🏆 First Place Winner Amazon Music Design
Designing for Emotional Engagement & Retention
Showed interest in earning and redeeming rewards.
Control Over Algorithm
“if i could get recommendations more suited to my music taste”
Emotional Connect
“More social features, ability to add notes, emotes, or react to songs with friends”
Suggestion Mode
Fine-tune recommendations in real-time for a personalized experience
Rewards & Loyalty Program
Exclusive perks, discounts and engagement-based rewards
What 60 users told us - in their own words
Project Type
Product Design, Design Innovation, Prototyping
My Role
UX Researcher, UX Designer
Project Timeline
4 Month
Design Challenge
Amazon Music
Software Used
Figma, Adobe Premier
Amazon Music Reimagined
Designing for Emotional Engagement & Retention
Process For The Solution
Conducted primary research with 50+ survey responses and 10 in-depth interviews to uncover retention barriers and emotional engagement gaps:
Affinity mapping session , synthesizing survey responses and interviews into clusters. Four core themes emerged.
What 60 users told us
No control over recommendations. "If I could get recommendations matched my taste, I'd use it way more. Right now, I feel like I'm guessing and getting it wrong."
No feedback or recognition, "I have no idea if the app is even learning from what I skip. There's no signal at all."
Music is not tied to identity. "I want more social features, like the ability to express my emotions and react to songs. Music for me is personal, but I cannot share that."
No reason to return daily "I open Spotify when I want music. I only open Amazon Music when I remember it exists."
We explored 4 directions before commiting to two
Before narrowing in on our final solution, we explored a range of feature concepts, each aimed at addressing a different facet of user retention, emotional engagement and brand loyalty. Here’s a look at the ideas we tested:
Gamified Rewards
Users could earn "Listening Points" for time spent streaming and redeem them for artist merchandise, concert tickets, or VIP perks.
Music Journal
A personal listening log where users could annotate songs with moods and memories, turning passive listening into something that felt like theirs. Think of it as a private music diary built into the app.
Mood Concept
We also looked into syncing with wearable devices like Fitbit to detect mood or activity. The app could then suggest playlists to match physical or emotional statescurating music to suit your energy
Suggestion Mode
Gives users direct control over how Amazon Music generates recommendations, trending, sound-matched, or algorithm-driven. Puts the user in the driver's seat instead of passively accepting whatever comes next.
Why we chose Suggestion Modes and Rewards System
Suggestion Mode
Every interview surfaced distrust of algorithms as their number one frustration. No other streaming platform lets users control how recommendations are generated. This was a genuine white space. And Amazon already has the ML infrastructure to make it real.
What’s Trending – Real-time popularity from the community, for users who trust people over algorithms.
Smart Suggest – Algorithm-driven, but you chose it. That one choice changes everything about how it feels.
Sound Match – Matches what you already love, like tempo, energy, and mood, without you having to explain it.
Rewards & Loyalty System
Amazon's e-commerce ecosystem is sonething Spotify, Apple Music and Youtube cannot replicate. Listening behavior tied to Amazon purchases, points earned through music, redeemed on Amazon, is competitive moat only Amazon can build.
Earn points for time spent, playlist creation, and music discovery
Redeem points for artist merchandise and exclusive drops
Visual dashboard with progress and rewards
Together, these two features formed a product experience that felt personal, rewarding, and distinctly Amazon. They struck the right balance between user value and business advantage.
What We Designed
Suggestion Mode
Rewards & Loyalty
Why this only works at Amazon
Daily Engagement
Premium Subscription
Strengthen Ecosystem
Recommendation Quality
Drives Daily Active Use
The reward habit loop generates a daily return trigger, where users return to earn points, not just because they remember the app exists. This addresses the #1 retention gap we've researched.
Micro Rewards
The points trigger on discovery behaviors: new song, new artist, playlist completion. Each listen is a small win. This encourages and rewards the very same behaviors Amazon wants to see more of: active engagement over passive listening in the background.
🏆 First place. Here's exactly why we won
Amazon Music's executive team selected our submission from 50+ completing teams.
We were the only team to identify algorithm ddisruptionas the root cause of passive listening, not just a symptom of bad UI.
Suggestion Modes was recognized as technically feasible and competitively different.
The Reward System was recognized for uniquely leveraging Amazon's e-commerce infrastructure in a way no competitor could replicate.
