Product
Mastercard: Validating Design Under Pressure
Securing user validation before a strict project roll-off by accelerating the testing process with AI. De-risking delivery and generating actionable insights for the final high-fidelity designs.
NDA protected
This project is under close NDA protection. Visuals, specific feature details, and client-facing materials cannot be shared. This case study focuses on the approach, constraints, and measurable outcomes.
Users tested
300
across two primary user groups
Ease of use
96% top-box score
Clarity
98% top-box score
Context
Project overview
I joined this project during an ideation phase with the task of developing potential solutions based on user research conducted by a third-party agency.
Over several rounds of ideation and playbacks with key stakeholders within the Mastercard leadership team, the design advanced significantly. It became clear that before moving further, we needed to validate our most recent thinking with real users.
Constraint
The problem
The project was coming to a close with a strict roll-off date. The timeline left no room for a traditional user research setup, which would have meant the designs went untested before the project ended.
Without validation, the team would be handing over high-fidelity design direction built on assumptions — leaving the client with unverified decisions and no actionable data to refine from.
Outcome
My impact
I secured buy-in to accelerate the user-testing process using AI. In just under two days, I developed a mid-fidelity front-end application while the developers prepared the pre-existing back-end solution to be tested with users.
By the end of the week, my front-end was connected to the back-end and handed over to the third-party research company for testing.
The testing covered 300 users across two primary user groups. Notable findings included a 96% top-box score for ease of use and a 98% top-box score for clarity.
We overcame the project constraints, validated our designs, and de-risked the project by providing further actionable insights for the final high-fidelity designs. This was a significant and measurable impact for Mastercard.
Want to validate designs fast inside constrained timelines?
I find ways to move quickly without skipping the rigour — securing the evidence needed to de-risk delivery and give teams something concrete to act on.