THE FUTURE OF MUSIC DISCOVERY
Research shows that many Shazam users identify a song and then quickly switch to another app, missing out on the platform’s full potential. Our goal is to deepen user engagement by encouraging them to explore Shazam’s broader features, keeping them connected and enhancing their overall experience.
Project Goal
My Role
Project manager, UX Strategist, and designer in a group of 3.
Timeline
2 weeks
Tools
Notion, Monkey Survey, Figma, and Figjam
Methodology
User interviews, surveys, Competitive Analysis, Features Prioritazion, User Flow, Usability Testing.
PROJECT OVERVIEW
The Brief
Design new features on the Shazam mobile app to increase user engagement. While Shazam is known for recognizing songs, many users are unaware of its full capabilities. Our team explored its ecosystem to understand users and identify areas for improvement, focusing on enhancing the overall experience.
The Problem
User lacks a clear understanding of the app's features, preventing them from fully personalizing their music experience and connecting with music that suits them.
The Solution
Develop features in the mobile app that use AI to help users discover new music tailored to their tastes while also offering better organization of their Shazam-identified songs.
Discover
Research user needs and business goal
Define
Synthesize research to define persona and problem statement.
Design
Ideate solutions through sketches and build wireframes.
Deliver
Test Solution Iterate on designs.
Takeaway:
After analyzing competitor features, the focus will be on identifying the most critical user needs and frustrations to inform the development of a viable MVP, rather than trying to match all competitor capabilities. The next step is to dive deeper into user research to select the right set of features for the MVP.
Exploring Our Competitors
Competitive Analysis
Discovering our users
Shazam's data revealed users typically spend less than 30 seconds on the app. This insight led to a clear business goal: Increase user engagement time through new, compelling features.
Our research aimed to: Understand user behaviors in music discovery, curation, and interaction, identifying key experience factors.
Methods
User Interviews & Sureys
Competitive & Comparative Analysis
My team and I conducted 10 interviews and 12 surveys with current and former Shazam users to identify their pain points and understand their needs.
Research Data
user Interviews
of users deleted the app because they didn’t perceive its value
20%
of users would recommend shazam
30%
are searching for feature that already exists but are unaware of its potential
50%
How Our Users Discover New Music
Data from survey
Discover new music through social media and playlist streaming apps
80%
50%
Discover through friends and family
Discover through radio stations.
30%
Quotes
“Sometimes Shazaqm can’t find new songs or remixes. It would be greate if it could identify alltypes of songs, including original tracks.”
“It would be cool if there’s an AI feature that the app can listen to live music or covered an actually detect music that are not mainstream or just from spotify.”
“I just take screenshots of whatever appears. I’m not sure how it works, weather it’s saved under my name or recorded somewhere. For an app that I used so often and I owe a lot to, I don’t know what other features it offers.’
Key Insights:
-
Users crave a diverse platform that offers an extensive selection of music genres and styles.
-
They seek multiple ways to discover music, such as voice search, personalized suggestions, and curated recommendations.
-
Tools that help users efficiently organize and manage their music libraries are highly appreciated.
-
Tailored recommendations that reflect individual preferences significantly enhance the user experience.
Defining our users and their pain point.
Drawing from our interview insights, we created Sam, a persona representing our typical user. Sam's experiences and needs really helped shape our design approach, making sure we focused on the target audience's goals, needs, and frustrations.
Our Target Audience
Persona
Takeaway:
Sam represents a tech-savvy user who loves discovering new music but is frustrated with current platform limitations in personalization and music discovery features.
Ideating Solution
Brainstorming features
Features prioritization (MVP)
After meeting with users and identifying their pain points and needs, we brainstormed as a team to define what features can we develop for our users.
Low Impact, Low Effort
High Impact, Low Effort
High Impact, High Effort
Based on our research, 80% of users love the Spotify playlist feature. While Shazam offers a playlist of Shazamed songs, it lacks organization and categories. This is an area we can improve with minimal effort and high impact for our users.
AI features have rapidly transformed our industry, with many apps and modern technologies using AI for assistance. By integrating this feature into our design, we enable users to connect more deeply with technology and stay ahead of industry trends.
We also developed a swipe feature that allows users to swipe to a song of a similar genre immediately after Shazam identifies a track.
After listing all the features and organizing them into a matrix, our team analyzed which features to implement into the design, taking our limited timeframe into account.
Medium Impact, High Effort
Importance
Impact/ Potential Rewards
Feature Prioritization Matrix
High Impact, High Effort
High Impact, Low Effort
Low Impact, High Effort
Low Impact, Low Effort
Insider: The idea of an AI bot came to me after visiting the Metropolitan Museum. During a fashion exhibition; Sleeping beauties, the Met collaborated with OpenAI to create a chatbot for Natalie Portman’s wedding dress, allowing visitors to interact with the artifact and bring it to life.
Ideating Solution
Bringing our Idea to Life
Studio design and Wire-framing.
Studio design and Wire-framing.
My team and I collaborated in a design studio, sketching wireframes and developing a design solution with a clear goal: enhance user engagement on Shazam, but also help to better user experience. We structured the experience around three key tasks for users:
1st Iteration after design studio
2nd Iteration before usability test
We decided to replace the Shazam button with an AI shortcut for quicker access, while keeping the original swipe-up gesture for users to identify songs as usual.
Attempt to discover a new song on Shazam after song identification.
Add that song to a new playlist.
Interact with Ai chat bot.
Usability Insights- Round 1
Engagement time increase by 100%
The recommendation rate has increased from 30% to 66%.
8.7 - Average user score, with 100% of users satisfied with the new features.
I created the swipe animation for the onboarding program, but due to time constraints, we couldn’t finalize the onboarding process before the low-fidelity test. As a result, we left this animation element out, causing users to miss the purpose of the swipe button during testing.
If we have more time, our team would love to circle back with this idea and tested it with our user and see if there’s feedback or reaction from users.
Time constrain
Validating Shazam’s Design Choices
Usability Testing
We conducted two rounds of usability tests to ensure our new Shazam feature is user-friendly, intuitive, and meets user satisfaction. The feedback from these tests influenced our design refinements, with the main changes detailed below.
3rd Iteration Before Next round of Usability Test
Adding onboarding process for users to navigate
Adding onboarding process for users to navigate
Adding consent to confirm user’s information/ location.
Usability Insights- Round 2
70% roughly of users were able to return to home screen after creating playlist
Every participant in our usability testing said they would recommend the redesigned Shazam app to others. This 100% likelihood to recommend underlines users overall satisfaction with the app’s new features, design, and usability.
AI is the biggest stand out and should receive the most resources for next iterations
9.25 out of 10 satisfaction rate from users.
4th Iteration- High Fidelity (Final)
