Muse: Mood & Music Journaling App
Muse is a reflective music journaling app that lets users track their emotional well-being through personalized playlists, mood logging, and journaling. With mood maps and curated recommendations, Muse helps young adults understand their emotional patterns while enhancing mindfulness through music.
Role: UX Researcher, UX Designer
Duration: 4 months
I set out to explore how people emotionally connect with music in their everyday lives...
36 of 45 survey participants identify between the ages of 18 and 24 years old.
40 of 44 survey participants indicate they listen to music daily.
Target Audience
18–34-year-olds who listen to music daily and care about emotional well-being. This group includes students, young professionals, and creatives interested in mood awareness, journaling, and personal growth.
Key Challenges
Lack of Emotional Context in Music Applications
Traditional music apps often disregard a user's current emotional state, leading to recommendations that don't match their mood and diminish the quality of their listening experience. My research indicated that many users explicitly desire personalized song recommendations based on their mood.
Fragmented Self-Reflection Tools
Current mood tracking and journaling apps often feel detached or lack seamless integration with music, making it hard for users to visualize emotional patterns or reflect deeply on how music influences their feelings. The varying preferences for journaling methods (structured prompts vs. free-text) and frequency of use observed in our survey further underscored the need for a flexible and integrated solution.
Users struggled to understand and express their emotional states.
Survey Data
The survey results indicated that a notable portion of young adults, the ideal audience for the app, do not currently track their mood or do so only occasionally through journaling. This highlighted a gap in engaging, accessible tools for emotional tracking.
Users also expressed a frustration with the "lack of emotional context in music applications" and the "no seamless integration of journaling music", implying that existing music services don't adequately cater to emotional states.
Competitive Analysis
Mood tracking apps like Daylio were noted as potentially "too simple for users wanting deeper journaling" and lacking advanced customization.
Headspace, while strong in mindfulness, had a "subscription model [that] may deter users" and could be too structured.
Spotify Wrapped, while engaging, "only provides a yearly recap—users might want more frequent insights" and has limited personalization beyond data summaries. The user persona, Emily Tran, found existing apps "either too clinical or lacking personalization".
Literary Analysis
My secondary research highlighted that "traditional music recommendation systems often disregard the emotional context, relying predominantly on past listening behavior," which can lead to recommendations that "do not match their current mood".
The research also underscored the importance of "human-centered design in developing mood regulation solutions".
Emily is a college student who turns to music and journaling for emotional clarity and calm. She craves a personalized, intuitive way to track her moods and match them with meaningful soundscapes. This persona highlights her motivations, frustrations, and daily interactions with a Music & Mood Journal app designed to help her feel seen, heard, and grounded.
I built the first flows, visual language, and interactions that allowed users to see and hear themselves more clearly.
These early wireframes outline the core user flow of a mood-based journaling app that pairs emotions with music. From tracking feelings to receiving AI-curated song recommendations, users can log entries through text, voice, or prompts.
“I think it’s really cool! I think you should include more ways to journal, like maybe with stickers, emojis, or even a drawing tool. Also, a backspace or delete option would be super helpful.”
Through feedback and iteration, the app became a space of self-reflection.
Features
Mood Logging with Music Pairing
This core feature enables users to log their daily moods and directly associate them with specific songs or playlists. It's useful because it creates a direct, tangible link between a user's emotional state and their musical choices, facilitating self-awareness and personalized emotional understanding.
Mood Visualizations and Trends
The app generates visual "mood maps" over time, displaying color-coded mood shifts and a "Music-Mood 'aura'". This feature is useful for users to visually track their emotional journey, identify patterns in their moods, and gain clarity on how music influences their mental state, resembling Spotify Wrapped's "Your Audio Aura".
Smart, AI-Powered Music Recommendations
Leveraging AI, the app suggests personalized songs and playlists based on the user's mood trends. This is incredibly useful as it overcomes the limitation of generic recommendations, offering music that genuinely resonates with the user's current emotional state and helping them discover new music that can enhance or influence their feelings.
These high-fidelity prototypes bring the mood and music journal to life with a calming, pastel UI and smooth emotional flow. Muse is designed to help users like Emily reflect, feel seen, and find sonic comfort. Each screen gently guides the user through personalized emotional experiences, making mood tracking not just helpful, but beautiful, intuitive, and deeply personal.
I listened to the user, lessons learned, voices valued, and where the next step begins.
Conclusion
The Music & Mood Journal app is designed to fill a critical gap in personal well-being tools by seamlessly integrating mood tracking with music discovery and reflective journaling. By combining emotional design, user-centered principles, and intelligent recommendations, the app aims to empower users to gain deeper self-awareness, proactively manage their emotional well-being, and discover music that truly enhances their daily emotional landscape.
Insights
Integration is Crucial for a Seamless User Experience
A key learning is that users desire a cohesive and integrated experience across different aspects of their digital lives, especially when dealing with personal data like mood and media consumption.
Emotional Context and Hyper-Personalization Drive Deeper Engagement
The project revealed that traditional music recommendation systems often fall short because they "disregard the emotional context, relying predominantly on past listening behavior".
Visualizing Abstract Data Enhances Self-Awareness and User Engagement
The project learned that interactive mood visualizations, such as color-coded mood maps and "music-mood aura," are highly effective in making abstract emotional data tangible and understandable over time.
Flexibility in Interaction Methods is Essential for User Adoption and Consistency
This flexibility caters to different user preferences and situations, making journaling more convenient and accessible, thus improving adherence to self-reflection practices.
Thoughtful Gamification and Gentle Nudges Foster Habit Formation for Well-being Apps
These gentle prompts, like "It’s been 3 days since your last journal entry. Do you want to check in with a song?", address user pain points around maintaining habits and transform the app into a "stress-free way to check in with your emotions".
Designing for Mental Well-being Requires Sensitivity and a Non-Clinical Approach
The project's target audience, young adults interested in mental well-being, often found existing mood-tracking apps "either too clinical or lacking personalization".