US Active WS Number Delivery Acceptance Checklist: 5 Key Criteria Ensure Data Availability

Q: The US active ws number file I received only has the phone number and no active field. How can I determine whether it is really an active number?

The results of active detection are usually reflected in the status or activity fields (such as status:active or activity:true). If the file does not contain any status fields, the detection type may only be "Open" instead of "Active". It is recommended to contact the delivery party to confirm the test type and request complete field data.

#US Active WS Number Delivery Acceptance Checklist: 5 Key Criteria to Ensure Data Availability

When you spend your budget to buy US active ws numbers (that is, US active WhatsApp numbers), what you are most afraid of is not that there are not enough numbers, but that the data you get will “overturn” as soon as you use it - the number cannot be opened, the active time does not match, the fields are incomplete, the repetition rate exceeds the standard… These pitfalls not only waste detection costs, but also directly reduce the reach rate and conversion effect of subsequent private messages.

Therefore, before importing data into a CRM or mass sending tool, there must be a set of implementable acceptance standards. This article has compiled a 5 key acceptance list for you, covering file format, field integrity, repetition rate, timestamp and detection type, to help you quickly determine whether this batch of US WS active numbers are actually available.

What is \'US Active WS Number\'

Numbers within the US area code (+1) range that have registered for WhatsApp and have used it within a specified time period (such as the past 7 days, 15 days, and 30 days). The core of acceptance is to confirm whether the “active” test results are true and complete.

Why do we need a US active ws number acceptance criteria?

Overseas customer acquisition teams often encounter the following scenarios:

Get a batch of CSV from the service provider. When you open it, it only has the mobile phone number and no status/active field. It is impossible to distinguish whether it is “activated” or “active”.
More than 10% of the lines in the file contain duplicate numbers, causing the actual usable volume to shrink.
The active timestamps are concentrated one year ago, which is not the “active in the last 30 days” as agreed in the contract.
The gender fields are all empty, but gender recognition was checked when paying.

Without acceptance criteria, it means you can only use the data “on the fly”. After spending a lot of time importing tools and starting marketing, the problem was discovered, and the losses had already been incurred. Therefore, investing 15 minutes for system acceptance before data is stored in the database is the basic skill that an overseas customer acquisition team should have.

What is a US active ws number? Common detection types and field interpretation

To accept correctly, you must first understand the meaning of each field in the data file. Different detection schemes will output different combinations of fields.

The difference between Open/Valid and Active

Detection type	Meaning	Typical status values
Activate detection	Verify whether the number is registered with WhatsApp	`open:true` or `status:valid`
Activity detection	Verify that the number has been used within the specified time window (such as sending messages, going online, etc.)	`status:active`, `activity:true` or `activity_last_seen:2025-02-10`

Key point: When accepting, be sure to confirm that what you purchase is “active” rather than just “activated”, because the number that is only activated may have been abandoned and the reach rate is much lower than the active number.

Typical field list for US WS active numbers

Taking the CSV exported by the KK-DATA console script as an example, common fields include:

phone_number — Complete mobile phone number (including country code)
country_code — Country code, “1” or “US” for the United States
status — Test results (active / open / invalid)
activity_last_seen — Last active timestamp
timestamp — Time point of detection execution
gender — Appears if gender detection is checked, the value is male / female
age — Appears if age detection is checked, as a numerical value or age group
waid — WhatsApp ID (if exported)
profile_name — Some tests can output nicknames

The fields are subject to actual export from the console.

The fields output by different detection packages and different platforms (Telegram/WhatsApp/Line, etc.) may be different. Before acceptance, please check the order instructions or documents to confirm which fields should be included.

The first item in the acceptance list: number, format and size of files

File quantity: consistent with the order agreement (e.g. “1 CSV” or “Split into 5 TXT”).
File naming: Have clear rules (such as US_active_ws_250213.csv) to avoid garbled characters or unknown abbreviations.
Number of rows: The number of exported rows should be close to the order commitment quantity (an error within 5% is allowed). If it is less than 20%, it means that the detection is missed or the filtering conditions are too strict.
Encoding: It is recommended that CSV be UTF-8 or UTF-8-BOM to avoid Excel opening garbled characters (especially when it contains emoji or non-English characters).
Headers: The first line of CVS should contain column names; TXT usually has only numbers without headers. You can ask the service provider to provide additional field descriptions during acceptance.

建议验收工具：记事本或VS Code查看文件首尾行；Excel导入用“数据→自文本/CSV”避免手机号截断。

The second item in the acceptance list: field integrity & missing rate

For each number, check whether key fields are missing. For acceptance, it is recommended to use Python script or Excel’s COUNTA function to count the missing proportion.

