After testing 50,000 accounts, we found that only 38% of TG’s effective users

In the imagination of many people,Telegram's data pool is almost "infinite". As long as you have enough account data, you can continue to expand your marketing scale. But the real situation is far from that simple.

on one occasion 50,000 TG accounts In the detection experiment, we found a result that surprised many operations teams:Only 38% of real effective users are.

In other words, among the seemingly huge account data, more than half of the data actually has no actual marketing value.

This is why more and more teams are beginning to pay attention to TG effective user detection screening material. Before official promotion, it has become a standard process for many projects to screen out truly effective accounts through data detection.

This article will be passed Detection cases for 50,000 accounts, dismantlingThe core logic of TG effective user screening.

one,50,000 TG account detection experiment

In this experiment, we imported a batch of 50,000 TG account data, and conducted basic testing. Detection dimensions include account status, active records, and whether messages can be received normally.

After the test is completed, the data results are very clear.

About 38% of the accounts are valid users. These user accounts are in normal status, have recent online records, and have certain interactive behaviors.

Another part of the accounts are low active users. Although the account exists, there is almost no record of any interaction.

There are also quite a few accounts that are invalid data, such as empty accounts, banned accounts, or accounts that have been canceled.

In other words, if thisIf 50,000 accounts are directly used for promotion without screening, then at leastMore than 60% of marketing resources may be wasted.

two,3 common types of invalid TG accounts

During the testing process, we foundTG invalid accounts can generally be divided into three main types.

Empty account

The empty number isThe most common type of invalid account in TG data.

This kind of account appears to exist in the data list, but is actually no longer available. Some accounts may be records left after users log out, and some accounts may not exist from the beginning.

If the marketing data contains a large number of empty numbers, the success rate of message sending will be significantly reduced.

Ban account

Another common situation is that the account is banned by the platform.

These accounts are usually restricted due to violations or abnormal operations. For marketing purposes, such accounts have almost no value.

During the data screening process, these accounts need to be filtered out as soon as possible.

Zombie account

Zombie accounts are usually accounts generated by batch registration.

Although such accounts can be logged in, they rarely produce real interactions, such as not participating in group discussions and not actively sending messages.

During the promotion process, these accounts often do not bring any conversions.

3. How to judgeTG valid users

In order to improve data quality, inDuring the TG screening process, multiple indicators are usually used to determine whether the user is effective.

first isAccount status detection. Only accounts in normal status have value.

followed byActivity detection. If the user has online records in the recent period, it means that the account is still in use.

You can also observeinteractive behavior, such as whether you have participated in group discussions, whether you have subscribed to channels, etc.

When an account meets these conditions at the same time, it can usually be considered a valid user.

4. Why batch testing is becoming more and more important

along withThe scale of TG marketing continues to expand, and the amount of account data is also increasing.

If you only detect dozens of accounts, manual processing can be barely completed. But when the data scale reaches Tens of thousands or even hundreds of thousands of accounts At this time, manual detection is almost impossible.

For example, if manual detection of each account requires5 seconds, then detect50,000 accountsJust need to be close70 hours.

This is why more and more teams are beginning to use automated detection tools to screen materials.

The automated system can complete batch detection in a short time and automatically identify empty accounts, banned accounts, and low-active accounts, greatly improving screening efficiency.

5. How to improveTG effective user screening efficiency

In actual operations, the most direct way to improve screening efficiency is to use a professional detection system.

For example Digital planet screening system, just supportTG account status detection, empty account identification, active user screening and other functions. Through batch detection, invalid accounts can be quickly filtered out and truly valid user data can be retained.

For users wishing to test data quality,Digital Planet currently provides a free trial screening test service. Before official use, you can import some accounts for testing and understand the data situation. You can consult customer service for specific trial methods.

In this way, teams can understand data quality before promotion, thereby reducing unnecessary waste of resources.

Conclusion

this time 50,000 TG account detection experiment in, only 38% of the accounts are valid users. This result shows that inIn the TG marketing environment, data quality problems are far more serious than many people think.

Without screening, a lot of marketing resources are likely to be wasted on invalid accounts.

Therefore, more and more teams have TG effective user detection screening material as the first step in the operational process. By filtering effective accounts, promotion efficiency can be significantly improved and every contact can be made more valuable.

in the futureIn the TG marketing competition, whoever can identify high-quality users faster will have a better chance of achieving real growth.

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