdata_robot For more operating instructions, please refer to Usage Documentation.