TG Active Data Screening Pitfall Guide: 6 Common Misunderstandings in Overseas Marketing

#TG Active Data Screening Pitfall Guide: 6 Common Misunderstandings in Overseas Marketing

When doing Telegram community marketing or private messaging, the first step is to screen for high-quality TG activity data. But are the numbers you screen out really “active”? Many teams spend a lot of budget, but what they get is a large number of dead accounts that cannot be reached, or the delivery effect is dismal due to misreading the fields. From a practical perspective, this article breaks down 6 common misunderstandings in overseas marketing in Telegram screening, and provides a reusable operation checklist to help you avoid pitfalls, reduce costs, and improve efficiency.

Misunderstanding 1: Mistaken “activated” as “always active”

Many operators think that a mobile phone number registered with Telegram is equivalent to an active user, and they directly use the tg activation test results to send group messages or private messages. As a result, the reach rate was less than 20%, and the account was blocked for unknown reasons.

Why is the activated status not equal to active? Understand the types of TG detection in one picture

KK-DATA’s Telegram screening code includes two major types of detection:

tg activation detection: only verify whether the number has registered a Telegram account. Even if you haven’t logged in for six months after registration, it will still show “activated”.
tg active detection: Verify whether the number has logged in or used Telegram within the specified time period. For example, “7 days active” means there has been activity in the past 7 days.

Detection type	Meaning	Applicable scenarios
Activation	Registered TG account	Basic verification, only determines the number ownership
Active (7 days/14 days/30 days)	There are activities within the designated window	Group sending, private messages, event contact

The activity level is wrong. Why can’t a large number of numbers be reached?

Suppose you choose tg to activate data. After importing the group sending tool, only 60% of the numbers have actually logged in recently. The remaining 40% are either zombie accounts (never used after registration) or have been banned. Result:

A large number of group messages are returned, affecting the sending efficiency.
The private message was judged by the system as “high-frequency invalid contact”, resulting in account risk control.
The cost of each test is wasted (the unit prices for activated tests and active tests are different).

Correct approach: Select the corresponding TG activity data according to the touch scenario. Group notifications can be active for 30 days, and private message conversions are recommended to be active for 7 days.

Misunderstanding 2: Can tg’s 30-year-old data really accurately locate “30-year-old” people?

Many users see “30 years old” displayed in the KK-DATA report and think that this is the accurate age at the ID card level. In fact, Telegram’s gender/age field is reference data based on account public information and behavioral model inference, which is not 100% accurate.

Interpretation and correct usage of KK-DATA gender/age field

Age field: The approximate age range is given through a comprehensive evaluation of avatar, nickname, language, behavior pattern, etc. For example, “about 30 years old” does not mean that you are 30 years old, but is a biased judgment of 20-35 years old.
Gender field: The accuracy rate is high (avatar/nickname/profile cross-validation), but there are also a few misjudgments (such as using cartoon avatars).
No fiction: The platform does not provide “ID card-level age screening” and has never promised to be accurate to single digits.

How to combine activity level + age + gender to stratify crowd portraits

The correct usage is multi-dimensional combination rather than relying on a single field:

Screen active first: 7 days or 30 days to eliminate dead accounts.
Re-screen gender/age: For example, “female + about 30 years old”, as a high-intention group.
Retain tgid when exporting: to facilitate subsequent behavioral analysis within the community.

After stratifying in this way, you can get a batch of numbers that are “recently active and fit the profile”, and the interaction rate after reaching them is significantly higher than that of random groups.

Misunderstanding 3: Don’t differentiate between scenarios, and use one set of parameters to cast all

The same team uses the same set of active parameters for brand notifications, promotional activities, and personal privacy, but the result is always to lose sight of the other.

Active window suggestions for different scenarios

It is recommended to balance the reach cost and conversion rate:

Brand exposure/community invitation: active for 30 days (wide coverage, low unit price)
Private message conversion/high-value activities: active for 7 days (high accuracy, better interaction rate after reaching)
First time customer acquisition: First use 30 days of active batch coverage, and downgrade high-click groups to 7 days of re-screening.

Actual case: An overseas e-commerce company used 7-day active data to send promotional private messages. The interaction rate was 40% higher than that using 30-day active data, but the coverage was reduced by about 50%. If the goal is large-scale brand exposure, it is more cost-effective to be active for 30 days. Therefore, set the scene first and then select the parameters.

Misunderstanding 4: If you don’t look at the time zone, task data sent early in the morning will become worse.

The tg activity detection result depends on the latest login time of the target number. If your target audience is concentrated in the Americas, and you submit a detection task at night in the Chinese time zone, the detection server may only record the activity data from the day before the target time zone, resulting in a low activity rate.

Relationship between activity detection and target audience active time

It is recommended to conduct screening according to time zones:

For Middle Eastern and European audiences: Submit tasks in the morning of Beijing time (corresponding to local morning).
For American audiences: Submit at night in China (daytime in the Americas).
Submit in batches by country/region in the KK-DATA console, and each task specifies a different active window.

