Line Valid Number Screening Pitfall Guide: 5 Common Mistakes and Correct Operation Steps

Obtaining a Line valid number is a key step in acquiring customers in Southeast Asia, especially in markets such as Thailand, Indonesia, Vietnam, and Japan. Line is the core social tool for users’ daily communication and consumption. However, many teams make some common mistakes during the number screening process, resulting in poor number quality, wasted budget, and even data contamination. This article summarizes 5 high-frequency mistakes and provides a step-by-step correct operation guide to help you efficiently output accurate customer groups.

What is a valid Line number? Two concepts that must be understood before screening

Before starting to screen numbers, be sure to clarify the specific meaning of “Line valid numbers”. Line screening usually detects the following two states, and different states correspond to different marketing goals.

Effective vs Active: Which status do you need for your marketing goals?

• Activated (valid): Indicates that the mobile phone number has registered a Line account and is the basis for reachability. Suitable for adding friends in batches, sending invitation links, etc.
• Active: Indicates that the account has online behavior within the specified time period (such as the past 7 days, the past 30 days). Suitable for high interaction needs such as private message promotion and community activation.

If you just want to confirm whether the number is registered with Line, just select “Activate”; if you want to filter out recent active real users, you must select “Active” detection. Confusing the two will lead to target deviation - a number that is simply “activated” may have been abandoned long ago, and activity detection will help you filter out “zombie accounts” that have not logged in for a long time.

What can Line gender recognition do? How to select people around 30 years old?

Line gender detection is based on public data and model inference. The returned fields usually include male, female or unknown, and some scenarios come with an age range (for example, 25-34 years old). You can use the age field to select people “about 30 years old” as a reference for demographic characteristics, but note: Age and gender are not ID card-level accuracy and are only used for targeted screening and cannot replace manual verification. For example, when promoting a beauty product for women around the age of 30, you can narrow the scope by combining the gender “female” with the age range 25-34 to avoid casting a wide net.

Mistake 1: Use uncleaned number library to screen numbers directly - data pollution is almost irreversible

After many teams collect mobile phone numbers from various channels, they directly submit the screening numbers without any cleaning. As a result, either a large number of numbers have incorrect formats and are skipped by the platform, or duplicate numbers lead to repeated deductions.

Correct approach:

• Uniform Format: All numbers must comply with the E.164 international standard, that is, ”+” plus country code plus local number. For example, Thai numbers are written +66 8X XXX XXXX (the hyphen can be removed).
• Duplication removal: Use Excel or script to remove duplicates to avoid multiple detections of the same number.
• Supplementary country code: If you only have a local number (no area code), you need to manually add the corresponding country code. For example, Indonesian numbers add +62, and Vietnamese numbers add +84.
• Remove invalid characters: Remove non-numeric symbols such as spaces, brackets, dashes, etc.

The cleaned number library should be exported as plain text or CSV, with one number per line and a uniform format. Although this step is time-consuming, it can significantly improve screening efficiency and prevent data pollution.

Mistake 2: Choosing the wrong number screening platform causes the proportion of effective Line numbers to be falsely high or low.

Different screen number platforms may have different definitions and detection logic of “Line valid”. Some platforms only judge based on online status (if it detects that the account is online, it is valid), while others rely on a more comprehensive registration database, resulting in a huge difference in the proportion of results. For example, if your platform only checks online status, then inactive registered numbers will be judged as “invalid”, resulting in a low effective ratio; conversely, if the platform only checks whether the number format matches the Line user table, some inactive numbers may be mistakenly judged as valid.

Mistake 3: Ignoring the country code and number format - common thresholds

Line number filtering relies on the international number format. The lack of country code will cause a large number of numbers to be automatically filtered by the platform. Especially in Southeast Asian countries, number lengths and prefixes vary.

Quick check of Line number formats in major Southeast Asian countries (Thailand, Indonesia, Vietnam, Japan)

Country	International area code	Number length (including area code)	Example
Thailand	+66	9-10 people (officially 10 people)	+66 8X XXX XXXX (10 people)
Indonesia	+62	10-12 people	+62 8XX XXXX XXXX (12 people)
Vietnam	+84	10-11 digits	+84 9X XXX XXXX (11 digits)
Japan	+81	11 digits	+81 90 XXXX XXXX (11 digits)

Note: The prefixes of different operators (such as Thailand 08, 09) change frequently. It is recommended to use a small sample to verify whether the number length is compliant before submitting.

How to use the global number generation tool to pre-generate compliant numbers for testing

KK-DATA provides the Global Number Generation module, which can randomly generate numbers that meet the standard format by country/region, or generate them in batches by number segment. You can use the generation tool to generate a batch of test numbers before screening numbers, then submit a small-scale number screening task and observe the uid and 开通 fields in the returned results. This way you can not only verify whether the number format is correct, but also understand the approximate range of Line registration rates in that country. It is completely free to generate, and fees will be deducted on a per-item basis when screening numbers.

Mistake 4: Detecting the entire amount of data at once - missing batching and deduplication strategies

Submitting hundreds of thousands or even millions of numbers to screening at once is very risky: if errors occur in the process (such as number format problems that cause a large number of invalid numbers), not only will it be impossible to modify them midway, but a large amount of balance may also be wasted. At the same time, repeated submission of the same number will result in repeated deductions.

