Fictional Mobile App
Bgreen helps people understand and reduce their personal contribution to climate change.
How?
A holistic summary of their carbon footprint and suggestions for how to live greener that can be customized to adapt to the constraints of everyday life.
Mobile App
120 Hours
Many people want to help fight climate change, but they face several obstacles
Bgreen: an app that helps you lower your carbon footprint
I conducted user interviews and a competitor analysis to confirm my assumptions and identify a problem to solve.
I interviewed 5 people and learned:
People want to do something about climate change, but there are big challenges to living greener:
“The lack of information…I first need to research these things and see what the sources of the research are”
“You have to spend a lot of time and energy researching stuff”
“The convenience…biking could be a thing, but cars are more convenient”
I brainstormed solutions for the main pain points uncovered during discovery.
Pain Point
It’s hard to understand how your lifestyle contributes to climate change
There’s a lack of credible and accessible info about living greener
Living greener can feel and be inaccessible due to limited time, money, and info
There’s no clear way to compare the impact of different activities
➞
➞
➞
➞
Solution
Calculate your carbon footprint based on your lifestyle, provide clear breakdown of how each action contributes
Provide credible and accessible info
Provide suggestions for how to live more sustainably and let users tailor suggestions to work within their daily lives
Let users compare the environmental impact of different activities
I ranked solutions on an impact/effort matrix and chose those with the highest impact and lowest effort.
Learning Moment
While I had originally assumed that the solution would rely heavily on a social aspect - being held accountable by your peers, and having a tool to get others involved and taking action to live greener - this feature was ruled out as too high effort for an unknown impact
Before focusing on branding and visual design, I wireframed each flow to understand how the user would move through the app. This helped reveal any missing steps in the flows and provided the framework for the final prototype.
Learning Moment
Although the length and complexity of many of the onboarding flows stood out to me during competitor analysis, I ignored my misgivings and proceeded with a similarly long and complicated onboarding flow in my own design. I assumed the competition knew something I didn’t and had the right approach because so many of them were doing it. I was wrong and should have come up with a better solution as this would later come back to bite me during usability testing.
Learning Moment
As everyone’s brain works differently I thought it would be helpful to have both donut and bar charts to display the user’s footprint. But, once I added content the bar chart became cluttered and I realized the donut chart would be more appropriate given the amount of information I needed to show.
I tested the prototype with 4 people using these 4 flows:
Learning Moment
While writing the usability test questions, I was struck again (as during competitor analysis) by the length and complexity of the onboarding flow. In order to ensure test participants could complete the flow, I had to write the questions with very specific directions. Instead, I should have stopped to think about a better solution: a shorter, less complicated onboarding flow with the option to skip straight to the home screen.
I should have asked usability test participants if they could see themselves using the app as a tool to live greener.
4/4 participants completed all 4 tasks
2/4 participants were concerned with accessibility and clarity of UI elements
2/4 participants struggled to use the time picker
3/4 participants said they wouldn’t remember which category was which in their footprint summary without additional labels
2/4 participants were concerned with accessibility and clarity of UI elements
2/4 participants struggled to use the time picker
3/4 participants said they wouldn’t remember which category was which in their footprint summary without additional labels