For omnichannel retail groceries, Lifetime Value (LTV) plays a key role. Measuring Customer loyalty and making marketing decisions based on LTV across channels is essential to keep on acquiring new loyal customers. One of the biggest challenges about LTV is its difficulty to include these signals in DV360 in new customer acquisition campaigns. While for returning customers historical transaction data is available for predicting future LTV, for newly acquired customers predicting LTV and using these signals for Bidding is more challenging.
Carrefour, In collaboration with Making Science as the Tech Partner has developed a Machine Learning model that predicts the LTV for newly acquired customers and imports the predicted LTV through Matchid.
Making Science has developed a Custom Bidding Algorithm that leverages the Machine Learning LTV signal in Prospecting DV360 campaigns (new customer acquisition campaigns).
Arena as the Agency and as responsible for the media activation has developed an A/B test in DV360 comparing previous Custom Bidding (Using Revenue signals) Vs the new test leveraging the new Customer Bidding (using predictive LTV signals)
The A/B test has been active for 6 months.
Carrefour implemented predictive LTV signals in DV360 and after an A/B test that lasted 6 months, these were the results.
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