US Data Delivery Acceptance Checklist: A Complete Guide to File Numbers, Fields, Duplication Rates and Detection Types

Obtaining high-quality U.S. data is the basis for efficient customer acquisition for overseas marketing teams, but how to accept the data after it is delivered is easily overlooked. Many teams get tools to directly import CSV files, only to find that the fields are incomplete, the duplication rate is high, or the activity level is incorrect, which greatly reduces the marketing effect. This article provides a complete list of U.S. data acceptance standards, covering file quantity, field integrity, repetition rate control, timestamp and detection type verification, to help you establish an implementable acceptance process.

Whether you use US data for Telegram group marketing, WhatsApp private messaging, or Facebook ads targeting US users, this set of checklists can help you avoid data waste and cost losses.

---

What are US data acceptance criteria? Why does the overseas team need this list?

The core dimensions of U.S. data delivery acceptance include: file quantity and format, field integrity, duplication rate, detection timestamp, and detection type matching. Establishing a standardized acceptance process is not unnecessary, but a “firewall” for data operations.

Take a typical U.S. customer acquisition scenario as an example: You batch-check 100,000 U.S. numbers through the number screening platform, mark Telegram active users, and then plan to use this batch of data for private message promotion. If it is found during acceptance:

• The tgid is missing in the field, resulting in the inability to send messages in a targeted manner;
• The duplication rate is as high as 15%, and the actual effective users are only 85,000;
• Two weeks have passed since the detection time, and the active status has already changed.

Then the delivery effect will be greatly reduced. Therefore, acceptance is not optional, but a must-have for data-driven marketing.

---

How to check the file quantity and format of US data delivery?

The number and format of files is the first step in acceptance and is also the most easily overlooked link.

Check the number of files and naming rules

The number of files exported by each screening task should be consistent with the volume strategy set when the task is submitted. For example, if you submit a detection task of 1 million numbers in the KK-DATA console and check “Export into volumes every 200,000”, you should eventually receive 5 files (or dynamically divide them into volumes based on the actual number of detections). File naming usually includes task ID, detection platform, country code (such as US) and timestamp to facilitate archive management.

Acceptance points:

• Check whether the total number of files matches the task settings (such as single export, volume export).
• Whether the file name clearly identifies the task ID, platform and country to facilitate subsequent tracing.
• If there are multiple batches, check whether the batch serial numbers are consecutive and there are no missing ones.

Export format and preview

Common export formats are CSV and TXT. During acceptance:

• Open the file with a text editor or Excel, check the first 100 pieces of data, and confirm that there are no garbled characters and the field alignment is normal.
• Check whether the number format is an international format (such as +1xxxxxxxxxx) to avoid format errors affecting subsequent system import.
• Confirm that the file encoding is UTF-8, which is compatible with mainstream CRM and marketing tools.

---

How to verify field integrity of US number data?

Field integrity determines whether the data can be used directly for marketing execution. The core fields contained in the screening results of different platforms are different, and they need to be checked one by one according to the platform during acceptance.

List of required fields: number, status, activity, gender

Taking Telegram’s US screen number as an example, typical fields include:

Field	Business Value
Phone number	Basics of reaching users
tg activation (Registered)	Whether the number is registered with Telegram
TG activity (Online/Last Seen)	User’s recent activity level, used to filter reachable users
TG gender, TG age	Population targeting, such as screening female users or users about 30 years old
tgid	Used for API directed messages

For WhatsApp US data, fields such as wsid, WA activation/active/gender need to be checked. For iMessage detection, you need to confirm “iMessage is valid” and iOS device related fields.

How to determine whether a field is missing or abnormal?

• If a certain field (such as “TG Active”) is all displayed as “Unknown” or “0”, it may mean that the detection task is configured with an inappropriate active window (for example, it is required to be active in the past 7 days but the actual number segment is mostly registered a week ago), or the platform has limited active data sources.
• The proportion of empty field values ​​is too high (for example, 90% of the gender field is empty). It is recommended to recheck the detection type based on the task configuration. For example, if you only select “Activate Detection” without checking “Activity/Gender”, the corresponding fields will not be output.
• Use the Excel filter function to quickly count the proportion of null values ​​in each field. If more than 20% of the fields are abnormal, it is recommended to contact customer service to confirm whether the task is executed normally.

---

How should the repetition rate in US data be controlled and accepted?

Repetition rate directly affects marketing costs and data value. For example, if there are 20,000 duplicates out of 100,000 US data, that means you only get 80,000 unique users, and duplicate detection consumes a lot of budget.

Recommended acceptance criteria: repetition rate less than 5%. If the repetition rate exceeds 10%, the reasons need to be investigated:

• Does the number list you uploaded contain duplicates? (e.g. no deduplication when merging from multiple channels)
• Is the duplication mechanism of the screening platform effective?

Acceptance operation: After exporting, use Excel’s “Delete Duplicates” function or script to count the number of unique numbers, and calculate the repetition rate = (total number - unique number) / total number × 100%.

---

Timestamp and detection type: How to confirm the freshness and accuracy of data?

Data freshness is related to marketing timeliness, and the detection type determines whether you get “activated users” or “active users.”

