Case Study: Sephora cut data warehouse costs 75% with Funnel
Key results
The challenge
Sephora's marketing data was scattered across local teams throughout Europe. The central data team spent an entire working day each week collecting and consolidating reports from local markets before it could analyze and present findings to leadership.
The solution
Funnel was used to collect and prepare marketing data, feeding a stack of BigQuery, dbt, and Looker Studio. Clean, pre-modeled tables replaced the manual consolidation of hundreds of BigQuery tables.
“With data consolidated in Funnel, we can output clean data tables with just the dimensions and metrics we need, instead of having to consolidate hundreds of tables in BigQuery. This alone saves us 75% on data processing costs.”
HBHamis BadarouChief Analytics Officer, Hanalytics
The results, in context
Sephora reported a 75% reduction in data warehouse processing costs and recovered roughly one full working day per week for its central data team. Reporting was delivered to 18 local teams across Europe.