Acceptance standards for TG male numbers delivered by agents: How to ensure that the studio gets real and usable data?

In the overseas customer acquisition chain, TG male numbers are the core resource for Group private messages, channel promotion, and one-to-one contact. Many studios have signed long-term cooperation with agency operation teams and receive hundreds of thousands of numbers every month. However, during actual delivery, they often find that: the opening rate is not as good as expected, the gender accuracy is erratic, and a large number of numbers are “zombie numbers.” The root cause of the problem is often not intentional fraud on behalf of the operator, but rather the failure of both parties to establish unified acceptance standards before delivery.

This article is aimed at marketing studios that receive data, and establishes a practical tg male number acceptance process from the four dimensions of activation rate, gender accuracy, activity, and deduplication rate. Whether you are cooperating for the first time or you already have a stable supply chain, this set of standards can help you quickly identify data quality and reduce invalid delivery.

Why is it easy for agents to deliver TG male numbers to “overturn”?

The agent operation market is a mixed bag, and even the compliance team faces two natural bottlenecks:

• Number Source Difference: Some providers use global number generators to mix in unregistered numbers, and the activation rate may be less than 50%.
• Limitations of the gender detection model: tg gender recognition is inferred based on public information such as user nicknames, avatars, usernames, etc., and the accuracy of different models varies greatly. Some low-profile detection reports a large amount of “unidentified gender” data as male, resulting in delivery data containing a large number of female or invalid numbers.
• Duplicate delivery: Agency operations often merge multiple data sources and deliver them directly without deduplication, resulting in the studio receiving the same batch of numbers multiple times.
• Ambiguous definition of activity: The “active” time window has not been agreed upon, and the agent operation may deliver active data 90 days ago, which is actually invalid.

Therefore, when delivering tg male numbers on behalf of operators, the studio must proactively establish acceptance standards to avoid the loss of “invest first and discover later”.

What are the core indicators for accepting TG male numbers?

The following four dimensions are the cornerstone of any acceptance process. It is recommended to clearly stipulate the minimum value of each dimension in the contract, which not only protects the interests of the studio, but also gives clear delivery guidelines to the agent operation.

Acceptance Dimensions	Recommended Qualification Criteria	Description
Opening rate	≥70%-80%	Proportion of successfully registered Telegram numbers
Gender accuracy rate	≥80%	Proportion of real men among identified men
Activity (last 7 days)	≥60%	Proportion of login records in the last 7 days
Data duplication rate	≤5%	Cross-batch number duplication ratio

1. Opening rate - is the number truly registered?

Opening testing is the most basic link. If a number does not have a registration record on the Telegram server, all subsequent marketing actions will be a waste.

During acceptance: sample 500-1000 items, and use a professional screening platform (such as KK-DATA) to re-test the “tg activation” field. If the proportion of “not activated” in the test results exceeds 20% (that is, the activation rate is lower than 80%), it is recommended to ask the agent to provide original test screenshots or re-screen the number.

2. Gender recognition accuracy and field credibility

tg gender detection is not equal to real-name authentication. Most platforms (including KK-DATA) use algorithms to analyze account public information to infer gender. The accuracy is greatly affected by language, region, and avatar style.

Upon acceptance:

• Ask the operator to explain the detection model and data source used (for example, using a three-in-one model of avatar + nickname + username, the accuracy is usually higher).
• Sample 200 numbers whose gender is marked as “male” and manually check whether the avatar (such as cartoon, landscape, team logo) matches male characteristics. Avatars with no obvious male characteristics can be counted as “edge cases”, but if more than 20% of the numbered avatars are obviously female or non-characters, the gender accuracy rate is judged to be substandard.
• Common error scenarios: Some female users in Southeast Asia use neutral nicknames and cartoon avatars, which are easily misjudged as “unidentified” or “possibly male”.

It is recommended to stipulate in the contract that the gender accuracy pass line is 80%, and batches that do not meet the standard will be rescreened proportionally or negotiate discounts.

3. Activity – can it actually reach users?

Activity is a key indicator of whether a number is “useful”. Numbers that were online more than 30 days ago may have changed devices or are no longer active. It is recommended to use “online behavior within the last 7 days” as the active criterion.

Upon acceptance:

• Use the “tg active” function of the screening number platform, specify a “7-day” window, and re-test the sampling number. Compare the activity rate of agent operation delivery.
• If the delivery target is “7 days active” and the activity rate in the random inspection results is less than 60%, it means that the agent operation may have used data recharge in a longer window (such as 30 days, 90 days).
• Note: The higher the activity, the higher the screening cost (more frequent server requests are required). This point needs to be communicated in advance during the operation quotation and working hours evaluation.

