Data Science

Customer Segmentation

Leverage your data to automatically segment your customer base

What is a segmentation?

  • Customer segmentation aims to divide the customer base into meaningful groups, with the idea of customers in the same group being more similar to each other than those in others groups
  • A segmentation allows the brand to optimize customers visits by adapting the range of products pushed, merchandising, pricing, promotions to a  particular segment of customer according to its main purchase characteristics
  • Implementing a segmentation gives the brand a better understanding of their customers and purchase habits, leading to an increase in customers loyalty and purchase value

Dimensions considered for the segmentation

This segmentation is based on three sales dimensions:

  • Recency: How long has it been since the last customer activity/purchase?

A customer that has not done a transaction with the brand for a long time should be given priority and special treatment so as not to lose it

  • Frequency: How many transactions has the customer made during a particular period of time?

A customer with a high purchase frequency is more engaged and loyal to the brand than a store with a few transactions registered

  • Monetary : How much did the customer spend during a particular period of time?

This dimension makes it possible to evaluate the purchasing potential of customer, it’s important to differentiate big spenders and small ones


  • View the distribution of customers on all dimensions
  • Measure the performance per segment
  • Assess the evolution from one segment to the other

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