Case Study: Cdiscount achieves higher conversion and faster R&D with Crownpeak Product Recommendations

How Cdisount uses algorithm orchestration to improve recommendations and merchandising

Cdiscount, a leading French e-retailer with over 9 million customers and a large marketplace catalog, needed to better personalize customer journeys and scale recommendation R&D as marketplace volumes outgrew internal resources. The merchandising team also wanted control over rules without relying on data scientists.

Cdiscount implemented Crownpeak Product Recommendations in server-side mode to orchestrate and hybridize multiple algorithms, processing and enriching large data volumes in real time. The solution improved personalization and merchandising—boosting conversion rates (e.g., +2.5% from complementary strategies, +3% from journey models, +1% from new merchandising rules), increased average basket size, accelerated R&D through rapid A/B testing and hybridization, and cut merchandising setup time from days or weeks to under a day.

CDiscount

Simon Berthet-Bondet

Head of Merchandising