Create clusters in customer databases

A very common mistake is to diagram communication campaigns to a customer base, with the same message for all.


The trick is to create audiences or clusters, according to preferences and purchase frequency, in this way, the campaigns will be hyper personalized, more profitable and you will achieve higher conversions in your eCommerce.


The segmentation must be carried out based on economic criteria, (Customer Lifetime Value) purchasing propensities, (Buyer Persona Profiles based on data) and personalized product recommendations.


Communication directed to inactive customers is not the same as to those with a certain degree of loyalty. You have to create different strategies for each segment.


The Customer Lifetime Value segments customers who are at the same level of loyalty.

Each Customer Lifetime Value segment (high / medium / low customers) needs a different strategy and attention


Define a different promotion strategy for newsletters and use the most loyal customer segments to create lookalike audiences on Instagram and Facebook campaigns.


By automatically analyzing customer databases, different Buyer Persona profiles can be discovered. With this information, we can also personalize communications with more relevant content for each segment.


We must also identify the purchasing propensity of each profile to create upselling and cross-selling strategies by automating communications.


Customizing the recommendations for each client is the definitive step to increase conversions in eCommerce, increase the first purchases, increase the average ticket and improve the conversion of campaigns with relevant products for each client.


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