American Data Field Dictionary: Guide to Interpretation of Number Status, Activity, Gender, Age and Platform ID

When you get a batch of filtered US number data, what does each column of fields in the CSV or TXT file represent? This is the first confusion many overseas marketing teams encounter when using US data. Without correct field interpretation, no matter how high-quality the data is, it cannot be converted into effective leads. This article will systematically explain the core fields in the US number screening results - from the number’s activation/validity status, activity, gender and age to the platform’s unique ID, to help you quickly master the practical skills of US data screening and accurately locate high-value customer acquisition groups.

What is the US Data Field Dictionary? Why is customer acquisition analysis important?

US Data Field Dictionary refers to the set of attributes attached to each record after the number screening is completed, usually including:

• Number activation/validity status (whether the number is registered on the target platform)
• Activity (how recently you have been active on the platform)
• Gender identification results (male, female, unknown)
• Age field (numeric value or age range)
• Platform unique ID (such as tgid, wsid, uid, etc.)

Understanding the meaning of these fields can help you:

• Quickly judge number quality: Avoid including invalid numbers into the lead pool and save subsequent marketing resources.
• Accurate targeting of people: Filter specific users based on gender and age fields to improve conversion rate.
• Avoid duplicate detection: Use platform ID to remove duplicates and reduce balance waste.
• Optimize subsequent operations: Export IDs such as tgid for message push or secondary analysis.

It can be said that the field dictionary is the “getting started guide” for US number data analysis and the basis for efficient use of US customer acquisition data.

How to interpret the “open/valid” status field of a US number?

“Activated/valid” is the most basic field in the number screening result. It directly answers “Does this number exist on the target platform?” Different platforms have different definitions of this status and need to be understood separately.

Differences in the definitions of “activated” and “valid” on different platforms

Platform	Common field names	Meaning
Telegram	tg activation (or account_active)	Whether the number has registered a Telegram account. Registration is considered “activated”, and inactivity is also considered activated.
WhatsApp	wa_available (or wa_available)	Whether the number exists on WhatsApp (usually based on network registration status).
Line	line valid (or line_valid)	Whether the number is associated with a valid Line uid. “Valid” for Line essentially means that the uid exists and can receive messages.
Zalo	zalo active (or zalo_active)	Whether the number has an account on Zalo. Zalo is especially important in Vietnam and Southeast Asia.
iMessage	imessage is valid	Whether the number has enabled iMessage service.

Important: Telegram’s “activation” does not mean “active”, while WhatsApp’s “activation” usually means that the number is available in the WA ecosystem. The validity of Line relies on the existence of uid, which is slightly different from the registered state. When interpreting US number data, you must first clarify the status definition corresponding to the target platform.

Common values of status fields and their business meanings

The status values returned by the filter number usually include the following:

• active / yes / 1: The number is activated/valid on this platform. This type of number is the first choice for the basic lead pool.
• inactive / no / 0: Not activated or invalid. Can be removed directly without subsequent processing.
• unknown: Unable to determine (may be due to network timeout, platform limitations, etc.). It is recommended to use it with caution and you can re-detect or manually exclude it.
• error: An error occurred during the detection process. Usually the amount is small and can be ignored or resubmitted.

Business Suggestion: Prioritize numbers with “activated” status as the initial clue pool, and then further filter based on activity, gender and other fields.

How to use the activation status to filter the initial lead pool

Practical steps:

1. Submit the US number screening task in the KK-DATA console and select the target platform (such as Telegram, WhatsApp).
2. After the task is completed, export the CSV file.
3. Open with Excel, Google Sheets, or any text editor and filter out the rows where the “Open” column value is “Yes” or “1”.
4. Use these numbers as basic clues, and you can continue to do activity detection or gender identification later.

This will ensure that you have at least real registered users, rather than empty or unregistered numbers, which will greatly increase the reach rate of subsequent marketing.

Activity field: How to determine the active time window of a number?

The activity field tells you when or how often the number was last active on the target platform. Common activity indicators include:

• Number of recent active days: For example, “active within 3 days”, “active within 7 days”, “active within 30 days”.
• Monthly Active Count: Number of logins or actions in the past 30 days.
• Weekly active times: The number of active times in the past week.

For example, if you are doing a limited-time discount promotion, give priority to US users who have been active in the last 7 days; if you are doing a brand content subscription, you can relax it to 30 days or more. Note that the precise unit of the activity field is based on the column name exported by the KK-DATA console, common ones are last_active_days, active_freq, etc.

Typical scenarios for using activity fields:

• Filter out “active in the last 7 days” WhatsApp users to send instant offers.
• Exclude Telegram accounts that have been “inactive for more than 90 days” to avoid disturbing zombie accounts.
• Combined with the gender field, target Line users who are “active in the last 30 days and male”.

Gender and age fields: key to crowd targeting

Gender and age fields can help you target people from a large number of numbers. Although these data are derived through algorithmic inference (based on avatars, nicknames, public information, etc.) and are not 100% accurate, they are sufficient for crowd stratification in batch screening scenarios.

Interpretation of gender field results (male, female and unknown)

The gender column in screen size results typically contains the following values:

• Male/male: The algorithm determines that the person is male.
• Female/女: The algorithm determines that the person is female.
• Unknown/Unknown: Unable to determine gender. It may be caused by insufficient information such as blurred avatar, neutral nickname, unpublished name, etc.

