Epsilon, a global leader in marketing solutions, sought to revolutionize how it delivered personalization for clients across verticals like retail, pharma, and travel. The goal was not just to build powerful machine learning (ML) models but to do so transparently — avoiding black-box solutions and offering visibility into both model performance and business outcomes.
The team faced the challenge of finding a flexible, enterprise-ready platform to accelerate AI product development while satisfying client demands for transparency and measurable results. Over eight years ago, the solution became clear: Dataiku, The Universal AI Platform™.
Why Dataiku? Transparency, Speed, and Scale
Choosing a Platform That Empowers, Not Obscures
Epsilon rejected the notion of adopting a black-box AI platform. They required a solution that empowered their engineering and analytics teams with visualization capabilities, clear workflows, and the flexibility to meet varied client needs. Dataiku fit the bill, offering not only best-in-class model development tools but also the transparency necessary for internal stakeholders and external clients.
Beyond Software ROI
Unlike many organizations, Epsilon deliberately chose not to build a business case solely around software ROI. Instead, Epsilon framed Dataiku as an essential tool, much like a carpenter’s hammer: valuable only when skilled people use it to create meaningful business outcomes.
Driving Impact: From Engineering to Client Success
Initially adopted by the engineering team, Dataiku soon gained traction across Epsilon’s analytics teams as well. The platform’s ease of use, combined with its ability to support both code-first and code-free users, helped overcome resistance and broaden adoption across disciplines.
Dataiku became Epsilon’s decision engine — the heart of personalization programs for a vast array of clients. Through Dataiku, Epsilon linked ML outcomes to key business KPIs such as revenue growth, increased customer engagement, and operational efficiencies for its clients.
Overcoming Challenges: Change Management and Transparency
While the benefits were clear, change management posed hurdles:
- Process changes required to shift teams from legacy tools
- Cultural resistance to adopting low-/no-code tools among seasoned data scientists
- Hiring new resource profiles aligned with modern AI workflows
Additionally, Dataiku’s transparency made it easier to satisfy compliance and governance requirements — essential in marketing contexts where understanding how models work is just as important as the results they produce.
Looking ahead, Epsilon will expand Dataiku’s use into its media and ad buying operations, embedding the platform deeper into core revenue-driving activities. Epsilon also launched a champion/challenger program, challenging internal data scientists to outperform existing models in production. Winning models earn both adoption and recognition, encouraging innovation and improving client outcomes.
By integrating Dataiku deeply into its engineering and analytics functions, Epsilon has created a scalable, transparent, and high-impact AI operation. The result? Faster innovation, greater ROI for clients, and a robust foundation for the next wave of AI-driven personalization and decisioning.
