Solving retention for Amazon Music, making it more personal and more rewarding.
Solving retention for Amazon Music, making it more personal and more rewarding.
Solving retention for Amazon Music, making it more personal and more rewarding.
Overview
Amazon Music Product Design Challenge
In 2025, the team, 565 Collective, including me, Radhika Balaji, Sakshi Rane, and Shreya Lohakare, reimagined Amazon Music to tackle the critical issue of user retention across its tiers. Our approach provided a more personalised and rewarding experience for music fans, motivating them to remain on Amazon Music. The solution was highly praised by Amazon Music stakeholders and won the Best Design Thinking Award for the challenge.
What difference did we make?
Empowering Amazon Music & the Fans
60%
Users expressed that the feature would positively transform their music listening experience.
100%
Of the key stakeholders from the Amazon Music design team expressed interest in the feature.
#Best
Team earned the Best Design Thinking Award, securing us as one of the challenge winners.
The Problem to Solve
What Prompted us to Re-Imagine
Amazon Music?
What Prompted us to Re-Imagine the Industry?
Amazon Music was experiencing a significant decline in user retention across its Amazon Music Unlimited tiers and was seeking to identify the reasons behind this issue and find effective solutions.
Understanding What Drives Retention
User retention is typically influenced by two factors: competition that draws users away, leading to decreased retention, and innovation within the product that provides compelling value, making it difficult for users to leave, thereby improving retention.
Competition
There is some crucial quality competition has that Amazon lacks, causing users to return back.
Innovation
Amazon Music needs something that would make it impossible for users to leave.
The Process
Bending the Laws
Amazon follows the double-diamond process for design, and all teams were expected to do the same. However, to gain more time and achieve better results, we adapted the process slightly. Instead of strictly separating research and ideation, we conducted them in parallel and only retained ideas that aligned with our research findings. This approach led to the development of four well-defined ideas in the ideation phase, each with a comprehensive implementation plan.
User Research
Unlike other teams that concentrated on gathering quant. data for a statistical approach, we embraced a different path by exploring what music and music streaming services truly mean to users. Since Amazon Music refers to its users as fans, we allowed the fans to share their voices and prioritised empathy—focusing not on numbers but on emotions and understanding.
Ideation
After thorough research, we identified two main clusters based on the responses to our questions. One cluster centered around the desire to have control over the algorithm or concerns about it not working as intended. The other cluster focused on people’s emotional connection to the music culture that Spotify has cultivated.
We identified three solutions from the bank that resonated well with the research; all focused on addressing emotional connection. However, none tackled the desire for greater control over the algorithm. To bridge this gap, we ideated Suggestion Modes, giving fans the ability to influence the algorithm.
Still, we were uncertain which of our four solutions would be the most effective in improving retention. To determine this, we designed a specialised filter that considered all three essential aspects of Amazon Music—the users, the business, and the technology.
Rewards & Loyalty emerged as a standout idea by offering users the ability to earn rewards through their music engagement and spend them on experiences that embody music culture - such as concerts, merchandise, early access, and more. This feature promoted a deep emotional connection by directly linking music listening to the broader culture. Meanwhile, Suggestion Modes excelled due to its alignment with people's expectations and being a technological innovation.
Both concepts addressed critical aspects of retention. Rewards & Loyalty aims to make switching back to Spotify unnecessary by providing a richer connection between music streaming and culture. On the other hand, Suggestion Modes creates a level of customization that makes it difficult for users to find a comparable experience elsewhere.
Therefore, tackling retention required a combination of both solutions, as relying on just one was not enough. However, Rewards & Loyalty follows a very different approach - rooted in psychological principles of gamification, while Suggestion Modes leverage design to shape technology in the users’ favor. I have addressed Suggestion Modes here; to explore our approach to the Rewards System, go here.
Introducing Suggestion Modes
Suggestion Modes emerged from extensive research into how music recommendation algorithms function. By analyzing the key factors that influence music recommendations across various apps, we found a way for users to take control. The three simple modes allow users to disable certain algorithmic factors, resulting in more relevant suggestions based on the remaining factors.
MUSIC ALGORITHM 101
The music recommendation algorithm uses two filtering methods: collaborative filtering, which suggests tracks based on the listening habits of users with similar tastes, and content-based filtering, which focuses on similarities in sound characteristics like genre, style, instruments, and composition.
The suggestion modes allow users to toggle off one factor, providing music recommendations based on just one criterion. There are three modes: “Smart Suggest,” which incorporates both factors; “What’s Trending,” which uses collaborative filtering only; and “Sound Match,” which relies solely on content-based filtering.
The Key to Effective Implementation
To design the feature, we applied the JTBD framework to pinpoint potential challenges that could hinder user acceptance. We also adhered to relevant design principles to address these issues, ensuring the solution is not only efficient but also effective in its implementation.
Clear Communication
Addressing Touchpoints
We pinpointed key touchpoints for the feature by understanding how users prefer to engage with it. After introducing the feature via the app-wide settings, we discovered that a more intuitive touchpoint was the upcoming song list section while playing music.
Encouraging Discoverability
The feature’s touchpoints, including the app-wide settings access button and the prompt that appears when a user dislikes a suggestion, are highlighted using a subtle color-based micro-interaction to enhance discoverability without being disruptive.
Priming to Other Features
During the interviews, we discovered the strong potential of the feature to create personalized playlists by considering key factors like trends in similar genres and styles. This, in turn, improved the playlist-making experience, leading us to offer subtle priming to the playlist-making process.
Why it Works
Solution's Impact
High Impact
46% of users choose to play a single track instead of starting a playlist, making them highly dependent on the algorithm for their next song recommendation.
A Psychological Effect
Gives users the sense that the algorithm is tailored specifically for them rather than passively accepting its suggestions with no choice.
Hard to switch
Dissatisfaction with algorithm is a common concern. It will become hard for users to switch to other apps that don’t have the same personalization.
Results
Making Moves
#1
The solution was recognized as the top feature for its application of design thinking and its effectiveness in improving user retention.
The solution, along with the rewards system, was recognized as the winner of the Amazon Music Product Design Challenge for its design thinking and effectiveness in addressing user retention for Amazon Music.
Innovating Experience
Innovating Experience
Creating empathetic designs, swiftly enhancing business solutions, and transforming lives for diverse individuals, in other words, innovating experiences.
Creating empathetic designs, swiftly enhancing business solutions, and transforming lives for diverse individuals, in other words, innovating experiences.
Innovating Experience
Creating empathetic designs, swiftly enhancing business solutions, and transforming lives for diverse individuals, in other words, innovating experiences.