UXDI Project 1 Retro: Friend Food Finder
Background
My first project for the General Assembly User Experience Design Immersive was centered around researching, identifying, and addressing a problem around food. This project spanned 2 days, at the end of our very first week of class.
I initially assumed most people would want cooking recommendations, ways to stretch meal prep for many days, to cook in a big batch at the beginning of the week, to get sufficient nutrients on a tight budget. These concerns may have simply been my own projection onto the project, and it was quickly apparent that my users were much more interested in dining out.
User research
For this solo project, I interviewed 3 classmates and 2 family members, 4 women and 1 man, ages 25–87. I asked open-ended questions to explore the depth and breadth of the topic with my interviewees. I tried to follow up on common threads between my interviews, but mostly to let the conversation flow. People were the most revealing when I allowed them to follow threads of interest to them. I found it difficult to respond without agreeing, or being too positive in my listening (nodding, affirmative noises, etc).
When asked how they discover new restaurants, users said,
“…it’s nice getting a recommendation from someone I know who can already confirm it was a good experience or can recommend something on the menu.”
“I walk a lot, and sometimes I see a new restaurant and I write it down. Usually it’s by a recommendation. I don’t trust Yelp, and I know which friends whose opinions I trust to tell me about something I would actually like.”
“I definitely am aware that people from [Yelp] will like food I don’t like, but I still want to keep trying it. Maybe I will find something I like. I like to explore and keep trying.”
This state of affairs spoke to me. These devoted diners were using all the best information at their disposal, putting in the right research, trying to discover on their own, and it still wasn’t cutting it. The beacon of hope here was that everyone has friends whose food recommendations they trust, and their sense of adventure was encouraged by finding wonderful dining experiences.
Synthesis
As a part of my synthesis, I created an affinity chart. I listed attributes stated in interviews, especially those common to more than one interviewee, then marked an X for each user for whom it applied. I also grouped these recommendations (the color coded categories to the right) by their subsection within the larger “food” umbrella. Question marks were used for similar but not exact response matches.
The most common threads throughout my interviews were that each diner preferred recommendations from friends when they went out to eat, and that the preferred cuisine was always from Asia. Additionally, diners valued social dining experiences, healthy, seasonal, fresh, varied, and local food. I intended that some of these categories should be listed within the app.
It was clear at this point in my research that socializing around food and dining experiences was important to my users. Food type was my most frequent category, but my participants did not always rank it as their most important determinant of dining out. Many users wanted to eat food that they couldn’t cook at home, food with variety and a sense of adventure. Health was also a recurring important factor for many diners.
I identified an insight, a research problem, and a question to help focus my ideation.
People prefer to eat at restaurants based on recommendations from friends. Mostly, they get sub-par recommendations from internet sources, which they deem less trustworthy. How might we help them easily connect to food recommendations from friends?
Ideation
Brainstorming! It’s so freeing to let your imagination run without restraint, and that was the exact approach I tried to use to ideate on the problem I had identified. Users want to know what their friends think of restaurants, but they also want to eat food they will like and feel good eating. Many users had indicated that they trusted recommendations from others within limits.
I wanted users to feel like the experience itself was friendly and simple, and that it included basic sorting features such as cuisine, price, and location.
Testing / Iteration
I used my paper wireframes to test my user flow, and to ensure that users could perform the primary functions of my app. In user testing, I asked 3 participants to:
1. Find Helen’s restaurant recommendations
2. Find a new place to eat that you have never been to before
3. Bookmark a restaurant you’ve been meaning to try
For the first task, 2 of 3 users navigated to the “Friend List” button, selected Helen, then looked through her recommendations. One user went to the “Friends Recommend” button, and when she did not find what she was looking for, she backtracked easily and took the correct path. This interaction did lead me to believe that these button names may be too similar.
For the second task, All 3 users chose to “Explore,” and the first user chose the first option presented. She stressed that location was important in choosing a restaurant, because no matter how good it is, if you have to travel a long time to get it, it’s too far. I think this could be resolved by including proximity as a selectable factor for search criteria. The second user wanted to also look at the recommendations of friends, and the third user would have been happy with any of the first three buttons.
The third task flowed less smoothly. Users did not intuitively navigate to the bookmark button to mark a new restaurant. All 3 wanted the option to bookmark a restaurant from a friend’s recommendations, or from the search feature to prevent needless back-navigation. I incorporated this user feedback, and added the option to bookmark restaurants from any place where a selection appears. The ultimate list of Bookmarks remains the same, as a touch point for reference. One user wanted to bookmark places he had already been and wanted to return to, as opposed to just new restaurants.
Wireframes
In my wireframes I attempted to address user issues, chiefly the ability to connect with friends and their recommendations. I also considered other user wants and needs, such as the ability to choose food based on location, cuisine, price, or top ratings. My main aim was to allow users to get the most trustworthy ratings from friends in as many ways as logically possible.
Prototype
My Marvel prototype enabled me to bring my little paper screens to life, and to act like a real app. This part is like magic. Please click around, and let me know what you think!
Next Steps
In the future, I would like to incorporate a feature that would enable users to contact one another to schedule a dining experience at a mutually bookmarked restaurant. I also intended for location to be one of the sorting criteria, but did not wireframe a map option. I would like for users to be able to find recommended restaurants nearby, perhaps through a map screen pinpointing the locations of friend-recommended restaurants close to them. I also did not explicitly state that ambiance and service should be categories listed as search criteria, but I think those would be novel features to add to an app.
Of course, I would also prefer for the app to undergo further user testing to ensure its usability.
