Moodcast
Mobile app suggesting podcast based on user’s mood
Mobile app suggesting podcast based on user’s mood
This was a school project with the task to design a podcast app. Using online statistics as my starting point of concept development, along with discoveries from my own research, has inspired me to design a podcast app suggesting based on user's mood.
Everything!
Tools
Research, ideation and design
To understand existing podcast trends, I have conducted research online, here were my findings that I found particularly interesting:
of Australia listen to podcasts, lower than the global average than 41%. (Sang et al, 2020)
More than half of podcast listeners consume podcasts while multitasking:"59% have listened while doing housework. 52% while driving. 51% while cooking. And 46% while going for a walk.” (The Edison Research, 2017)
The statistic on multitasking sparked my interest most, thus I decided to begin from there.
To dive deeper into understanding the habits of podcast listeners, an interview was conducted with three interviewees who were occasional podcast listeners.
My interviewees multitasks while they listened to podcasts. Two of my interviewees listens to podcast while sleeping, while one listens while driving
they were two deciding factors into whether or not they would continue listening to a podcast.
My interviewees multitasks while they listened to podcasts. Two of my interviewees listens to podcast while sleeping, while one listens while driving
2 behavioural archetypes were then developed based on my interviews:
Podcast listeners who listen to podcasts before they sleep or while they’re sleeping
Finding a comforting podcast for her to listen to before she falls asleep
Podcast listeners who listens during their ong morning drive to work.
Finding a comforting podcast for her to listen to before she falls asleep
After the interviews, I have gathered some key points and revisited my research afterwards.
A pattern I have found between these users was that they struggled with interacting with their podcast apps while conducting the task they were doing: Driving users can’t look at their phones while driving, while users falling asleep had issues with making interactions with their phones in the dark.
How Might We ease interaction between multitasking users and the app?
Another important point that stood out to me was when asked about what factors influenced their choice of the podcast, one commented on how the host’s voice always factors into whether or not they will listen to it or not.
How Might We increase confidence in the user's choice of podcasts, so interaction can be minimised between multitasking users and the app?
Not only should we enhance interaction for multitasking users, but we should make users feel more confident in their choice of the podcast, so interactions would be minimised.
I have then took the pain points of users, and began ideating opportunities to solve these pain points:
To narrow the scope of this project, I have decided to only focus on sleeping podcast users.
How can I design better experiences for these users so they can have a better night’s sleep, improving motivation and performance the next morning?
I have then wireframed screens before putting into high fidelity prototype:
Final solution
My final solution is 'Moodcast', a podcast app that generates recommendations based on user's mood.
For multitasking listeners, they can enter specific modes that enhance their listening experience.
Because of time constraints, I have only developed a solution for users that listens to podcasts while falling asleep. Here is a full view of the final solution:
Fun onboarding screens
Pick and choose a mood
1. Users choose how they're feeling and a task they are doing
2. Recommendations are given based on this. (Eg. if the user is feeling ‘restless’, podcasts of meditation or ASMR will be recommended. If users ‘need a good laugh’, humour podcasts would be recommended)
3. Tasks dictate on what mode users will be taken to
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Extensive filters tailored to different tastes
Soothing noises for a better sleep
Minimal lock screen
Seamless experience with Fitbit or Smart watch
1. Connecting electronic watches or Fitbit to app
2. When watch detects a declining heartbeat rate, volume starts to fade and turns off, saving battery and providing listeners with a better listening experience
Using data collected from listener’s's smart watches, the app could recommend better podcasts to other app users. For instance, if data shows users on the platform fall asleep quicker to a certain meditation podcast, then it will be more frequently recommended to other listeners facilitating better recommendations.
Takeaways and future considerations
This was a school project that spanned for a duration of 4 weeks where I was taught UX design thinking and put it to practical use.
If this was a real project. I would take time to do more research into podcast listeners, interviewing and observing their behaviour to identify needs and pain points.
Additionally, I would also conduct research into non podcast listeners, and explore on 'tasks' more, designing features for more multitasking listeners.
Technical feasibility would also be a consideration in a real project, such as how would voice be defined? and how would we generate recommendations based on moood?
