Case Study: SEGA achieves personalized gaming experiences and reduced churn with Databricks Lakehouse

Delivering next-level gaming experiences that keep players coming back

SEGA Europe, a long-standing games publisher with 30 million customers generating about 25,000 event records per second, struggled to turn massive, dispersed streaming and unstructured data into actionable insights. A COVID-era doubling of active players exposed limits in their legacy stack (S3, Redshift, Azure), causing compute bottlenecks, slow ingestion, blocked queries and constrained data science work on local machines that prevented scalable analytics and ML.

SEGA migrated to the Databricks Lakehouse on AWS (Delta Lake, Databricks SQL) to centralize data, scale real-time ingestion, and enable collaborative data science and BI. The platform democratized datasets and accelerated ML-driven use cases — from cohorting and churn prediction to personalized in-game updates — allowing minute-level data collection (vs. half-hour) and delivering 1M+ personalized experiences daily, reducing churn, improving engagement and unlocking new revenue opportunities.

SEGA

Felix Baker

Data Services Manager