Acceptance process: 4 steps from data receipt to bottom line verification

A standardized acceptance process can align the goals of both parties. The following are steps that can be directly reused by the studio:

• Step 1: Basic attributes of sampling statistics Randomly select 1000 items from the delivery data (or 5% of the total data, whichever is greater). Check: number format (country code + mobile phone number, no blank lines), whether the country/region is consistent with the target market, and whether each number is unique (check before deduplication).

• Step 2: Connect with third-party tools for secondary verification Use a professional platform such as KK-DATA to create a new screening task, import the sampling number, and select the detection type: tg开通 + tg活跃（7天） + tg性别. After the task is completed, compare the two data:

  • The activation rate delivered by agent operation vs. the actual activation rate measured by sampling
  • Activity delivered by agent operations vs. sampling measured activity
  • Proportion of “masculine” gender markers vs. measured proportion of men If there is a significant deviation between the two dimensions (such as a difference of more than 15% in the opening rate), it is recommended to initiate an objection process.

• Step 3: Deduplication Import the current batch number into the data deduplication warehouse or local deduplication tool. Statistical duplication ratio with historical delivery data. The portion with a repetition rate exceeding 5% can be directly claimed for deduction.

• Step 4: Summary Report Organize the results of the third step into a brief report, attach a screenshot of the sampling data, and send it to the agent operator for confirmation. After both parties sign or reply to confirm, the subsequent delivery plan will be implemented.

Common acceptance disputes and handling suggestions

Even if there are acceptance criteria, there are still several points that are easy to argue with in practice:

• **Controversy 1: Is the source of substandard gender accuracy a model problem or a supplier problem? ** Suggested handling method: Both parties negotiate to use the same screening platform as the “arbitration benchmark”. For example, it is agreed that the test results of KK-DATA shall prevail. Before the test, both parties jointly confirm the sampling list to avoid disagreement.

• **Dispute 2: The agent operation said “there is a delay in activity detection”, which the studio did not accept. ** Suggested handling method: clarify the execution time of the acceptance test. If the studio completes random inspection within 24 hours after the data is delivered by the agent operation, the data discrepancy shall be attributed to the agent operation; if the sampling interval exceeds 48 hours, the difference may be caused by changes in user online behavior, and both parties will bear half of the responsibility.

• **Controversy 3: A random inspection by the studio found that 20% of the numbers were female or unidentified, and all were required to be redone. ** Suggested handling method: refer to the gender accuracy rate stipulated in the contract. If the exceedance is within 5%, negotiate a discount or deduct the next cost; if the exceedance exceeds 10%, rescreen according to the proportion of exceedance. Avoid the overly costly approach of “re-doing everything”.

How to improve the delivery quality of TG male numbers from the source?

Acceptance is only an afterthought. If the agency operation team can adopt more scientific strategies in the screening process, the delivery quality will naturally improve:

1. Choose a platform that supports multi-dimensional simultaneous detection: One-time detection of tg activation + tg active + tg gender to reduce data loss caused by running multiple tasks. KK-DATA supports checking multiple detection types at the same time in a single task.
2. Use global numbers to generate default number segments: Before filtering, generate the number segment of the target country (such as the United States +1, Indonesia +62), and then screen these numbers to increase the hit rate of registration numbers and active numbers.
3. Set up data deduplication warehouse: Each batch number is checked with the historical warehouse before delivery, and the duplication rate is controlled below 1%. KK-DATA’s deduplication warehouse can automatically deduplicate across tasks to avoid wasting balances through repeated detection.
4. Provide traceable screen number report: The data is delivered with the screen number task ID and timestamp, which is convenient for the studio to check by itself in the Application Console. This detail can significantly reduce the trust cost during acceptance.

Summary: A clear set of acceptance criteria makes cooperation more efficient

The cooperation in operating and delivering tg male numbers is not a one-time trust game. Only when both parties agree in advance on the four core indicators of activation rate, gender accuracy, activity, and deduplication rate and establish an executable acceptance process can cooperation be sustainable and efficient.

For studios: random inspection + secondary verification + contract terms are the most direct way to protect themselves. For agent operations: delivery with original screen number reports and the use of a high-precision testing platform can reduce after-sales disputes and win more long-term orders.

Regardless of role, choosing professional inspection tools is a lever of efficiency. If you want to personally verify the true quality of a batch of numbers, or need to complete activation, activation, gender detection and deduplication in one stop, you can start here.

👉 Log in to the console to start screening numbers Two-way contact customer service: https://t.me/kkdata_robot Official website: https://kkdata.cc/ Usage documentation: https://docs.kkdata.cc/