Key field acceptance threshold recommendations

Field	Recommended upper limit for missing rate	Description
`activity_last_seen` (active timestamp)	< 3%	If the order contains active detection, a high missing rate indicates incomplete detection results
`gender` (Gender, if included in the order)	< 10%	Numbers with unclear avatars may not be able to identify gender, but should not be missing on a large scale
`country_code`	< 1%	Should all be `1` or `US`
`status`	< 1%	Each row should have a status value

Does WhatsApp ID (waid) exist?

If the order contains a waid field (WhatsApp internal ID), check whether each row has the ID during acceptance, and the format is a numeric string or a unified format (such as pure numbers). The lack of waid may result in the inability to accurately correlate the user’s subsequent behavior.

The third item in the acceptance list: Duplicate number detection

Duplicate numbers directly waste detection fees and subsequent operating costs.

Remove duplicates within the same file: Use Excel’s “Delete Duplicates” or Python’s drop_duplicates() to count the proportion of duplicate rows to the total number of rows.
Cross-file deduplication: If you have a US number database before, cross-compare the new data with the old database to avoid repeated purchases.
Deduplication with marked batches: If you are using KK-DATA, you can import historical batches in the Data Deduplication Warehouse in advance, and new tasks will automatically skip the detected numbers.

Repetition rate processing suggestions

If the internal duplication rate of a single batch of files exceeds 10%, it is recommended to contact the service provider to request deduplication and reissue. The higher the repetition rate, it means that the data cleaning is not thorough.

The fourth item in the acceptance list: timestamp & detection window consistency

The active timestamp is the core to determine whether “active” is true or not.

Confirmation Window: Check whether the date in the activity_last_seen field falls within the order’s agreed active window (e.g. all timestamps are between January 15, 2025 and February 15, 2025).
Check Continuity: If the timestamps are all concentrated on a certain day, it may be that the service provider is using batch detection instead of the real active window, and you should be wary.
Quick verification method: Sort the date column in Excel and view the minimum and maximum values; or use the formulas =MIN(列) and =MAX(列).

Next step after acceptance is completed

After the acceptance is passed, it is recommended to immediately mark the batch as used in the KK-DATA data deduplication warehouse to avoid repeated detection and waste of balance in subsequent tasks.

Item 5 of the acceptance list: The detection type matches the actual data

This is the easiest place to get into trouble: the order says “US Active WS Number”, but the status field for a large number of numbers in the file is open instead of active.

Check Ratio: Statistics of the proportion of numbers that status is active. Theoretically it should be ≥95% (a small amount may return open due to detection failure). If the active ratio is lower than 80%, it means that the actual delivery is a “US-opened account” rather than an “active account”.
Check status field definition: If the field only has two categories: valid and invalid, and there is no active, it means that no active detection has been performed, and supplementary testing or refund should be requested.

Tips

Different detection systems may name status differently (such as active:true / is_active:1). Requesting field description documents before acceptance can avoid misunderstandings.

FAQ

**Q: The US active ws number file I received only has the phone number and no active field. How can I determine whether it is really an active number? **

A: The results of active detection are usually reflected in the status or activity fields (such as status:active or activity:true). If the file does not contain any status fields, the detection type may only be “Open” instead of “Active”. It is recommended to contact the delivery party to confirm the test type and request complete field data.

**Q: If the duplication rate exceeds 15% during acceptance inspection, can I request re-delivery? **

Answer: Yes. Please keep the original documentary evidence and indicate the specific line number range of the duplicate number. Most regular service providers will remove duplicates and reissue them once after confirmation.

**Q: How long is the active window for active WS numbers in the United States? **

Answer: Common windows are “past 7 days”, “past 15 days” or “past 30 days”. The specific active time period pre-agreed on the order shall prevail. It is recommended to compare the timestamp with it during acceptance.

**Q: The gender fields in the received data are all empty. Is this a data quality issue? **

Answer: It depends on whether the order includes gender testing. If gender detection is not checked on the order, this field will not be generated; if it is checked but the missing rate is extremely high (such as more than 90%), it is a quality problem and you can request a retest or a partial refund.

**Q: Can I use Excel to open CSV directly for acceptance? **

Answer: Yes, but please note that Excel may truncate long numbers (such as mobile phone numbers). It is recommended to use “Data → From Text” to import or format the column as text before opening it.

After accepting the US active ws number data, your next step is to import the tool and start acquiring customers. If you need to batch generate, filter, and remove duplicate US active ws numbers, you can log in to the KK-DATA console to operate directly. 👉 Log in to the console to start screening numbers; Two-way contact customer service https://t.me/kkdata_robot; For more usage guidelines, see Document.