Making group dining decisions faster, easier and smarter

We were interested in how people made decisions on where to go, what to eat, etc., so we went to cafes, stores, and restaurants, interviewing professors, students, service providers, and a retired couple. From this, we found that people wanted to "personalize the crowd," allowing users to find other strangers that they could trust for reviews and the like. We decided to specifically explore how people could take the advice of the crowd in streamlining group decisions which seemed to be a major pain point.

Taking into account our initial needfinding interviews, we created two very rough experience prototypes implemented on paper. Accord took users through the task flow of finding a place to eat with friends. Marauder's Map was a way for users to see what other people near them were doing--seeing in real time where were people going. We tested these experience prototypes with users. Some valuable insights we gleaned had to do with privacy/authenticity (Marauder's Map) and the importance of task flow simplicity (Accord).

Given some of the privacy concerns for Marauder's Map, and the clear frequency and ubiquity of group decisions, we settled on Accord. We created a concept video (right) to exhibit the use case and the intended tasks. This helped us to refine our vision for what Accord should (and should not) cover. We decided that we wanted Accord to "make group decisions faster, easier, and smarter."

We experimented with several sketches of different implementations for Accord. Some of these implementations envisioned using AR/VR, smart watches, verbal commands to an app, and an iPhone app. While we were very excited by some of the extended functionality of AR/VR, given that we wanted our app to be quick and simple ("faster, easier, and smarter"), we decided to go with an iPhone app given the phone's relative ubiquity, mobility, and frequency of use. We then went to Arrillaga Family Dining Commons, Bytes Cafe, and Tresidder to test this low-fi prototype with users, and we got some great insights from users on icon use, navigation flows, and information density.

Using the insights from our low-fi prototype tests as well as our studio feedback, we made a medium-fi prototype using Sketch and Marvel. Specifically, we re-envisioned our "newsfeed," which originally copied Venmo's newsfeed (showing user's actions), and made it into a more restaurant-centric experience, showing which restaurants were popular in real-time. This effectively circled back to integrate the most exciting parts of our other experience prototype, Marauder's Map.

Finally, we presented our med-fi prototype to our studio, which then went through a heuristic evaluation from a group of four experts in our class, who spent time out of studio to go through the flow and find any violations listed by Nielsen in his heuristic evaluation process.

Using the feedback from the heuristic evaluation, we created our high-fi prototype with Swift (actual app available for download in Prototypes section). We then prepared and presented a 30-second pitch for hundreds of students, investors, and industry professionals.