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Overview & Problem
My Role
Human Centered Design Approach
Success Measures (pre-launch)
We set a target of increasing customer engagement by 25% within 6 months, hoping our redesigned platform would draw users back regularly.
Our goal was to reduce navigation-related support calls by 10%, which would indicate we had created a more intuitive interface that customers could navigate without assistance.
For usability, we aimed for at least 90% of users to successfully complete the redemption flow without abandonment—a significant improvement over the existing experience.
All of this needed to be delivered on schedule, despite the complex vendor relationship with Epsilon that added layers of technical and communication challenges.
Results & Impact
Our platform drove engagement up by 37% in the first quarter after launch, as customers discovered how much easier it was to use their rewards.
The story gets better with redemption flows - what was once a frustrating experience completing only 68% of the time now saw 91% completion rates, showing our redesign truly removed barriers.
One customer summed it up perfectly: "It's finally easy to find and use my rewards." This validated all our hard work.
The business impact was equally compelling: retention increased 12% among rewards users, our scalable design system was adopted throughout the organization, and we built a collaborative model between design, engineering and vendor teams that continues to deliver results.
Lessons Learned & Solutions
Earlier low-fidelity prototype testing would have been valuable - we discovered users wanted a more visual dashboard approach only after weeks of design work.
Solution: Implement a rapid prototyping framework with weekly user testing sessions from project kickoff.
Involving support teams earlier would have helped us prioritize features better, especially for redemption tracking.
Solution: Create a cross-functional advisory panel that includes frontline support staff and meets bi-weekly throughout the design process.
A staggered rollout instead of a big-bang launch would have provided real user data sooner, allowing us to optimize features like the rewards calculator before full release.
Solution: Develop a phased release strategy with clear metrics to evaluate at each stage before proceeding.
Future iterations should focus on personalization - our research showed customers respond significantly better to tailored rewards suggestions.
Solution: Build a recommendation engine powered by machine learning to analyze transaction patterns and suggest relevant rewards.
Reflection
Looking back, I'm proud of how I navigated this complex project with multiple stakeholders. I learned that staying true to human-centered design principles wasn't just theoretical, it helped me cut through constraints and deliver real, measurable results that made a difference for both customers and the business.