How do we increase Shazam's Screen time?
Currently Shazams greatest strength is also its greatest weakness, simplicity. Though it has made countless design iterations through out its 21 years it remains at the top of music discovery applications because of its always reliable core feature which is identifying a song.
This is a concept made only for an academic exercise, my team nor I are affiliated with Shazam.
My team and I started everything with the Problem Statement
“Shazam needs a way to utilize their excess amount of user-centered data in a way that increases user engagement with their app.”
The first thing I launched into was the C&C Analysis.
Moving away from C&C we then wanted to hear what current users experiences are like from our User Interviews.
Below is a quick synopsis of the most important questions users were asked.
Heres is a look at the extensive interview questions.
From here we moved onto making a current Site Map and User Flow:
Last but not least in the research phase, we did some Affinity Mapping.
With so much user centered data at our finger tips, it was time to create a Persona. It started to become more and more apparent why Shazam currently struggles with increasing users screen time in the app. A lot of the features have almost been hidden away and most users had no idea where or what they did.
Think, think, think…our team started to form some Sketches for what may help Shazam improve its screen time. The two ideas we started to iterate on was creating a more stream lined layout for the whole app that has onboarding, and a new Super Shazam feature that utilizes Shazam's user data and location.
Now comes the fun part, lets check out some first iterations the team and I came up with as our Moodboard and Wireframes.
• blue: shazam’s main color, home
• black: My Shazams, history of precious tags
• yellow: new feature: Super Shazam
Super Shazam is our solution to a no-fuss way to discover new music that excites the user through colors, animation, and more gestures. Users use this to generate a list of songs that are top Shazamed at a desired location
A list is curated to users and makes use of Shazam’s excess user-centered data
and works in conjunction with individual user-inputed preferences
recommended songs that are Shazamed by other users with similar tastes.
With our final features iterated and tested it was time to make our High Fidelity prototype interactive and see what the next steps are. this is our Before and After of Shazam.
FIGMA: High Fidelity Prototype Link
Thank you the reader for following along on this journey of music discovery, if you made it this far I really appreciate you taking the time to see what became of our design and where we want to take it. Just below this you will find our Conclusions from the final usability test, and the next iterations to our project.
Special thanks to my team members: Katrina Allick and Vicki Chen
