Operationalizing Analytics Data at Scale (DEICHMANN SE)
DEICHMANN SE · Germany
DEICHMANN SE, Europe's largest footwear retailer with roughly 4,700 stores in more than 30 countries and about 8.7 billion euros in 2024 revenue, adopted Databricks Lakebase, a managed PostgreSQL database integrated with its Databricks Lakehouse, to activate governed customer and product data for e-commerce marketing without building separate integration pipelines. Lakebase reduced a data-product publishing pipeline to 3 clicks and about 30 seconds, and is now in production across Europe feeding SAP Emarsys for e-commerce marketing.
Overview
DEICHMANN SE, Europe's largest footwear retailer with roughly 4,700 stores in more than 30 countries and about 8.7 billion euros in 2024 revenue, adopted Databricks Lakebase, a managed PostgreSQL database integrated with its Databricks Lakehouse, to activate governed customer and product data for e-commerce marketing without building separate integration pipelines. Lakebase reduced a data-product publishing pipeline to 3 clicks and about 30 seconds, and is now in production across Europe feeding SAP Emarsys for e-commerce marketing.
This entry has 14 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
“The integration gap between our data lakehouse and marketing platform required ongoing engineering intervention,” explained Kevin Haferkamp, Head of Data Platform & Engineering CoE, IT Data & Analytics. “We needed a self-service solution that would let CRM teams access the customer data they needed without constant technical support.”
The solution
The breakthrough came with Databricks Lakebase, a managed PostgreSQL database that aligned with DEICHMANN's architectural vision. Lakebase offers an OLTP database solution directly integrated with the Databricks Lakehouse, enabling the team to serve data from their analytics layer into operational applications with minimal overhead. Data engineers and software engineers manage synchronization logic and guardrails, while platform engineering teams focus on instance setup and governance standards; CRM teams can then trigger data synchronization to support campaign execution without relying on constant engineering support. The Lakebase instance supporting this use case is in production across Europe for e-commerce marketing and integrates with SAP Emarsys as the downstream activation platform.
Reported business value
With Lakebase in place, DEICHMANN can activate a broader set of customer and product data for e-commerce marketing workflows with less operational effort than before. “Having three clicks taking maybe 30 seconds, then you have your synchronization job of a table available,” said Haferkamp. “Any other effort in programming the pipeline to sync to an external database is unbeatable.”
Sources
Open any source and check the claim yourself — that is the point of the register.
Other retail entries in the register.
Furniture.com Transforms Online Search with Databricks
Furniture.com unifies over 60 retail partners and 1.5 million SKUs on the Databricks Data + AI Platform, using Delta Lake, MLflow and Unity Catalog to run its ML lifecycle. Its Find It AI product-discovery tool uses generative AI to create a synthetic image representing shopper intent, then matches it against the product catalog for image-based search. A Collections model uses LLMs to automatically group related products, finding more than 16,000 collections across 50+ partners with no human intervention. Users who interact with Find It AI show a click-through rate 8x higher than baseline and a return rate 3.2x higher than baseline.
How Walmart Achieved Enterprise Transformation Through Digital Experience Innovation
Working with implementation partner Nativa on LivePerson's technology, Walmart customized and integrated conversational technology into its WhatsApp channel, including a FAQ-Transactional Bot to streamline searches, inquiries and purchases. The solution delivered a 60% increase in productivity and a 10 percentage point improvement in CSAT/NPS, along with operational savings through automated customer service processes.
Zalando enhancies customer engagement and operational efficiency with Mistral
Zalando, a European e-commerce platform, integrated Mistral models hosted on AWS Bedrock into its platform to add natural language processing and machine learning capabilities. The integration supports personalized recommendations, improved customer service and streamlined operations for the retailer's shopping experience.
McGee & Co uses Syte's visual AI to connect shoppers with complementary home decor pieces
Furniture and home decor retailer McGee & Co implemented Syte's visual search and AI tagging technology to tie products together, helping customers who find an item like an end table or couch also discover the complementary pieces from the same collection. Josh Batchelor, VP of Technology at McGee & Co, said the goal was to make sure shoppers are served complementary pieces when they need them.
Was this helpful?
Your feedback helps us improve our use case database