{"slug":"global-fashion-leader-increases-revenue-with-better-data","url":"https://findausecase.com/use-cases/global-fashion-leader-increases-revenue-with-better-data","title":"Global fashion leader increases revenue with better data","description":"Burberry combined the Databricks Data + AI Platform with Snowplow's Behavioral Data Platform to build a real-time AI-Ready Customer 360 from website clickstream data, replacing daily data batches. The platform runs 40 personalized machine learning models covering product recommendations, propensity scoring and customer lifetime value, cutting clickstream data latency by 99% and extending cookie duration 52x, letting in-store client advisors see customers' recent online behavior on mobile devices to deliver personalized service.","company":"Burberry","industry":"Retail","aiCapabilities":["Recommendation & Personalization","Predictive Analytics"],"businessFunctions":["Marketing","Sales"],"technology":["Databricks Data + AI Platform","Delta Lake","Agent Bricks","Snowplow Behavioral Data Platform","dbt"],"deployment":"Public Cloud","problemStatement":"Burberry's cloud-based data warehouse delivered the previous day's clickstream data anywhere between 2:00 and 7:00 PM GMT, too late to pass along to client advisors in stores worldwide. The warehouse also automatically pre-aggregated and sanitized the data, making it difficult to trust or validate details about customer visits, so simple questions about website activity often went unanswered.","solutionApproach":"Burberry implemented the Databricks Data + AI Platform together with Snowplow's Behavioral Data Platform to realize real-time AI-Ready Customer 360s from across digital touchpoints. Clickstream data flows into the Databricks Data + AI Platform, which contains 40 personalized models covering product recommendations, propensity scoring and lifetime value, instantly recalculating data before sending it to the company's action system. Burberry also switched to server-side cookies via Snowplow and used the dbt plug-in for Databricks to gather additional detail from referral sources, consent banners and server-side cookies for a refined marketing attribution model.","businessValue":"By reducing clickstream data latency by 99%, Databricks enables in-store client advisors to view opted-in customers' recent online browsing habits on mobile devices during the typical two- to six-hour webrooming window, allowing for tailored product recommendations. Server-side cookies extended cookie durations 52x, from 7 days to 12 months, improving marketing attribution while complying with GDPR and customer privacy standards.","evidence":{"band":"high"},"sourceUrl":"https://www.databricks.com/customers/burberry-snowplow","dates":{"publishedAt":"2026-09-21T05:47:00.321Z","publishedAtSource":"pipeline","updatedAt":"2026-09-21T05:47:00.321Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/global-fashion-leader-increases-revenue-with-better-data. Bulk republication requires permission."}