If you don’t want to manually divide time zones, you can first use “30 days active” to screen them uniformly, and then refine them by region according to the reach stage. Remember, it is best to concentrate the same billing country number in active detection tasks during the same period to reduce time difference deviation.

Misunderstanding 5: Without deduplication, repeated detection wastes balance

Many users import hundreds of thousands of numbers at once and submit number screening tasks in batches, but forget that these numbers may overlap. As a result, the same number was detected multiple times and the balance was wasted.

KK-DATA has built-in data deduplication warehouse function: when submitting a new task, you can choose to “filter detected numbers”. The system will automatically compare historical task records, skip the numbers that have been detected, and only deduct new ones. For long-term operating teams, this can save 20%-40% of screening costs every month.

Best Practice: Create a deduplication warehouse in the “Number Management” console, upload the deduplication before each import of new data, and then generate a screening task. The deduplication itself is free and is only billed on a per-item basis during the final inspection.

Misunderstanding 6: Screening the number is enough, lack of follow-up verification

After getting the tg active data, directly import it into the group sending tool and it’s over? This is the biggest waste. Screen number is only the first step, the real value lies in data closed loop.

Tracking Feedback: Record which numbers are successfully reached (read, replied, clicked), and compare the hit rate of active fields.
Correction parameters: If the reach rate of 7-day active data is lower than that of 30-day active, it means that your active window setting is wrong.
Update Expired: The active status will change over time. It is recommended to rescreen the core number every 2-4 weeks.

For example, a community operation found that 30% of the numbers had unread messages in the 7-day active data. Further analysis found that these numbers had only logged in once after registration. Although they were “active”, they were actually “one-time users.” So they switched to “logging in ≥ 2 times within 7 days” as the activity criterion (KK-DATA supports customizing the activity frequency, see the console for details). After optimization, the reach rate increased from 62% to 89%.

How to establish a standard screening process? (Includes checklist)

Based on the above six misunderstandings, the recommended standardization process is as follows:

Clear scenario: Brand exposure? Private message conversion? Event invitation?
Select active window: Select 7 days/14 days/30 days according to the scenario.
Configure deduplication: Enable “Data Deduplication Warehouse” in the console.
Submit by time zone: Submit in batches by country/region and select the active time in the corresponding time zone.
Export fields: At least include mobile phone number, activity status, tgid, and gender/age if necessary.
Verification before importing the tool: Randomly select 100 numbers and manually send test messages to confirm validity.
Review after contact: Record the feedback data and adjust the next screening parameters.

Checklist (printable):

Reaching scenarios have been defined (exposure/conversion/invitation)
active window selected (7d/14d/30d)
The deduplication warehouse has been opened and historical data has been uploaded
Tasks are batched by time zone (Middle East/Europe/America)
Export fields checked (phone, active, tgid, gender)
Sampling verification passed (at least 100 items)
The subsequent re-screening time has been set (recommended 2 weeks)

FAQ

**Q: Will the active status of a mobile phone number change? How often does it take to rescreen? ** Answer: It will change. The active status of tg is affected by factors such as user usage habits, account bans, device changes, etc. It is recommended to re-screen the activity of high-value numbers every 1-2 weeks according to the marketing rhythm, and the remaining numbers can be updated every 30 days.

**Q: Can the filtered TG activity data be directly imported into other group sending tools? ** Answer: Yes. KK-DATA supports CSV and TXT format export, and the export fields include tgid, mobile phone number, active status, etc. Most mass sending tools support batch import of these formats without secondary cleaning. It is recommended to remove duplicates in the tool before importing.

**Q: Why is it sometimes detected that TG is activated but there is no user avatar? ** Answer: The avatar field is part of the tg gender detection product. If your task only selects “Enable” detection, additional information such as avatar and username will not be returned. For richer fields, select a task whose detection type includes gender. An empty avatar does not mean the number is invalid.

**Q: Should I choose to be active for 30 days or 7 days for overseas marketing? ** Answer: It depends on the touch scene. Mass notifications/brand exposure can be active for 30 days (wider coverage); private message conversion/high-cost activities are recommended to be active for 7 days (high accuracy, better interaction rate after reaching); first-time customer acquisition can be screened for 30 days of activity, and then downgraded to 7-day monitoring for high-converting groups.

**Q: Why are the unit prices of active detection different on different platforms (TG/WhatsApp/Line)? ** Answer: Each platform has different detection costs, technical difficulty, and data source stability, so the unit price is different. Please refer to the real-time price on the KK-DATA console for the specific unit price. The estimated deduction will also be displayed before submitting the task.

Verify your tg active data screening process now

If you are also engaged in TG community operations or overseas outreach, you may wish to run through the above checklist with a real number to see how many pitfalls you have encountered in the current process. Clarifying the requirements before screening, choosing the right active detection parameters, making good use of deduplication warehouses, and configuring tasks in time zones are the keys to controlling costs and improving reach rates.

👉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/