Case Study: Picard achieves better customer lifetime value predictions with Dataiku

Picard Predicting Customer Lifetime Value for Better Outcomes

Picard, a growing retailer, needed to move beyond SAS to a more scalable and collaborative data platform to handle rising data volumes, stronger analytics demands, and limited support for machine learning. The company chose Dataiku to modernize its data operations, unify fragmented workflows, and help teams work more flexibly with tools like Python and R.

With Dataiku, Picard migrated 15+ years of SAS workflows, trained teams through Dataiku Academy, and automated key analytics processes. The result was a monthly updated Customer Lifetime Value model and broader improvements across CRM, budgeting, and segmentation; Picard also achieved 75% accuracy in predicting customer segments after the first purchase, while gaining faster collaboration, better forecasting, and more scalable analytics.

Picard