Case Study: Burberry achieves faster, personalized customer experiences with Databricks

Global fashion leader increases revenue with better data

Burberry, the global luxury fashion brand, wanted to deliver more personalized customer experiences but was limited by slow clickstream data processing that made online behavior hard to analyze in time. Using the Databricks Data Intelligence Platform alongside Snowplow, Burberry set out to build a unified customer view and support in-store advisors with timely insights.

Databricks helped Burberry combine customer behaviors from multiple sources and reduce data latency dramatically, enabling client advisors to see opted-in customers’ recent online activity on phones and tablets. The solution improved personalization, extended anonymous cookie duration from one week to 12 months, and is helping Burberry work toward near-real-time data delivery of about five minutes, with measurable gains in customer service and sales opportunities.

Burberry

Ben Halsall

Analytics Technology Director