Shazam
ADDING COMMUNITY FEATURES INTO AN ESTABLISHED ECOSYSTEM
INTRODUCTION
Music discovery has become an integral part of the modern listening experience, with apps like Shazam helping millions of users instantly identify songs on the go. However, despite its advanced algorithm, Shazam is not always able to recognize every song, which can lead to frustration for users seeking to explore new music. This case study explores the challenges users face when Shazam fails to identify a song, and presents a solution: a new feature within the app that allows users to save song samples for later identification or discovery, ensuring that users can continue to discover new music.
PROCESS
Throughout the design process, I worked to develop the initial concepts and prototypes, while regularly seeking feedback from a group of designers. Their insights helped refine the design and ensure it addressed key user needs, particularly in areas like usability and visual clarity. We held feedback sessions where I presented iterations and made adjustments based on their input. This iterative approach enabled me to refine the user experience, ensuring the solution was both efficient and user-friendly.
PROJECT SCOPE
A team of designers.
Jan 2023
TOOLS
Figma, Miro, Maze, Slack
Problem Statement
Shazam is not always successful at identifying songs.
Although Shazam allows people to quickly and easily discover new music, the app is not always successful at identifying the songs using its algorithm. With no results from its database, users are not able to figure out the name of new songs and artists.
HMW help users discover more songs that were not identified in the app?
The challenge was finding a way to identify and discover songs that Shazam's algorithm couldn't recognize, while still providing users with a smooth and enjoyable experience in exploring new music.
The Solution
A feature that manages and crowd-sources song samples
Users can now save song samples when Shazam is unable to identify a song and share them with friends or a community of users for further discovery.
When Shazam is unable to identify a song
Saving a Sample
Name the sample and add an image to personalize
See a list of samples in a library
Creating a Post
Adding Samples to Lounge
Share the sound sample with a community of users
Help other users in their music discovery
Preview
Dark Mode
User research revealed that some users preferred using Shazam in dark mode. To address user needs and ensure inclusivity, I added a dark mode option to the app.
Impact
Future Development
Projected Impact
Although the feature has not been released yet, based on usability testing and competitive analysis, we anticipate the following outcomes:
Increased User Retention & Engagement
Expected 15-25% increase in session duration as users revisit their saved song samples.
Estimated 10-20% boost in user retention, as saving and sharing features encourage repeat app usage.
Enhanced Social Interaction
Projected 30-40% rise in song-sharing activity within the app, fostering more in-app engagement.
Similar features in music apps like Spotify Wrapped and Apple Music Replay have led to a 60% increase in social shares—Shazam could benefit from a comparable trend.
Business & Monetization Potential
Potential 5-10% increase in advertising impressions, as longer sessions lead to more ad exposure.
Higher likelihood of premium partnerships, as music streaming services may benefit from increased song discovery and conversion rates.
Future Success Indicators
If implemented, tracking the following KPIs would measure success:
- ✔ Number of song samples saved per user per month
- ✔ Number of shares per user
- ✔ Increase in returning users within 30 days
- ✔ Growth in overall app engagement
