Amazon Music Design Challenge: Rhythmic Focus

Leverage AI to elevate the Amazon Music, creating a tailored and efficient listening experience that helps users stay on track and motivated.

Type

2024 Amazon Music Product Design Challenge (APP Design)

Host

Amazon Music & Pratt Institute

Duration

1 month (2024)

My Role

Design Lead
UX Design
UX Research
User Interview

Tool

Figma

Team

2 Designers

Overview

Challenge Prompt

Given the current state of Amazon Music, how might AI enhance a customer’s experience with music and /or podcasts?

Our Goal

We explore the needs of staying productive and focused during work and study sessions while listening to music and our business impact ensures Continuity, fostering deeper and more frequent engagement with Amazon Music among users!

Outcome

Top 3 Finalists
Our team won the 2024 Amazon Product Design Challenge as Top 3 Finalists out of over 20 teams, earning the "Most Implementation-Ready" award.
Pitch to Amazon Team
We delivered a pitch of our final design to over 150 Amazon representatives, including the VP of Design and Creative and received positive feedbacks from them!

“The research and experience are an in-depth exploration of all facets of the experience, including the ‘processing arrow’ and allowing access to screen time, etc. The visual language is simple, but strong — especially the use of color. The story is clearly told and the research cleanly presented.”

Final Design

Rhythmic Focus: Utilize AI-generated focus playlists and statistics, along with the Pomodoro technique to aid focus and productivity.
↓Scroll down to view the project in detail.

Let’s take a few steps back to where it starts...

Quick Statistics from 107 Respondents

We conducted surveys as our first step and document our findings from young adults who are mostly laborers or students.
97 %
Use music streaming platforms several times a week
76 %
Work or study with using music streaming services
39 %
Actively choose what to listen to by browsing genres or categories

We quickly realized that...
‍Nearly 80% of them listen to music while working or studying, which indicates that people need music as companion when focusing on their tasks.

Next, we looked for more inspiration through interviews

These interviews Bring many Inspiring insights about their needs

“Having music playing in the background makes tasks more enjoyable, but I struggle to maintain focus on the tasks after a while.”
“If my focus is low and I struggle to stay engaged, I need something fast and upbeat like 90s/00s funk, rnb.”
“Music-related content from music-streaming platform gives common topics and connections between me and friends”

Our research provided us with 3 key insights:
1. Struggles with Sustained Focus
2. Diverse Music is Satisfying  
3. Desire for Connection

...That's how we honed into our project emphasis on productivity and continuity. 🔍

HMW

How might we leverage AI to enhance users' productivity and focus while listening to music?

Then, we started to utilize the findings to ideate!

Our first Attempt...

We explored ways to enhance focus and productivity, such as the Collaborative productivity Playlist. This idea involved creating a shared playlist with friends and using AI to recommend focus-enhancing music based on individual usage patterns.

However...
We did not proceed with this idea. Our concern was that it could be distracting rather than enhancing focus. Creating such playlists might consume too much time, conflicting with our goal of promoting deep focus.

Here comes our Second Try...

We came up with the idea of combining Pomodoro Technique with diverse music-listening options in Amazon Music when we went through again our research findings and thought this could best meet our users' needs.
For those who might don’t know what the Pomodoro Technique is: It is a time management technique by breaking work into intervals, typically 25 minutes in length, followed by short breaks.

We also made a quick competitor analysis to examine how similar products work

annotated screenshots to identify unique Design and Features

We took a throughly look at existing Pomodoro apps and explored specifically on the part that how do they integrate with music.

Key Finding:
‍‍While many incorporate music, we observed a lack of diverse options. Most offer only white noise and ambient sounds, which contrasts with our user research indicating a desire for diverse music choices.

What is our opportunity?

diverse music options with dedicated focus modes

The opportunity lies in blending diverse music options with dedicated focus modes. We decided to ideate features based on Pomodoro techniques and made sure them could integrate into the current ecosystem of Amazon Music App.

User Flow & Rapid Wireframing

Crafting our Design solutions

Our core features include : The focus time setting function / Choose music preferences / AI-based Personalized playlist / Pomodoro countdown clock / personalized data.
→ Go to Figma to see the 1st version prototype

We came up with a usability test plan to evaluate the design

User testings with 7 potential users

Scroll down to check what we have changed after user testing ✅✨

Key iterations we have made after the testings

#1 more Intuitive Option Sequence

✅ When building playlist with AI... Place Energy options before Genre options

#2 Reduce User Confusion

✅ On the Ready Page... Add playlist preview to highlight the connection between music and focus mode

#3 Align with Core Feature Concept

✅ After successfully completing a focus session... Display focus-related statistics rather than general listening habits

We applied these improvements to the next iteration

Refined the Final Design

We put a lot of effort on building our final prototype, making sure the overall visual style and design perfectly align with current Amazon Music app so that viewers and judge can understand our concepts more easily via high-fidelity prototype.
→ Go see final prototype!
Some transition/loading UI made by me ✌️

Final Design

Achieving Continuity in Music Streaming with AI and Pomodoro Collaboration

Let’s go deeper in detail.✨

01. Set Your Pomodoro Goal

Introduce your ultimate productivity partner!
Open up Rhythmic Focus on Amazon Music App, then get started, set your focus and break times and rounds for concentration.

02. Engaged More With Deep Focus Mode

Next, users could choose deep focus mode for a more extreme focusing time. But Also, users can go for "General Focus" mode, where they can still use other apps while focusing.

03. AI-Powered Personalized Focus Playlist

Moving on to build the Playlist accompanying your focus time. With AI-generated feature, choose the task type, energy level, sound, beat, and genre, you could experience how effortlessly you can to have playlists fit your specific needs.

04. Get Focused With Music!

Coming to the ready page, you could either start with your own or ask friends to join by sending invitation to them. Enjoy Rhythmic Focus with friends allows you see each others status and who is with you until the last second. For the countdown screen during Rhythmic mode, we aimed to make it clear and simple, prevent distraction, just like UI of car mode.

05. How Focused You Are?

If you succeed completing the focus time, unveiling the interesting statistics generated by the AI based on your history of using Rhythmic Focus Mode. Learn How Focus You Are With Music!

Learnings

Throughout this journey, I've been inspired to push the boundaries of incorporating AI into our designs while prioritizing user needs, particularly focusing on enhancing customer engagement with the product/platform.

My Biggest Takeaways:
Designing Within Bounds: Our ideas must align with Amazon Music's ecosystem, ensuring it is feasible and grounded in Amazon Music’s current state.
Consistency Matters: It is important to follow Amazon Music's design patterns to
ensure consistency across the platform.

If we had more time...

Illustrate more on different task type, such as workout scenario where users can connect Amazon Music to their smartwatch. For instance, The smartwatch tracks heart rate and calories burned during the workout Pomodoro sessions, providing users with statistics showing calorie burn rates based on different types of songs.

Next

Orca HCM