Our team worked on “plates,” which we envisioned as a platform helping to connect people over convenient, affordable meals. When we began, I had thought that many students on campus would be interested in meeting new people, and was under the impression that bringing people together through food matches–especially 1-on-1s–would be an effective way to do so.
While many of our assumptions were validated especially as we led conversations with potential users and gleaned valuable insights from their experiences, we also found that our perspectives were nuanced from the interviews. Some key learnings were that some individuals expressed reluctance to travel far for a meal, and asserted that a compelling-enough reason was required for them to feel that the effort to get the food was justified. Potential ways to convince them that picking up the food at a certain location was “worth it,” include if the food seemed to be of good quality or was something they could not easily access on campus. The prices of food was also a salient factor, especially if they were less expensive compared with other food delivery apps like DoorDash, or if they were comparable or even lower than those found at the restaurant.
I also discovered, after actually bringing together a group of people for a meal to more robustly test assumptions and simulate a random group “match,” that people are indeed open to the idea of eating together for “plates.” A note is that by matching 4-6 people, it is very possible that some people in a larger group may know (or know of) each other, as was the case in our test. Upon further reflection, I thought that having 4-6 people matches could be a better way to start a launch of plates, as it also helped to address potential concerns surrounding safety–it could feel more safe if there was a group, in comparison with the date-like undertones if matches were to be 1 on 1. Moreover, although we started out with the intention to also offer a single-person ordering option (for the sake of convenience, if people are busy and want to eat individually but still want to make a food order), we decided not to focus on this option at least initially because we decided to focus on the social matching part of our product, in addition to bringing affordable meals.
Another learning from our tests, however, was that there was some ambivalence to the idea of randomness when it comes to matching; however, they would feel more comfortable if they have some information about the people they are meeting beforehand (such as other people’s interests). Therefore, we would envision that users could see some basic interests and identifying information about their group match, and potentially a response to a more lighthearted and fun prompt, which would help them have some initial talking points when first meeting each other.
With more time, it would be interesting to explore potential ways to further engage people in social meal interactions. This might look like organizing an event or contest between groups to potentially build cohesion and camaraderie. We might also explore whether it could be feasible to bring people to the restaurant itself, perhaps via a partnership with ride-sharing services, which could be a novel addition to our vision of connecting people over convenient, affordable meals.
