100,000 TG account test results: TG empty number test screening material pit avoidance guide

existIn the Telegram marketing circle, many people have had similar experiences:I bought a batch that looked quite large.As for the TG account data, not much of it can actually be used.

It seems 100,000 account dataHowever, when I actually started to send group messages or reach users, I found that a large number of accounts could not be sent successfully, or even directly prompted that they did not exist. There is often only one reason behind this situation——Too many empty numbers.

The problem of empty numbers has becomeOne of the most common pitfalls in the TG data industry. If there is no detection before promotion, it is easy to waste a lot of time and budget on invalid accounts.

on one occasion 100,000 TG accounts During the detection test, we found a very typical situation:More than 40% of the accounts are empty or invalid accounts.

This article will combine the results of this test to explain clearly TG empty number detection sieve material Why it matters, and how to avoid data traps.

one,Real data after testing 100,000 accounts

In this test, we imported 100,000 TG account data, and conducted batch testing of account status.

The test results surprised many people.

In this batch of data, only approx. About 30% of the accounts are normally usable accounts. These accounts can receive messages normally and have recent login records.

Although some other accounts exist, they have been inactive for a long time and have little interaction.

The largest number of problem data comes from empty numbers. Many accounts are shown as non-existent or unavailable during detection.

In other words, if it is used directly for promotion without screening, then at least More than 40% of the data is completely worthless.

two,Why are there more and more empty TG accounts?

along withThe number of Telegram users continues to expand, and the proportion of empty accounts is also gradually increasing. There are usually several reasons for this.

The first is for the user to log out of their account. Many people registeredTG was only used for a period of time and then the account was deleted. These accounts still exist in historical data, but are actually no longer available.

The second is that the data collection time is too early. Some data packets may have been collected a long time ago, when the accounts were normal, but over time, some users stopped using them.

Another situation is to register accounts in batches. Such accounts usually only exist for a short period of time and will expire soon, so they can easily become empty when detected.

The sum of these factors leads toThe proportion of empty numbers in TG data is getting higher and higher.

3. What problems will the empty number data bring?

Many teams just started doingWhen TG was marketing, they were not aware of the impact of empty accounts. But when the data scale increases, the problem will become more and more obvious.

first isMessage sending success rate decreases. If the data contains a large number of empty numbers, the transmission failure rate will increase significantly.

followed byPromotion costs rise. Many marketing systems charge based on the number sent. If a large amount of data is empty, the budget can easily be wasted.

In addition, too many empty accounts may affect account security. Some abnormal sending behaviors may trigger platform risk control, thus affecting account stability.

Therefore, it has become a standard process for many teams to conduct empty account detection before promotion.

Four,Basic process of TG empty number detection and screening materials

In actual operations, empty number detection is usually completed through several steps.

The first step is to import raw account data, such as group capture data or historical user data.

The second step is to check the account status. The system will determine whether the account exists and can be used normally.

The third step is to filter the empty number data. All unavailable accounts will be automatically identified and removed.

The fourth step is to further screen the remaining accounts, such as detecting activity or interactive behavior.

Through this process, the originally mixed data can be cleaned into a higher quality user list.

5. The Importance of Automated Detection Tools

When the data scale reaches Tens of thousands or even hundreds of thousands of accounts At this time, manual inspection is almost impossible to complete.

For example, if manual detection 100,000 accounts, even if it only takes a few seconds per account, it takes a lot of time.

Therefore, most teams choose to use automated detection systems.

Automated tools can complete batch inspections in a short time and quickly identify:

l Empty account

l Ban account

l Low active account

For example Digital planet screening system, just provideTG empty number detection, account status detection, batch screening and other functions.

For first time users,Digital Planet currently provides a free trial screening test service. Before official use, you can import part of the account data for testing to understand the data quality. You can consult customer service for specific trial methods.

Through automated detection, invalid data can be cleaned up before promotion, thereby improving overall marketing efficiency.

Conclusion

this time 100,000 TG account detection test Among them, the proportion of empty accounts exceeded many people’s expectations. This also shows that inIn the TG marketing environment,Data quality issues have become increasingly common.

Without detection, a large number of empty accounts will not only waste promotion resources, but also affect the overall marketing effect.

Therefore, more and more teams have TG empty number detection sieve material as the first step in the operational process. By filtering out invalid accounts in advance, promotion can be made more precise and every message more valuable.

existToday, as competition for TG traffic continues to intensify, whoever can detect data problems earlier will be more likely to gain an advantage in marketing.

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