How to use AI to acquire customers

AI has been mentioned a lot in the past two years, and many teams doing overseas promotion have also begun to try to use AI to find customers. But after using it in practice, you will find a problem: AI can indeed help, but it is not as "automatic" as imagined.

A really well-used team,AI is just a tool; if used poorly, AI will amplify the problem. The key is not “whether to use AI or not”, but “where to put AI”.

The essence of AI customer acquisition is not to replace people, but to improve screening efficiency

What AI is best at is processing information, not judging transactions.

In the customer acquisition process, it is more suitable for doing the following things:

l Organize market information

l Analyze user characteristics

l Generate content and discourse

l Initial grouping of clues

But what it is not suitable for is to judge whether a customer is real, reachable, and whether a transaction will be completed. If these basic questions are given toAI, it’s easy to make mistakes.

soThe role of AI is more like "amplifying efficiency" rather than "replacing processes."

Overseas promotion in progress,In what areas can AI be used?

If you break down the entire customer acquisition process,There are actually many places where AI can participate.

On the front end, it can be used for market analysis

l Which countries are more suitable for current products

l What are the concerns of users in different regions?

On the content side, it can be used to generate materials

l advertising copy

l social media content

l private messaging skills

In the intermediate link, simple grouping can be done

l Classify customers based on keywords

l Make preliminary labels based on region or industry

On the back end, it can assist in optimizing communication

l Generate next steps based on customer responses

l Improve customer service response efficiency

But please note that these are"Auxiliary" is not the core judgment.

Why do many teams useAI effect is unstable

A very common problem is: directly hand over unprocessed data toAI.

For example:

l A large number of invalid contact information is mixed into the data

l Customer tags themselves are inaccurate

l Contact information is unavailable or abnormal

in this case,The judgments made by AI will also be biased.

The essential reason is: the data quality is not enough, but it is usedAI performs detailed analysis.

Just like doing calculations on the wrong basis, the results will only be more biased.

Before AI can find customers, it must first solve data problems

If you want toFor AI to really work, the first step is not to use AI, but to process the data cleanly.

At least ensure:

l Contact information is real and available

l The data does not have extensive duplication or anomalies

l Basic labels are relatively accurate

Only under this premise,The grouping and analysis done by AI are meaningful.

Otherwise, even ifNo matter how detailed the AI ​​is, subsequent attempts to reach it will still fail.

How should AI and screening tools be used together?

A more stable way is to clearly divide the labor between the two:

The screening tool is responsible for"validation data"

AI is responsible for “using data”

The specific process can be:

Screen number first

l Filter out invalid numbers

l Ensure data is available

reuseAI

l Make customer groups

l Optimize communication strategy

l Generate discourse

This can avoid a problem: wasting on invalid dataAI capabilities.

In actual operation, you can first use Digital Planet to do screening number detection, confirm the number availability first, and then hand over the screened data toAI does labeling and grouping processing. Digital Planet supports free trial screening test.

Which teams are more suitable to use?AI to acquire customers

AI is not suitable for all teams to use from the beginning.

More suitable situations include:

l Already have a stable data source

l Have a certain size of customer pool

l Have sales or customer service capabilities

l Have basic operating procedures

If even the data source is not stable, just useAI, it is difficult to see obvious effects.

don't putAI is the only way to acquire customers

AI can improve efficiency, but it cannot replace channels.

Customers still need to go through:

l Advertising

l Content diversion

l Community operation

l Channel cooperation

obtained in these ways.

The role of AI is to make these channels "more useful" rather than replace them.

What is really useful is"Process + AI" rather than "only AI"

No matter how good the tool is, it won't be effective if the process itself is messy.

A more practical idea is:

Let’s straighten out the process first

againAdding AI to improve efficiency

For example: data acquisition → Data screening → Customer stratification → Communication transformation

AI can be placed in the layering and communication stages, but the previous data screening must be done first.

Whether AI can help you find customers depends on what data you give it

many people look forward toAI "automatically finds customers", but in fact, what AI can do is optimize efficiency based on existing data.

If the data itself is clean, usable, and structured,AI can significantly improve results.

If the data itself is messy, invalid, and unusable,AI will only amplify the problem.

So the key is notAI, and the quality of the data you feed it.

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