Mercado customer data screening method: how to find users who are truly interested in purchasing

When doing cross-border e-commerce in the Latin American market, Mercado is an unavoidable platform. Many sellers have obtained a large amount of customer data through advertising, on-site traffic or event deposits. However, when they actually enter the follow-up stage, they find that the effective transaction ratio is not ideal. There seems to be a lot of data, but not many people are actually willing to buy it.

The problem is often not the traffic, but the filtering logic.

If users with purchase intention cannot be screened out from the data, follow-up private messages, text messages orWhatsApp reach will become inefficient. Screening is an action that must be completed before the transaction is completed.

1. Common structural problems of Mercado customer data

Mercado customer data comes from various sources, including:

lUsers who click on ads on the site

lBrowse users who have not placed orders

lHistorical purchasing users

lPromotional activities for retained users

When these data are blended together, significant differences emerge.

Some users only viewed it once.

Some users have not logged in for a long time.

There are abnormalities in some contact information.

Some data is duplicated or incomplete.

If the entire list is contacted directly, a lot of customer service time will be wasted on low-intent users.

2. How to design the screening logic

Effective screening logic is usually divided into three stages.

The first stage: data basic cleaning

Remove duplicates, unify formats, and delete obviously abnormal data.

The second stage: status identification

Confirm whether the contact information actually exists and is reachable.

The third stage: activity and behavioral judgment

Distinguish users who have browsed or interacted recently.

At the execution level, digital planet can be used to perform batch status detection, identify number registration status and active status, and output structured tags. In this way, silent or abnormal accounts can be filtered in advance.

3. Case: Comparison of conversion rates before and after screening

A seller sells single products with medium to high customers in the Brazilian market. In the initial stage, the list of investors staying in Mercado will be processed directly.When reached by WhatsApp, the overall response rate was less than 5%.

The team then optimized the list in two steps:

The first step is to use Digital Planet to identify registration status and filter exceptions.

The second step is to only reach recently active users.

After optimization, the list size is reduced by approx.35%, but the response rate increased to more than 9%. Customer service feedback has significantly increased the proportion of effective communication, and transaction conversion has become more concentrated.

This change shows that the value of screening is far greater than simply expanding the list.

4. How to embed screening into daily operations

In order to avoid temporary data sorting every time, it is recommended to fix the filtering action as a standard process.

lTest each batch of new data before importing it

lCreate a label hierarchy

lRegular review of history list

lAdjust reach order based on activity changes

Digital Planet supports batch import and result export, and can be connected with the marketing system to reduce manual processing time.

5. Marketing rhythm after layering

After the screening is completed, it is recommended to develop different reach strategies by level.

lHighly active users will be prioritized and followed up

lTest in batches with medium active users

lLow active users reduce frequency

lSuspended for abnormal users

This kind of structured management can make marketing resources more concentrated.

In the Mercado market, transactions do not depend on data scale, but on data quality. Through pre-screening and active identification, marketing actions can be made more precise. Digital Planet's capabilities in batch status detection and structured label output can help teams turn screening into a fixed process rather than a temporary action.

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