Usage Suggestions:

• If you promote a product that is geared toward a specific gender (such as women’s beauty products, men’s razors), prioritize numbers with clear genders.
• Numbers with unknown gender may still lead to conversions, but the targeting effect is weaker. It is recommended to use it as an auxiliary clue pool and filter it in combination with other fields such as activity level.

Interpretation and precautions of age field

The age field is usually derived from public platform information (such as Telegram’s user profile age) or algorithmically inferred, and may be formatted as a specific age value (such as 28, 35) or a age range (such as 25-34). KK-DATA’s Telegram gender detection includes an age field, which can be used to interpret people around 30 years old (for example, filtering for the 25-35 year old range).

For example, you can combine the filter: “US number + Telegram activation + active within 7 days + male + age 25-35 years old”. This can greatly improve the accuracy of the target audience. But don’t treat the age field as ID-level precision.

Platform ID field: the role of tgid, wsid, uid, etc.

In addition to the number itself, the screening result is often accompanied by a unique identifier assigned to the user by the target platform, such as:

• tgid: Telegram user’s unique ID
• wsid: WhatsApp user unique ID
• uid: Line user unique ID
• zalo_id: Zalo user unique ID

The main uses of these IDs include:

1. Precise message push: In some interfaces that allow messages to be sent through IDs, IDs can be used to directly reach users and avoid relying on numbers.
2. Duplication Management: The same user may appear repeatedly in multiple numbers, and ID can be used to remove duplicates across tasks to avoid duplicate detection.
3. Blacklist Control: Add blocked or invalid user IDs to the blacklist, and automatically exclude them from subsequent screenings.
4. Secondary analysis: Associate the ID with your CRM system to conduct further user portrait analysis.

Important: Platform ID is sensitive data, please do not disclose it to third parties. KK-DATA supports choosing whether to export the ID field in the task configuration. You can enable it according to actual needs.

How to combine the use of US data fields to optimize the screening task?

After mastering the meaning of each field, you can design an efficient screening process:

1. Step 1: Filter by activation status From the original number list, filter out the numbers “activated” on the target platform and remove invalid numbers.

2. Step 2: Narrow the scope based on activity Depending on the marketing scenario, select specific active windows (e.g. 7 days, 30 days) to further filter high-potential numbers.

3. Step 3: Target people by gender and age If you need to target a specific group of people (such as men aged 25-35), filter on the gender and age fields. Note that the age field is filtered by a range, not an exact value.

4. Step 4: Use platform ID to remove duplicates If you have accumulated leads before, you can import the historical ID list to remove duplicates and avoid paying for the same user twice.

5. Step 5: Export and apply Export final filter results to CSV or TXT and import into your mass messaging tool or CRM for follow-up.

When using files exported from KK-DATA, please double-check column names against this dictionary. The fields returned by different detection types may be slightly different, but the core fields (activation, activity, gender, age, ID) are basically the same. If you encounter an unrecognized column name, you can check the Usage Documentation or contact customer service.

FAQ

**Q: What exactly does the “activity” field of a US number refer to? ** Answer: The “Activity” field usually displays the number’s most recent activity time or frequency on the platform, such as “Active in the last 7 days”, “Active in the last 30 days” or “Active times per week”. The specific unit is based on the column name exported by the KK-DATA console, which is commonly seen as last_active_days or active_freq.

**Q: How accurate can the age field be? How do I screen for US users who are around 30 years old? ** Answer: The age field provides numerical values or age groups inferred by the algorithm, which are not ID card-level accuracy. You can set up a range filter (such as 25-35 years old) to target people around 30 years old. It is also recommended to combine the gender field to further narrow the scope. In KK-DATA, Telegram gender detection will contain age data, which can be used for such screening.

**Q: What are the uses of tgid and wsid? Can it be exported? ** Answer: tgid is the unique identifier of the Telegram user, and wsid is the user identifier of WhatsApp. After exporting, it can be used for deduplication, accurate message push, or secondary data analysis outside the platform. The export option can be selected in the task configuration, but please be careful not to disclose these IDs to untrusted third parties.

**Q: Does the “activated” status of different platforms have the same meaning? ** Answer: Not the same. Telegram activation only means that the number has registered an account; WhatsApp activation means that the number exists on the WA network; Line’s “valid” needs to be associated with a uid; Zalo activation means that there is a Zalo account. Understanding the differences in definitions for each platform is fundamental to the correct use of U.S. data.

**Q: What should I do if the status shows “unknown”? ** Answer: “Unknown” usually means that it cannot be determined during the detection process (such as network timeout, platform unresponsiveness). If the number of such numbers is small, it is recommended to eliminate them directly; if the proportion is high (such as more than 5%), you can try to resubmit the detection task, or contact KK-DATA customer service (https://t.me/kkdata_robot) to confirm the reason.

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Through the explanation of this article, I hope you have a clear understanding of the field dictionary of US Data. Whether you are filtering Telegram, WhatsApp or Line numbers, understanding the meaning of the fields can greatly improve your customer acquisition efficiency. Log in to the console now and start your first screening task!

👉 Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot For more usage tips, please refer to Document Center