Case Study: Flipp achieves a 10% increase in in-store traffic with Databricks

Connecting shoppers to savings with data-driven personalization‌

Flipp, a retail tech company that aggregates weekly shopping circulars, was struggling with siloed, unstructured data from retail partners and user behavior. Data pipelines were fragile and slow, analysts tracked experiments in tedious spreadsheets, and limited access to raw data made deeper analysis and reproducibility nearly impossible.

By adopting the Databricks Lakehouse with Delta Lake, Flipp centralized fast data ingest, ETL, and analytics using Spark APIs, Tableau dashboards, and MLflow for experiment tracking. This democratized data across teams, enabled real-time personalized offers and a recommendation engine, and delivered measurable impact — including a 10% increase in in-store traffic for retail partners — along with faster insights and more meaningful partner reporting.

Flipp

Guenia Izquierdo

Data Engineering Manager