Encourages Social Sharing & Virality
Referral rewards encourage users to invite friends. Community challenges create organic social buzz.
High Impact Due to Listening Behavior
46% of users play a single track instead of a playlist, relying heavily on the algorithm for the next song.
A Psychological Effect on Users
Gives users the sense that the algorithm is tailored specifically for them rather than passively accepting its suggestions with no choice.
Increases Retention & Customer Lifetime Value
A tiered system keeps users coming back to maintain their status (e.g., Prime vs. Unlimited).
What I Took Away
The most important decision wasn't visual:
We almost put the Suggestion Mode selector inside Settings. User testing is what caught it; nobody opens settings usually. Moving it into the active listening flow was a single decision that changed everything about how the feature felt. I learned that discoverability of control matters as much as the control itself
Business alignment should be a research question:
We built the business case section after the design was done. That was backwards. Understand Amazon's e-commerce flywheel and Prime tier structure should have shaped our ideation from day one, not been added to the justify design we had already committed to. The Rewards system solution got sharper when we started treating it as business strategy not a feature
What I'd test if this shipped
I'd run an A/B, users who change modes vs. users who don't, tracked on 30-day retention. My hypothesis is that mode changers retain better because they feel ownership. If what I think is true, mode selection should be a prominent onboarding step and not an optional discovery.
Psst! Are you on your phone?
This screen’s a bit too tiny for the full story.
Why can’t I see the full case study?!
Because your phone is too smol.
Why can’t I see the full case study?!
Because your phone is too smol.
👉🏼 Switch to a bigger screen for the real behind-the-scenes of this project full of messy sketches, big ideas, and some aha! moments.
Most Amazon Music users never chose to be there
Many used it simply because it came with Prime, not because they loved it. An emotionally uninvested user cancels music when they cancel Prime. An emotionally invested one upgrades to Unlimited; that's the business gap we were designing into.
What We Built
Suggestion Modes (give users control of the algorithm) + a Rewards System (tie listening to Amazon's e-commerce ecosystem)
Our submission was selected as the winner from 50+ competing teams by Amazon Music's exec team.
Design focus: What would make someone open Amazon Music because they wanted to, not because Spotify was loading slowly?.
Our Team
Sakshi Rane (ME!), Shreya Lohakare, Radhika Balaji, Nabhi Shah - Team 565 Collective
What I specifically owned
All 20 user interviews, where I wrote the discussion guide, recruited participants, moderated every session, and then synthesized findings.
Rewards & Gamification system: owned this end-to-end , rewards dashboard, and final hi-fi prototype
Visual design system, built the component library and visual language used across the design
Final presentation: co-presented to Amazon Music's executive review panel
Most Amazon Music users never chose to be there
Many used it simply because it came with Prime, not because they loved it. An emotionally uninvested user cancels music when they cancel Prime. An emotionally invested one upgrades to Unlimited; that's the business gap we were designing into.
What We Built
Suggestion Modes (give users control of the algorithm) + a Rewards System (tie listening to Amazon's e-commerce ecosystem)
Our submission was selected as the winner from 50+ competing teams by Amazon Music's exec team.
Design focus: What would make someone open Amazon Music because they wanted to, not because Spotify was loading slowly?.
Our Team
Sakshi Rane (ME!), Shreya Lohakare, Radhika Balaji, Nabhi Shah - Team 565 Collective
What I specifically owned
All 20 user interviews, where I wrote the discussion guide, recruited participants, moderated every session, and then synthesized findings.
Rewards & Gamification system: owned this end-to-end , rewards dashboard, and final hi-fi prototype
Visual design system, built the component library and visual language used across the design
Final presentation: co-presented to Amazon Music's executive review panel
Amazon Music
Increasing retention/Strengthening loyalty
🏆 We won!
Out of over 50 competing teams, Amazon Music's executive team selected our submission as the winning solution. Here’s the full story of how we transformed the experience for 60 users who felt indifferent when they opened the app, to introducing two features that encourage them to return.
View Prototype
Title
Amazon Music
Increasing retention/Strengthening loyalty
🏆 We won!
Out of over 50 competing teams, Amazon Music's executive team selected our submission as the winning solution. Here’s the full story of how we transformed the experience for 60 users who felt indifferent when they opened the app, to introducing two features that encourage them to return.
View Complete Project
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