L'Oréal amplifies the consumer experience by leveraging the Databricks Lakehouse

L'Oréal, the world’s leading beauty player, has chosen Databricks to enable the interoperability of its global Beauty Tech Data Platform and to pursue its multi-cloud strategy.

  • 1 year ago Posted in

With its strong leadership in digital, L’Oréal is now pioneering Beauty Tech. The L'Oréal Group’s experts use technology, data and artificial intelligence to develop services that deliver an unrivalled degree of precision and personalisation. This approach is revolutionising how consumers discover, try and receive advice about products, both online and in-store. 

 

The Databricks Lakehouse will unify data across all of L'Oréal’s cloud data platforms. The Lakehouse will provide a complete view of the consumer’s data journey, from inquiry to purchase, from shipment to care, and from the online to offline experience. With Databricks providing a key component of its enterprise data platform, L'Oréal can further improve its consumer and customer experience. 

 

L'Oréal began its journey on the Databricks Lakehouse in 2019 for its Consumer 360 and CRM operations in North America. The L’Oréal Tech team has already experienced significant benefits from working with Databricks, accelerating time to insight by consolidating and analysing real-time consumer data. In just two years, L'Oréal North America saw a 20% improvement in productivity through reduced maintenance effort, improved runtime, and cloud consumption. 

 

The L'Oréal Tech team is committed to contributing to the L'Oréal Group's sustainable development objectives and the optimisation and rationalisation of data exchanges to reduce the volumes transported across regions. 

 

“This strategic, global partnership with Databricks demonstrates our clear commitment to enrich our data capabilities and make L'Oréal the front-runner in the world of Beauty Tech,” said Etienne Bertin, Group CIO, L'Oréal. “L'Oréal operates in 150 countries, selling over 7 billion cosmetic products to more than 1.2 billion consumers every year, so having a data architecture that is unified, open, cloud-agnostic, interoperable, secure and scalable, is integral to our success. Leveraging the Databricks Lakehouse is enriching our global Beauty Tech Data Platform, and we are excited to see the partnership evolve in the years ahead.” 

 

“The Databricks Lakehouse offers a simple, unified platform to handle all data, analytics, and AI use cases. It’s never been more challenging for major retailers to keep up with a 360-degree view of the customer to ensure loyalty and growth, but data-forward organisations like L'Oréal are at the forefront of turning this challenge into an opportunity. We’re proud to deliver the global, real-time insights and data governance that enables L’Oréal to provide an incredible experience for its customers.” said Naveen Zutshi, CIO, Databricks.

 

“At Databricks, our commitment is to help organisations solve some of the world’s toughest problems with data and AI and we are proud to support L'Oréal on its journey to become the leading Beauty Tech organisation,” said Samuel Bonamigo, SVP & GM, EMEA, Databricks. “Our open, cloud-agnostic enterprise data platform is already demonstrating a clear impact and we are eager to see this partnership evolve in EMEA in particular, this year and beyond.” 

NinjaOne AI program focuses on customer success and thoughtful adoption over hype.
The new seven-story Fitzrovia-based space will be one of the company's largest offices outside of...
New research from Confluent sees IT leaders share their biggest data challenges.
Global IT Business-to-Business (B2B) revenues, coming from data centers, IT services and devices,...
Confluent adds Table API support for Apache Flink® making it even easier for developers to use...
Partnership and integration delivers innovative new ways to access data, improving the user...
Tessell has released Tessell for Oracle Exadata Database Service on Dedicated Infrastructure...
Introducing unified metrics, generative AI-powered reports and insights, and a custom ML model...