For my fourth project at General Assembly, I was tasked with creating a passion project that could feasibly be tied to brand. As a biohacking enthusiast, I thought a companion sleep app for the pioneer of the "bed in a box" model would be both relatable and truly further the company's mission. However, I decided to re-envision this sleep app by bridging it with the user's waking life data such as calendar invites and transit information.
Feature & Heuristic
We compared the features and system behavior of competitor custom product marketplaces.
We surveyed 50 people in order to learn more about their sleep behavior as well as their experiences with sleep related applications.
As Casper products are not targeted towards those with muscular-skeletal issues, we chose a 50/50 mix of healthy people who had experience with sleep apps as well as those that didn't to accommodate for multiple user types.
We assembled all of our data from the previous three phases of research and compiled them into emerging themes from which we would prioritize features and arrive at a problem statement and persona.
Notable Interview Quotes
“ Used a sleep tracker, but stopped using because it wasn't useful. Just told me how I slept but not how to sleep better. "
“ I feel so tired in the morning. I snooze it 30 min every morning. Alarm doesn't take me out of deep sleep."
“Told me(tracker) how my general quality of sleep is, what is my ratio of my deep sleep, light sleep… I've never dug into it too much.”
“ I want a sleep app that understands me. Not the other way around.”
Users lamented their bad habit of snoozing, so we decided to create a snooze function that requires a different gesture to disable it each time in order to force users to look at their phone.
Insights Over Data
Currently, most sleep apps only provide large amounts of data that perplex users. Rather, we decided to give people digestible data that allows them to change their behavior. Moreover, we offer recommendations on when to sleep based on this data.
Bridging Waking & Sleeping Lives
Users want recommendations to be relevant to them. As such, we incorporate transit and calendar data and adjust wake up times accordingly(traffic jam, train delays, etc.). to ensure users aren't rushed or miss the things that matter to them most.
Most users found their alarms jarring. To align with users habits of spending a few minutes in bed awake prior to waking up, we implemented a gradual alarm that would gently wake people up and prevent snoozing.
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Documents the process of our persona having his alarm wake him up early for his 9 am meeting after snoozing multiple times.