Mobile phone number filtering case in the US market: Reaching costs dropped significantly after list cleaning

The volume of data in the U.S. market has always been large, but the larger the list, the more obvious the problems are often. Many teams focus more on obtaining data in the early stage, but only when they start to use it do they realize that a large number of numbers cannot produce effective contacts.

For the same batch of lists, there will be significant differences in contact costs before and after cleaning. The problem is often not with the sending tool, but with the data itself.

Why is U.S. mobile phone number data becoming more and more complex?

There are many sources of data for the US market.

Common ones include:

l advertising leads

l Historical customer data

l third party list

l Social media data collection

After these data enter the same system, it is easy for the structure to become confusing.

For example:

l There are more and more duplicate numbers

l Some numbers have expired

l User status has not been updated for a long time

The longer the time passes, the more obvious the problem becomes.

The most common questions before list cleaning

Many teams do not do basic filtering before officially sending, and the results will appear:

l A large number of empty or unavailable numbers

l The proportion of long-term inactive users is too high

l Abnormal data affects overall statistics

In this case, even if the sending volume is large, not many people will actually enter the communication.

Moreover, customer service will spend a lot of time dealing with invalid users, and the overall pace will become slower and slower.

Why the bigger the list, the more obvious the waste

When the amount of data is small, problems are not easily noticed.

But when the sending scale is expanded:

l Every invalid send consumes resources

l Customer service needs to repeatedly confirm the user status

l Data analysis will become increasingly inaccurate

Especially in the US market, the cost of access is already high, and the waste caused by low-quality data will be more obvious.

Why does the cost of access drop after cleaning?

After list cleaning, although the amount of data will be reduced, the overall efficiency will be improved.

Major changes include:

l Invalid sending reduction

l Increased response rate

l Private chat is promoted to be more focused

Customer service will no longer waste a lot of time on unavailable users, and truly valuable users will be more likely to be prioritized.

The order of processing in this case is critical.

Many teams will send it directly and then adjust it based on the results. But a more stable way is to process the data first.

The process in the case is:

Check number availability first

Filter active users

Finally, stratify according to quality

After processing in this way, subsequent transmissions will be significantly more stable.

It is more stable to do a test before the list enters the system.

The problem is amplified if the data goes directly into the group or private messaging process.

In actual operation, you can first use Digital Planet to perform number screening to filter out unavailable numbers and abnormal data in advance, and then conduct subsequent marketing. Digital Planet supports free trial screening test.

This allows the list to undergo a basic cleanup before use.

After the list is cleaned, layered use will be more effective

After cleaning is completed, it is not recommended to use all data uniformly.

A more reasonable way is:

Reach high-quality users first

Continuous cultivation of medium users

Low-quality data reduces frequency or suspends use

This layered approach will be more stable than one-time mass distribution.

A common misunderstanding is to attribute the problem to the delivery effect

Many times, a drop in delivery rate is not a tool problem, but rather the data has expired.

If the list is not updated for a long time, no matter how good the delivery method is, it will be difficult to be stable.

Therefore, the quality of the list itself has become an important factor affecting the results.

Reaching costs are reduced, and the essence is to reduce waste

Many teams will interpret cost reduction as reducing budget, but a more direct way is actually to reduce invalid data.

After empty numbers, abnormal numbers and low active users are filtered in advance:

l More value every time you send

l Customer service communication is more focused

l Data analysis is also more realistic

The U.S. market increasingly relies on data cleaning capabilities

In the past, when working in the US market, I preferred to expand the size of the list. There is now an increasing reliance on data screening and list updating.

Because there is no shortage of traffic itself, what is really scarce are available users.

For the same batch of lists, as long as the processing methods are different, the final reach cost and conversion results will be much different.

digital planet is a world-leading number screening platform that combines Global mobile phone number segment selection, number generation, deduplication, comparison and other functions . It supports customers worldwideBatch numbers for 236 countriesScreening and testing services , currently supports40+ social and apps like:

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The platform has several features including Open filtering, active filtering, interactive filtering, gender filtering, avatar filtering, age filtering, online filtering, precise filtering, duration filtering, power-on filtering, empty number filtering, mobile phone device filtering wait.

Platform provides Self-screening mode, generation screening mode, fine screening mode and customized mode , to meet the needs of different users.

Its advantage lies in integrating major social networking and applications around the world, providing one-stop, real-time and efficient number screening services to help you achieve global digital development.

You can find it on the official channelt.me/xingqiupro Get more information and verify the identity of business personnel through the official website. official businesstelegram:@xq966

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