Customer Lifetime Value Prediction for a Leading Online Retailer

Online Shopping Retail


Leading retailer

Tech stack

Google Cloud


Spending optimisation


AI + Machine Learning

Our client is a leading online retailer, that sells products globally. We helped them optimise digital media spending by more accurately predicting future customer value using Machine Learning.

Our impact

  • Fully automated machine learning workflow
  • Identification of customers with ‘high future value’ that were otherwise classified as ‘low value’
  • Optimised audience targeting across paid search & paid social based on CLV


The challenge

Our client wanted to leverage historic orders and spend of customers to drive customer strategies across paid search and other marketing channels. Datatonic supported them with creating a model to accurately predict future customer value. With an accurate estimation of future customer value, the business can optimise its spend to acquire and re-engage customers, based on a reasonable expectation of monetary value it would expect to see returned.


The solution

In just five weeks, Datatonic delivered a rich feature set, with 270+ custom-level features, created from internal and externally sourced data. Our fully automated machine learning workflow retrains customer lifetime value (CLV) models and assigns predictions to the full customer base each day. Our client can now identify customers with ‘high future value’ that were otherwise classified as ‘low value’ based on the current Recency Frequency Value segmentation and optimise their audience targeting across paid search and paid social (through lookalike matching).