Quarantine Companion

Inspiring sociable and healthy behavior through user data insights and accountability.

Time
2 months
Role
UX/UI Designer, User Researcher
Project Type
Mobile Application

Project Overview

Problem: This project was developed as a personal class project, in response to a design brief called “The Quantified Self”. This design brief challenged my team to consider how to use design to demonstrate how personal data could be used as insights for either oneself or one’s community as a whole.

Solution: We developed the mobile app, “Quarantine Companion” to showcase how personal data insights on factors such as socialization and exercise can help users live healthier, socialable lives despite the pandemic.

My Process

Narrowing the Project Scope

Since the scope of the project was wide – as we could choose to focus on any data insight we wanted – my team sought to narrow our focus by picking on two specific user insights: socialization and exercise. In light of the COVID-19 pandemic, these two variables have seen a large downward plummet across the majority of the population in North America. By targeting these behaviors, we could focus our efforts into creating an app that specifically seeks to help users overcome obstacles of the pandemic that prevent physical and mental wellbeing.

Preliminary Research

Although everyone around the world is struggling with the pandemic, there’s still a lot of research we need to do to understand who exactly the users of our app are. In other words, who would benefit from data insights to better his/her health behaviours?

Well, yes, the answer is a lot of people again. But more specifically, let’s take a look at people living in lockdown or quarantine.  Our preliminary research, conducted through the web, found that:
.
Based off preliminary research data and later on, user interviews, we developed the below empathy map.

User Interviews

Our team interviewed 10 people of varying ages, from different countries, and who identified with different gender identities. Some key findings there were highlighted from these interviews were that:
Based off of the interviews, we developed a persona to represent our users.
Problem Statement
Wren, a full-time student and part-time pizza delivery driver, needs to focus on creating healthy routines in a very unstructured environment in order to successfully navigate the new pandemic landscape.

Rapid Sketching

Using our persona, Wren, and the guiding problem statement above, our team set out to rapdily sketch out some ideas for different pages.

Low-Fidelity Wireframes

Our sketches were converted to low-fidelity wireframes over Figma after we shared and discussed various ideas. Another team member and I worked together to create the following low fidelity wireframes based off rapid sketching concepts.

Low-Fidelity Testing: Wizard of Oz Testing

At this stage, we conducted our first user testing through a digital Wizard of Oz test with three participants. The test was conducted as we showed users the low fidelity wireframes on Figma and asked them to complete specific scenarios, such as:
Throughout this usability test, we took note of any issues users encountered as they tried to complete their tasks. Some key findings we discovered from the first test:
In order to combat these issues, our team made a series of changes in our mid-fidelity wireframes. For example, we split up the input section into a series of step-by-step pages to guide the user through the data input process. We also created more descriptive content labels and developed recognizable icons to improve the app’s intuitiveness.

Mid Fidelity Wireframes

Our sketches were converted to low-fidelity wireframes over Figma after we shared and discussed various ideas. Another team member and I worked together to create the following low fidelity wireframes based off rapid sketching concepts.

Mid Fidelity Testing: Think-Aloud Protocols

In order to test our mid fidelity wireframes, we conducted a usability test with the think-aloud protocols. We recruited five users and invited them onto our clickable, interactive prototype to complete tasks such as
This time, we picked up on finer details of the interface
In the improved version of the mid fidelity wireframes, we solved these problems by introducing a colour coded legend and axis to the graph on the main page, as well as adding a graph preference feature option in the profile page to accommodate users better.

Iterated Mid-Fidelity Prototype

The Quarantine Companion project wrapped up after adding improvements to the mid-fidelity wireframes as per testing. Below are a few frames we developed. In order to test our mid fidelity wireframes, we conducted a usability test with the think-aloud protocols. We recruited five users and invited them onto our clickable, interactive prototype to complete tasks such as

Reflection

The Quarantine Companion project introduced me to the process of rapid testing and prototyping, which was a new and enjoyable experience! It was always interesting to see the impact usability testing would have on each iteration, and I really think that’s what allowed this project to narrow in on user needs. Overall, I found this project emphasized the user-centric approach to design, and I enjoyed the opportunity to appreciate how significant user testing can be.