Case Study: Sportsbet achieves real-time personalized recommendations and faster time-to-market with Databricks

Creating a personalized gaming experience

Sportsbet, Australia’s largest corporate bookmaker with more than 1.2 million customers placing roughly 25,000 bets per minute, needed to deliver real-time, personalized experiences but was hampered by limited processing capacity, heavy pipeline maintenance, and long model development cycles that kept data scientists tied up in preparation work.

By building a real-time personalization engine on the Databricks unified analytics platform and AWS, Sportsbet automated data pipelines, simplified infrastructure with auto-scaling clusters, and enabled collaborative, multi-language workspaces. The result: large-scale real-time processing and ML at much higher speed—5x faster data preparation, 10x faster downstream ML processing, over 20x performance versus open-source Spark—and near-zero infrastructure management time, driving faster time-to-market, improved customer loyalty and increased revenue.

Sportsbet

Alex Kruger

Data Scientist and Machine learning Engineer