Amazon Music
Empowering avid listeners to actively support and discover their next favorite artists
Overview & Goals:
In February 2023, Amazon Music was looking for a fresh perspective for their customers — they wanted to know, "What is the future of the listener's experience with music and podcasts?". So Amazon Music partnered with The School of Information at Pratt Institute to host a design sprint to find a solution.
I worked with a small cohort to create two new features that could be integrated seamlessly into the existing Amazon Music App, which would grant new opportunities for Amazon Music listeners to discover underground artists, and provide the chance to give back to those artists in a new and exciting way.
Following a review from a board of faculty at the School of Information, our design concepts of Amazon Snippets and Amazon Credits were selected amongst 21 other teams as a finalist to present to Amazon Music's Product team and company.
After presentations and design critiques of our prototype, our team was selected as the overall winner of the challenge. Please feel free to explore our prototype or have a look at our final presentation.
Collaborators:
My Role
• UX Research (user interview, persona, competitive
analysis, research, and user testing)
UX Design (wireframe, hi-fidelity prototype design)
Duration
Feb 3rd - Feb 27th, 2023
Team
Katie Im
John Kellejian
Stacey O'Carroll
Shubhangi Singh
Our Process:
Empathize:
We knew we had to first identify our users: who exactly are they, and what are they looking for in a music streaming service?
We sent out a Google Form as an initial survey to people within our network. Our survey yielded a treasure trove of valuable data, with over 250 responses shedding light on how individuals consume music in the age of streaming. Following this, we narrowed our focus and interviewed volunteer participants to provide additional insights.
Our Problem Statement:
How might we improve Amazon Music so young music listeners can discover new music and see a fair representation of artists?
Ideate:
Feature Design Sprints!:
We held design sprint activities as a team for 30 minutes and grouped back together to vote with sticky notes on features we felt aligned with solving our problem statement.
IA:
Thinking of the Listener & Artists:
We analyzed and designed the information architecture of the Amazon Music app to fit our dual-sided feature of discovery and support.
Feature Breakdown for Snippets:
Below is a comprehensive overview of the functionalities that Snippets offer.
Example User Flow for Snippets:
Below is an example user flow for Snippets involving onboarding, utilizing filters, and discovering artists to give credits to.
Feature Breakdown for Credits:
Below is a comprehensive overview of the functionalities that Credits offer.
Vielen Dank:
I am sincerely grateful to Amazon Music and Pratt Institute for bringing forth this project. And, of course, a massive shout-out to my cohort — thank you all for the support and collaboration throughout this endeavor.
Crafting our Solution
Mid-fi and Hi-fi Prototype of Snippets and Credits:
We developed our porotype using Figma and concentrated on two key flows. The first involved exploring new artists by using the Snippets feature and then using one of the filters (Emotion, Location, or Activity) to find something more curated.
The second flow focused on the user giving Amazon Credits to an artist they wanted to support.
User Demographics & Insights:
What People Said:
Outcomes:
By meticulously analyzing our research findings, we identified three distinct outcomes.
How do Amazon Credits work?
How do Snippets work?
Snippets is a short form music content discovery to make it easier for artists and listeners to connect.
Gathering Insights:
Testing:
To gather feedback on our proposed features, we conducted user testing sessions with a sample of five participants.
