A self-service model of a secure file transfer process was proposed as an important new product feature. This would allow customers to manually upload their sensitive human resource employee data.
The customer side of the process was fraught with technical and tricky human processes (like getting cooperation between departments to create pre-merged files) and the on-screen solution needed to be simple, and user friendly to international, often non-English speaking users.
The also had to be fault tolerant and catch any data quality issues early and to help the user fix them easily in a new, self-administered paradigm. If successful, it would significantly reduce time and effort for on-boarding for large multi-national customers.
I created multiple scenario tests in order to do remote testing of customers using clickable prototypes on the Maze testing platform so I could record important feedback for validation and usability sessions.
A live video camera feed collected customer voice and facial responses to help unpack the client feedback and identify friction points that greatly helped get actionable insights on the experience. The Maze platform also collected task completion time, pathway results and screen mouse-click data displayed in heatmap displays. And it also collected feedback to generate SUS score results. Overall, this research was a powerful way to collect the data we needed from customers in different time zones, and at scale for the time we had, to guide the final mockups and help create the a simple interaction design that we could confidently give to developers.
Adobe XD, Maze.io, Adobe Photoshop, Leonardo AI (for illustrations)
