Feeling All the Feels: New Emotional Features
MY ROLE
UX/UI design
Persona, Information Architecture & User Flow, Wireframes, Visual Components, Lo-fi prototypes & Hi-fi prototypes, Mobile & Desktop Versions, Iteraction Design
‍
UX research
Competitive Research, Survey, Interview, Affinity Diagram, Data Analytics
OVERVIEW
Amazon music aims to create a near future music service for world-wide users. Our team target to Gen-Z listeners, developed a series of experience design mainly provide users with emotional features: emotion detection, recommended playlists based on users' emotion, and world & personal emotion tracking.
TEAM
4 UX Designers
COMPANY
Amazon Music
TOOLS
Figma, Google Forms, Miro
DURATION
2 months, February - March 2023

CHALLENGE

How do we reimagine the future of music for Gen Z listeners?

Our team of four designers was tasked with the challenge of designing future experiences for Amazon Music, focusing on music and podcasts. We looked 3-5 years ahead to develop a concept that leverages Amazon Music's offerings and reach, bridging digital, communal, and individual experiences through the use of new devices and emerging technologies.

SOLUTION

Create features that resonate with users globally, addressing their daily emotional needs

1.
Emotion detection based on facial expression and heart rate
AI detects users' moods by analyzing their facial expressions and heartbeats. An emoji reflecting the detected mood will appear on the loading page, accompanied by a message that complements that mood.
2.
AI-generated playlist based on user mood and environmental data
Users can set their emotional and environmental preferences, and the playlist will automatically update to align with their current mood and surroundings.
3.
AI-generated playlist updated based on your preferences
Users can click the "This got me" button to let the system know if a song matches their current mood. This feedback helps the AI refine future song recommendations, ensuring a more personalized experience.
4.
Global and personal emotion trends for connection and record-keeping
‍Users can explore their own emotional trends alongside the average emotional trends of different countries.

Button colors represent the predominant emotions in each country on that day. The chart displays daily emotion trends and highlights the top 5 songs for the selected day.

🎧
What Do Users' Music Habits Look Like?

DISCOVER

Users' emotions are highly affected by music

To gain insights into users' thoughts and music listening habits, we designed a survey and conducted interviews. Our survey received 57 responses, and we interviewed 8 participants.

The results revealed that users' emotions are strongly influenced by music and are particularly affected by close relationships, weather, and social life. We also identified common music-listening habits, such as frequent listening during commutes and while working.
When do users use music streaming services?
In what mood would users more likely to use music streaming services?
What functions do users use the most?
What reasons would affect users mood?
To what extent do users think that music affects their emotion?
How long do users listen to music a day?

💬
What Did Users Say About Their Music Experience?

OUR AUDIENCE

Active Gen-Z Listeners

Gen Z, currently aged 11-26, grew up in the digital age. According to the GWI Global Internet Usage Report, they are particularly active listeners, spending an average of 2 hours a day listening to music.

Key characteristics of Gen Z include:
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1. Desire to Connect with People Worldwide
Social media offers them the ideal platform to share their thoughts, ideas, and creativity with friends and a global audience.
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2. Interest in Discovering New Songs
Gen Z relies on algorithm-driven playlists and personalized recommendations from streaming platforms to discover new music that fits their taste, fueling their daily lives.

PAINPOINTS

Music discovery lacks an intuitive approach

From our user interviews, we discovered that song recommendations don’t always align with users' tastes, which can disrupt their listening experience when an unsuitable track plays. Additionally, users often struggle to remember the names of songs they've previously enjoyed but can more easily recall the mood they were in while listening.
Recommended songs do not align with user's taste
“ Sometimes the recommendations match my music taste, but sometimes they don't. ”
Recommended songs don’t always fit the type of music users are seeking. For example, a Swiftie looking for energetic tracks might be disappointed if hip-hop songs unexpectedly appear in their playlist.
Difficulty recalling songs associated with specific moods
“ I forgot the song's name; I just remember that I listened to it on a sad day. ”
Users might remember feeling sad last week but forget the exact date, making it challenging to find the sad music they discovered that day.

💫
How Can We Create a Better Experience for Users?

IDEATION

We developed four features based on two key themes

1. Emotional & Environmental Detection
•  How might we give users more control over recommended content?
•  How might we detect users’ emotions and environments to deliver songs that match their current situations?
2. Personal & Global Emotion Records
•  How might we reflect users’ personal emotional journeys?
•  How might we connect music lovers worldwide?
Main Features
Emotion Detection Based on Facial Expressions and Heartbeat
AI-generated Playlists Based on User Mood and Environmental Data
Real-Time Mood Tracking to Optimize Song Recommendations
Global and Personal Emotion Trend Pages for Users

FINAL DESIGN

AI-generated Playlist

FEATURES
Create personalized playlists by combining user emotions, current weather, and time. As users adjust their emotional and environmental preferences, the playlist automatically updates to match their mood and surroundings.

Optimize Song Recommendations

FEATURES
Users can click the "This Got Me" button to indicate if a song matches their mood.
This feature allows the system to immediately adjust song recommendations based on user feedback, improving the accuracy and relevance of the playlist.

World Emotion Trend

FEATURES
A page for users to explore emotion trends across different countries or globally. Buttons in various colors represent the predominant emotions in each country for the day. Each country’s page features a chart showing daily emotion trends and lists the top 5 songs for specific day.

Personal Emotion Trend

FEATURES
A page dedicated to tracking users’ emotional trends and song history. Users can scroll through the chart to select and view specific dates.

REFLECT

Next Steps
Conduct Usability Test
Due to time constraints in this design sprint, we have not yet conducted usability testing. Our next step is to carry out unmoderated and/or moderated user tests to evaluate our product. We plan to recruit Gen Z users who consider music an integral part of their lives.
© 2024 Liang-Yu Su. All Rights Reserved