Detect the meaning of timestamp

The activity status of Telegram and WhatsApp decays rapidly over time: a user who is active today may have become inactive two weeks later. Please pay attention to the following timestamps when accepting:

• Detection completion time: The time when the task is finally completed.
• TG active window: The active determination window set in the task configuration (such as the last 7 days, the last 30 days). If the window is 7 days, but the detection was completed more than 7 days ago, then the data actually reflects the active status two weeks ago, and the validity is reduced.

Detection type check

Confirm whether the detection type configured in the task is consistent with your needs:

• Do you only need to “activate detection” or do you need to “activate + active + gender”?
• Is tgid/wssid export enabled? (for subsequent API operations)
• For platforms such as Line and Zalo, check whether the uid field is output normally.

Acceptance method: Check the “Detection Type” checkbox on the console task details page and compare it with the exported result fields one by one.

---

What are the differences between the US data formats of different screen size platforms?

The U.S. number data involves multiple social platforms, and the field sets of each platform are significantly different. During acceptance, it needs to be checked against the platform’s exclusive field list.

Telegram US data field set

Typical fields include:

• tgid: Telegram’s unique user ID, used for API targeted sending.
• tg activation: registration status (yes/no).
• TG active: judged according to the active window (such as online in the past 7 days).
• TG Gender: Gender based on model interpretation (male/female/unknown).
• TG Age: Interpretation of age groups such as about 30 years old, not accurate to the specific age.
• Avatar: Whether there is an avatar (used in some marketing scenarios to determine the completeness of the account).

WhatsApp and iMessage US Data Field Set

• WhatsApp: wsid (WhatsApp unique ID), WA activated, WA active, WA gender. Note: WhatsApp active window is usually different from Telegram (e.g. online for the last 24 hours).
• iMessage: It is necessary to check the “iMessage valid” field (whether the number supports iMessage), and the “iOS device” related fields (such as device model, system version, provided by some tests).

Acceptance Suggestions: Design field checklists separately for each platform to avoid mixing them. For example, if your goal is to send an iMessage to users in the United States, you must ensure that the “iMessage Valid” field is present and not empty.

---

How to systematically accept US data? A checklist is enough

Summarize the key points of the above sections into a reusable acceptance list, and the team will check each item one by one each time it receives data:

Acceptance items	Inspection content	Passing standards
Number of files	The number of files is consistent with the task settings	Compliant
File naming	Contains task ID, platform, country code	Clear
Format encoding	UTF-8, CSV/TXT can be opened normally without garbled characters	Yes
Field integrity	Check the non-empty ratio of core fields by platform ≥ 80%	Yes
Repeat rate	Proportion of unique numbers ≥95%	Yes
Detection timestamp	Detection completed within 7 days	Yes
Detection type	Consistent with the actual checked type	Yes
Number format	International format +1xxxxxxxxxx	Yes

You can create this list into a form or document, which will be filled out by operations personnel after each data delivery. If an item fails, immediately investigate the cause and contact the customer service of the screening platform.

---

FAQ

**Q: What should I do if the number of files is less than expected when US data is delivered? **

Answer: First check whether “Export in batches” is selected when submitting the task. If the task is set to export all results at a time but multiple small files are received, it may be that the system automatically divides the files into volumes. If the quantity is obviously wrong, it is recommended to check whether the console task status is “Completed” or contact customer service to confirm whether the task was terminated midway due to insufficient balance.

**Q: Can KK-DATA’s deduplication warehouse guarantee zero duplication of exported data? **

Answer: The deduplication warehouse mainly reduces the probability of repeated detection of the same number between tasks, but it cannot completely eliminate the duplication of numbers within the same task (for example, the number list you uploaded already contains duplicate numbers). It is recommended to use Excel or script to remove duplicates during acceptance to ensure that the final data is unique.

**Q: How accurate are Telegram’s gender detection results? **

Answer: Telegram does not disclose the user’s gender field. KK-DATA’s gender detection is based on account public information and model interpretation. It is not guaranteed to be 100% accurate, but it can be used for crowd targeting reference (such as screening out women or users about 30 years old to deliver specific content). It should not be equated to ID card-level accuracy when accepting.

**Q: During the acceptance inspection, it was found that the activity of a certain batch of US data was generally low. Is this a data quality issue? **

Answer: Not necessarily. The activity level depends on the activity window you set (such as the last 7 days, the last 30 days), and is affected by the number segment, registration time, and user usage habits. It is recommended to check the active window settings in the task configuration first, and then judge based on the detection timestamp. If the window settings are correct but the results are abnormal, you can try a small batch retest for confirmation.

**Q: What should I pay attention to when accepting bills and fees? **

Answer: During acceptance, you can check the actual number of deductions and the exported quantity on the task details page of the console to ensure that the deductions are consistent with the platform pricing type (see the real-time price of the console for details on the unit price of each platform). If you have any objections, it is recommended to take a screenshot of the task status and expense page immediately after exporting.

---

Accepting US data is the first step to efficiently acquire customers. Log in to the KK-DATA console immediately to submit your first screening task, or contact customer service in two ways to obtain platform documents and one-on-one customization suggestions.

👉Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot