Turning retail data into actionable insights

The context

Over the past five years, an international retail group has progressively centralized its data into a modern data warehouse, with a strong strategic focus on the Google Cloud Platform (GCP). The ambition is clear: leverage centralized data to generate actionable insights and continuously improve operations, such as measuring the true impact of promotions on products and customer behaviour.

The Data Platform team of the retailer, supported by Euranova, is responsible for operating this data warehouse and ensuring data availability for the business.

The logic

With the success of the data warehouse, demand from business teams accelerated. Beyond data ingestion and migration, the key challenge became turning analytical models into reliable, maintainable, production-grade solutions. This required close collaboration between data engineers and data scientists to ensure long-term sustainability, scalability, and trust in results.

The solution

Euranova strengthened the Data Platform team and contributed to multiple high-impact use cases, working hand-in-hand with data scientists and business stakeholders. For instance:

• Promotion Impact Dashboard
  Business teams wanted to understand the true impact of promotions beyond simple before/after sales comparisons. Data scientists built a model measuring three effects: halo**,** channelling, and stocking**.** Over time, repeated refactoring made the code unreadable and fragile, eroding trust in the results. Euranova took over and rebuilt the solution from scratch, working closely with data scientists to deliver a modular, robust, and production-ready implementation on Google Cloud Platform (CGP). Each KPI was isolated to prevent cascading failures, restoring confidence and enabling sustainable evolution.

• Promotional Email Refactoring
  Personalized promotional emails rely on data science models but required manual, highly specialized configuration to run. Knowledge was siloed, making this critical business process risky and difficult to scale. The team refactored the codebase to standardize and simplify execution, enabling campaigns to be launched with minimal configuration—even by non-technical users.

Next steps in applied excellence

As more teams onboard the data platform, the focus shifts to industrializing analytics at scale. Upcoming priorities include accelerating model deployment, expanding self-service capabilities for business users, and continuing to modernize data pipelines to fully leverage the Google Cloud Platform ecosystem—ensuring data remains a strategic asset across the organization.