EatRight Mobile Application Find Healthy restaurants close to your location.
My Role: UX / UI Designer, Researcher
Project Duration: 3 months
Team: Individual
Programs Used: Sketch, InVision, Optimal Sort, Loop 11, UserTesting.com
Problem
It is easy to eat fast food but to find healthy restaurants that are high quality, taste good, have great service, and are close to a given location is a challenge. Conducting this search on apps like yelp does not provide enough information. An overall 4-star restaurant rating does not inform users much about food quality, service, decor, and taste. Also, discovering nutritional details about foods in restaurants can be a challenge as well.
Solution
A mobile application called EatRight which helps people discover healthy food options quickly and without a hassle. This application caters to people’s specific dietary needs. It helps them to choose healthy options that promote a healthy and nutritious lifestyle. Anyone that believes food is medicine will love using this application.
Research & Development Process
Initial Sketches
These were some of the initial sketches that I came up with before starting the wireframe process. Right from the beginning, I had a general idea of what I wanted to build.
Low Fidelity Wireframes
Before moving forward into high-fidelity screens I used my sketches to design low-fidelity wireframes.
Testing Methods
Below are the testing methods that I used to evaluate the EatRight application.
Card Sorting Test Objectives
The Card Sorting test was done in Optimal Sort to figure out the most intuitive category names for the application. I also asked survey questions about healthy eating to understand if there was a market for this type of application.
Naming Convention Results
There were 4 category names that were repeatedly created by participants. Below are the results. I added these words to the “get started” and the “food type” page in the application.
Survey Results
The survey results showed that searching for healthy restaurants is important for people along with high-quality food. This confirmed that there was a market for this application. Below are the survey results.
Quantitative Test Objectives
I conducted a quantitative test in Loop 11 with 37 participants to figure out user difficulty levels of completing 2 tasks in the application. The success rate was over 75% which showed me that people understood how to navigate through the application. I also asked questions to understand if the app serves its purpose. Below are my results.
Qualitative Test Objectives
I conducted a qualitative test in usertesting.com to gain insights into the thoughts and feelings of users while they performed 3 tasks in the application. I used three participants in this test. Below is some of their feedback.
High Fidelity Screens
These are some of the main high-fidelity screens that I designed.
Conclusion
My qualitative and quantitative user tests show that most people liked the EatRight app. They liked the vibrant colors and the use of images. They saw a benefit to it and they thought people with dietary restrictions could benefit greatly. Most users thought it is easy to use and did not have difficulties accomplishing their tasks. There were some changes that the participants wanted. Below are the 6 most high-level changes users wanted to see in the future.
Next Steps
Final Prototype Video Walkthrough
