Mobile. Material.IO. Finding Information.
SongEats
Food review and search applications are used commonly today, whether it be on mobile or desktop devices. As South Korea in general uses mobile phones for a countless number of purposes, a mobile app is weighted more heavily rather than a cross-platform application at first due to how widely phones are used over other devices.
People like to eat. People want to eat. People need to eat. The cup of ramen or microwaveable dinners or fast food restaurants solves the problem of accessible food, but what about finding good food? With this in mind, I hone the focus on this problem:
The problem: I want to eat delicious food.
If people want to eat delicious food, they make an effort to get it. Whether it is buying ingredients and homecooked meals, or going out to eat, people want delicious food.
The solution: Create a way to find delicious food through a mobile app.
SongEats received good reviews from user testing across the board and kept a respectable efficiency level.
Designing a product for a different country provides an extra layer of difficulty as I need to find ESL interviewees or a way to translate responses from interviewees. I started with surveys I distributed out on forums used by Koreans and/or Americans.
Surveys were a quick, inexpensive way for me to get the information I need, and sticking with text based answers early on allowed me to translate any Korean responses into English easily.
Personas were derived from the responses and criteria across all interviewees. Personas were created because I wanted a way to represent a larger group of people and draw a metaphorical circle on who we're designing for.
Some responses were in Korean, so I translated them into English and verified what they said with a bilingual Korean/English speaker on my end.
Writing down the goals and frustrations was a starting point, but I also needed to figure out their process from start to finish when actually using the proposed app so there are neither too few or too many screens to navigate through.
The user journey was created and extrapolated from the surveys. While users go about finding food in their own personalized way, their needs and pain points for finding delicious food are likely to be consistent.
How can we help users find the best restaurant choice in a specific area?
The SongEats application I design lets users review restaurants, choose where to eat, and give the means to clearly and accurately decide the best locations to eat.
There are multiple American and Korean restaurant apps available for download, so I examine several direct competitors to see what they provide, where they operate, and where there are opportunities.
A competitive analysis was necessary because there are plenty of products that do what we're trying to design already with sizeable market shares. It wouldn't hurt to look at opportunities and strengths of these companies to figure out what we can do well and better.
Noting from the competitive research, each competitor excels in one thing: searching for restaurants. Rather than design a completely different system, it is better to adopt current conventions, follow Jakob's law, and set up the application similarly to competitors. Mapping out information architecture will reduce the amount of time and screens I need to account for and keep scope in check.
After I have defined the personas, the user journey, as well as looking at our competitors to see how they solved their user problems and defined the information architecture for what to actually build, I began on designing the wireframes and a round of user testing on the initial prototype.
Low fidelity prototypes trade off reliance on the user "knowing" what does what and inferring how to navigate the app design, but allow for rapid iterations.
I tested the general flow and functionality of all features made within the user flow diagram. My assumptions going in were users could navigate and select restaurants of their desire, as well as edit items on their profile.
I found 8 people with English capability or translation available and 20-30 minutes to spare to go through an unmoderated, recorded testing session with the prototype.
Armed with plenty of insights about what the users really want out of the product, the changes to make, and the guidelines I made to follow, I moved into the final product mockups.
The colors used for the solution should be part of the Material.IO color guidelines as well as different enough from all other competitors its color scheme alone sets it apart.
The font is Noto Sans as it supports characters across multiple languages including Korean and fits within the Material.IO design system.
Users mainly start the journey by opening the SongEats application and searching for something they want to enjoy.
If the user isn't able to find a desirable restaurant on their first pass, they may refine their search criteria further.
Perhaps the user second guesses or isn't sure if the restaurant is the right choice afterall. Plenty of information is given to alleviate this concern.
There were two ways competitors commonly determined ratings: the 1-5 star system and a 3 mood system. More Korean-based competitors used the 3 mood system, so I incorporated that instead, as our focus was for Korean users.
The 3 mood system scores a restaurant between 1-5 with 3 choices given to a user. Like is 5 points, So-so is 3 points, and Dislike is 1 point. The algorithm takes the average likes to so-so’s to dislikes and produces the final review score.
The user successfully chose a restaurant! To get there, they might need directions and I have a map to get them there.
SongEats also allows users to create a profile through the app, tracking all of their reviews, photos they submitted, and lists of all their favorite restaurantsMake a List and Check it Twice
Users, when they set up a profile, can also track their favorites and set up lists to share with others.
Users can alter the native language of their application, they can access any screen from the hamburger menu in any part of SongEats, and they can refine their search criteria even further beyond a search term and tags.
I built a functional prototype of the software in Figma as well including the interactions between dialog windows and in-line editing.
It was more difficult than expected to design an app for an international audience. You’re dealing with language barriers and cultural barriers, and what might work for an American-centric audience wouldn’t fare as well with a Korean audience due to how drastically different their social and cultural backgrounds are.
In the future, I hope I can make more advanced applications and features, as this is only the start. I could see future features added, such as more expansive list options or more information displayed for each type of restaurant and even filtering by amenity types.
If I were to improve the app in the future, I would first change the look of the app to conform with any new Material.IO guideline updates. Next, I would figure out the primary pain points with user research after the product is released then hone in on features/changes to alleviate those issues.