TREKKR [STUDENT PROJECT]

Role    |    UX Researcher, Co-Product Manager

Insight    |    Jumping into designing a high-fidelity prototype too soon caused us to stray from our original goal and put out a prototype that attempted to solve many small problems rather than the one we had originally set out to solve. Our UX research confirmed that people wanted a solution to the problem we'd hypothesized and helped us get back on track toward solving it.

Problem    |     If you don’t know where exactly you want to travel to, it can be difficult to come up with a location. This can be due to lack of knowledge of the area or how to get to that area, a constrained budget, information overload when you google “cheap trips”, or even a lack of agreement amongst your group. Once you’ve figured out where to go, you then face several steps to plan the trip. We aim to help our users to find their perfect travel location and plan their trip all in one place.

Process    |    We focused our research on two primary user groups under the umbrella of millennials - undergraduates and young professionals. We started by conducting contextual interviews and observations of the users performing their normal process for searching for and booking trips in the environment in which they normally do so. We studied and synthesized the qualitative data to generate personas, affinity diagrams, user task scenarios, and workflow models that we then used to inform the creation of our lo-fi prototypes.

We then conducted user think-alouds on our lo-fi paper prototypes. The use of paper prototypes provided both benefits and challenges. It allowed us to make three very different versions very quickly in order to learn what worked best for users on very granular tasks during the think-alouds. By designing three distinct prototypes and user task scenarios, rather than three prototypes aimed at solved the same problem, meant that we got way ahead of ourselves adding additional functionality that hadn't been asked for. As a result the overall goal of the application did not come through. The feedback we got from users, who asked for stronger recommendations of travel locations, helped to reinforce the need for the solution that we had originally hypothesized.

We finished with a high fidelity prototype that took the best components from each low-fi prototype and brought them together in a smooth and intuitive feeling and flow and that solved the problem we had set out to solve.

Methods    |    Contextual Interviews, Persona Creation, Scenarios, Affinity Diagramming, Work Models, Cognitive Walk-Throughs/Think Alouds, Heuristic Evaluations, Control Experimenting