Case Study: ShowroomPrive achieves 2.5x more effective marketing campaigns with Dataiku

Putting ML-Powered Targeting in the Hands of Marketers

ShowroomPrive, an e-commerce flash‑sale retailer, faced inefficient, manual email targeting that produced overlapping audiences and sent irrelevant offers. To put machine learning into marketers’ hands, ShowroomPrive partnered with Dataiku to build Targetor, a Dataiku‑powered webapp that enables marketers to generate ML-driven targeting recommendations without heavy IT support.

Using Dataiku for model development, testing, deployment and webapp delivery, ShowroomPrive iterated Targetor over several years—adding user ranking, monitoring, A/B testing and a modular architecture—and now uses the webapp 2–3 times per day. The Dataiku-backed solution made marketing campaigns 2.5× more effective, improved cross‑team collaboration, and drove operational upgrades (e.g., moving to Kubernetes) to scale model execution.

ShowroomPrive

Damien Garzilli

Strategy and Business Intelligence Manager