Case Study: Awin Global achieves 9x higher recommendation acceptance and 20% compute cost savings with Databricks Lakehouse

Improving affiliate marketing ROI with customer insights

Awin Global, a large affiliate-marketing network in retail and consumer goods, struggled to manage and act on massive customer and transactional data—ingesting about a terabyte daily—which led to clogged pipelines and day-long delays for reports and insights that advertisers and publishers needed to make timely campaign decisions.

By moving to the Databricks Lakehouse with Delta Lake and integrating Power BI/Tableau and ML models, Awin cut ingestion-to-insights time from a day to about an hour, reduced ETL windows by over 40%, and lowered compute costs by 20% (plus ~$25K/month in hosting savings). The platform enabled a recommendation engine that boosted publisher-acceptance rates 9x, supports 250+ reports and dashboards, and unlocked faster time-to-market, higher campaign ROI, and new revenue opportunities.

Awin Global

Anup Belbase

Head of Data Warehousing