Recommended Strategy:

• Submit in batches: It is recommended that a single task should be controlled within 50,000-100,000 items, and the maximum should not exceed 500,000 items. It is convenient to check the results and make timely adjustments.
• Use deduplication warehouse: Many platforms provide cross-task deduplication functionality. You can import the list of historically detected numbers into the system, and the system will automatically skip these numbers when submitting later to avoid repeated deductions.

Mistake 5: Only look at the “activation” result and ignore subsequent conversion verification

Obtaining a large number of valid Line numbers (registered) does not mean that the other party will reply, add friends or complete the purchase. Many “opened” Line accounts may be user accounts, abandoned accounts, or users may have set privacy restrictions (such as prohibiting adding friends). If you only rely on the activation results, it will easily lead to no response to subsequent private messages.

Correct approach:

• Combining activity and gender fields: For example, only select numbers that have been active in the past 7 days and have a female gender for the first step of private message testing.
• Staged conversion verification:
  1. First use 100-500 numbers to add friends in batches or send welcome private messages, and observe the friend acceptance rate and reply rate.
  2. Adjust the filtering conditions based on the initial conversion rate (such as shortening the active window, changing gender targeting).
  3. After high conversion rate, launch on a large scale.
• Keep unactivated data: Unactivated numbers may be registered on other platforms (such as WhatsApp) and can be used as candidates for cross-screening.

How to correctly operate Line valid number screening? A step-by-step guide

The following is a standardized operating procedure that is recommended to be saved as a team checklist.

Step 1: Number preparation and cleaning (including country code)

1. Collect mobile phone number sources from all target countries.
2. Unified format: Add ”+” and country code before each number, and remove spaces, brackets, and dashes.
3. Use Excel or script deduplication to remove duplicate rows.
4. Verify that the number length complies with the target country specifications (refer to the table above).
5. Export to CSV or TXT file, one number per line.

Step 2: Select detection type (activated/active/gender)

1. Log in to the KK-DATA console → Create a screening task.
2. Platform selection: Line.
3. Detection type:
   • Just “Activate” → Select Line Activate Test.
   • Requires “Recently Active” → Select Line Activity Detection to set the activity window (such as the past 7 days, 30 days).
   • Gender and age required → Select Line Gender Detection to return male/female and age range.
4. Confirm the price: The console will display the estimated cost of this task. If the balance is insufficient, you need to recharge first.

Step 3: Submit in batches and wait for the results

1. Split the cleaned number file into multiple sub-files, each with a size of ≤ 500,000 (50,000-100,000 is recommended).
2. Upload the file and check “Use deduplication warehouse” (if there is historical data).
3. Submit the task and wait for completion (the time depends on the number of numbers, usually a few minutes to a few hours).
4. After the task is completed, obtain the results through the console or Telegram notification (requires binding in advance).

Step 4: Export and apply recommendations (e.g. gender filter, active window)

1. Export the result file (CSV or TXT), including fields: original number, activation status, active flag, gender, age range, uid, etc.
2. Filter out the data in Excel that are “Active=Yes” and “Active=Yes” and “Gender=Male/Female”.
3. Export as a new contact list for subsequent marketing activities.
4. Unactivated numbers can be reserved for screening on other platforms (such as WhatsApp screening).

FAQ

Question: Can Line’s valid number filter detect whether the other party adds me as a friend?

Answer: No. Line valid number screening can only detect whether the mobile phone number has registered a Line account (activated status) and whether it has been online recently (active status). Whether friends have been added is social relationship information and cannot be obtained by the screening platform. Valid numbers screened out need to be further verified through private messages or invitation tools.

Question: Is Line gender recognition accurate? Can it be accurate to the ID card level?

Answer: Line gender recognition is based on public data and model inference, and the accuracy is high but not 100%. The gender field output by the platform is usually “male”, “female” or “unknown”. The age field can be used for group filtering (such as about 30 years old), but it cannot be accurate to the age on the ID card. It is recommended as a reference for orientation and should not be used as the only criterion for judgment.

Question: Is it necessary to add the country code when screening? What will happen if you don’t add it?

Answer: Must be added. Line’s effective number screening relies on the international standard number format (E.164). Numbers that lack country codes will be recognized by the platform as invalid formats and skipped, resulting in a large number of undetected numbers. It is recommended to add ”+” or “00” + country code before the number. For example, for Thai numbers, write +66XXXXXXXXX.

Question: Why is the proportion of valid Line numbers I filtered out so low? What are the possible reasons?

Answer: Common reasons include: 1) A large number of mobile phone numbers that have not been registered with Line are mixed in the number database (such as non-Line users captured from other platforms); 2) The country code is wrong or the number format is not standardized; 3) The “active” status is detected instead of the “activated” status, and the activity standard is higher. It is recommended to first use a small number of numbers to test the “open” status comparison ratio, and then gradually adjust it.

Question: How many Line numbers can be screened at a time? Can I still get a refund after the balance is deducted?

Answer: KK-DATA supports up to about 1 million numbers in a single task, but it is recommended to submit in batches to check the results. After the test is completed, the balance will be deducted based on the actual number of tests, and there is no refund mechanism. The estimated fee will be displayed on the console before submission. Please confirm that the balance is sufficient. For specific unit prices, please see the real-time price on the console.

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The above 5 common mistakes and how-to guides can help you avoid most screen size traps. The key to obtaining high-quality Line valid numbers is to clean the data, select the right platform, remove duplicates in batches, and combine active and gender field targeting. You can start your first screening task now:

👉 Log in to the console to start screening numbers Two-way contact customer service https://t.me/kkdata_robot For more features and documentation please visit https://kkdata.cc/ and https://docs.kkdata.cc/