I led a redesign of the Client Profile section of the AlayaCare app (an area visited by tens of thousands of users daily), including improvements to the Information Architecture (IA) and the design of specific pages.
I conducted a card sorting exercise, analyzed data analytics, ran internal stakeholder testing, and carried out prototype testing with users.
This project resulted in increased user satisfaction across three markets (US, CAN, AUS) as well as increased engagement with and connection to the users via the creation of an online AlayaCare Research Community.
Project Lead, Product Designer
Information Architecture, Card Sorting, Data Analytics, Internal Stakeholder Testing, Prototype Testing, User Testing, Visual Design
Optimal Workshop, Amplitude, Miro, Framer
2022
Upon analyzing the client profile of AlayaCare’s home health/care facilitating application, it became apparent to me that sections of it that I would expect to be grouped together were far away from each other. I considered the consequences of a poor information architecture (IA) and how it could negatively impact the onboarding of new users onto the software, affect user workflow efficiency in general, and cause difficulties in the future as we plan to edit and consolidate related pages.
Information Architecture skeleton of the original client profile
I set out to test my hypothesis of our IA by first organizing an open card-sorting exercise with some colleagues, whereby each person would sort the different features found in the client profile into categories that they would assign themselves. The results of this exercise would show me how each person would organize the client profile based on their own logic and if there were any patterns emerging from the sortings that could help inform the next iteration of the client profile IA. Also rather than labeling the cards with the exact name of the feature as displayed in the app, I tried to describe the feature’s purpose to help lower any conformation bias.
Results of one of the card sorting exercises
I followed 11 people over Zoom video as they completed the card sorting exercise, asking each to narrate their thought process throughout so I could better understand their logic.
Many similar organization-related patterns emerged from the results of the study between each person. Finally, it became apparent that there was a discrepancy between how the people in my study would organize the client profile and the existing IA in the app.
To further test my hypothesis, I looked at user behaviour data on Amplitude to see which pages were being most visited above others and to understand the journey users were taking from one tab to another.
miro workspace showing the various user segementation charts I analyzed
The results of the data analytics were substantial: I learned that certain pages could be deleted because of near 0% visits, the logic of the various user journeys showed possible tab/feature groupings which resonated with the results of the card sorting exercise and the order of tabs could be rearranged based on chronological and frequency of use. In short,
After creating a first proposal of a new IA skeleton, I invited key internal product and CS people from different markets to analyze the drafted IA and offer their comments and thoughts. Their feedback informed a second proposal which was now ready to be tested with users.
miro workspace showing first IA iteration and comments from key internal colleagues