Case Study: Wehkamp achieves personalized shopping experiences and 2x revenue with Databricks

Democratizing data for better shopping experiences

Wehkamp, a leading fashion e-commerce company, needed a faster, more collaborative way to work with massive daily data volumes from 500,000 visitors and 400,000 products. Its legacy data warehouse and data silos slowed time-to-insight, made machine learning hard to scale, and delayed new feature releases across its global websites. Wehkamp turned to Databricks for data analytics and machine learning.

Databricks implemented a Unified Data Analytics Platform on AWS to help Wehkamp ingest data at scale, automate pipelines, and enable teams to collaborate in notebooks using SQL, Scala, Python, and R. With Databricks, Wehkamp built image classification and recommendation engines, trained hundreds of models per day, reduced operational costs by about 70%, and doubled revenue through more personalized shopping experiences.

Wehkamp

Arnoud de Munnik

Data Scientist