Case Study: How Burberry is increasing revenue with better data
Key results
The challenge
Burberry relied on daily batch exports of clickstream data, which constrained how quickly it could personalize experiences across channels. Browser restrictions, such as Safari capping server-side cookies at seven days, further limited its ability to connect anonymous browsing to known customers.
The solution
Burberry deployed Snowplow's customer data infrastructure alongside the Databricks Lakehouse Platform, replacing daily batch exports with near real-time clickstream data feeding personalization models. The setup powers 40 personalization models spanning product recommendations, propensity scoring, and lifetime value.
The results, in context
Burberry reduced data latency by 99% by moving from daily batch to near real-time data with Snowplow and Databricks. It also extended its server-side cookie window from seven days to 12 months, a 52x increase, improving its ability to tie anonymous browsing to known customers, and now powers 40 personalization models on the data.