Project Overview

Muse is a mobile application that looks to add a human element to the way people discover new music. By establishing a social music community, sharing and discovering music becomes a more interactive, dynamic and ultimately rewarding experience.

Motivation

Users who enjoy discovering new music have a desire to share their music preferences and discover others’ to form meaningful connections and establish a more robust listening platform. 

1. Research

I conducted a hybrid of several user interviews and a user survey. Some excerpts from the interview responses are shown above. As you may see, my primary focus was to explore how people interact with music and, beyond that, how they share that experience with others. Do they discuss their music tastes with their coworkers? Are they embarrassed to share what their favorite song is? Do they think someone’s taste in music reveals something about their personality?

Above are some key metrics drawn from the survey. The two left-most are an interesting pair: 54% of respondents said they get most of their new music from their streaming service algorithm (think Spotify Discovery Weekly or Apple Music Radio stations). However, 80% of people said that they felt these recommendations were not truly representative of their music tastes. This clearly shows an overlap of people who feel their primary source of new music isn’t actually providing music they like.

The two right-most figures of discussing and connecting via music both point toward a deeply social element of music and the potential it has to bring people together. The bottom line: people want new ways to discover music, and a social forum may be the best way for them to do that.

2. Ideation

I began the Ideation phase by constructing an Affinity Diagram using the responses from the survey and interviews. I collected responses into 7 categories based on trends in user behavior, beginning to identify commonalities in how users' leverage tools today and what they would be looking for in a new solution.

I then constructed a Persona to reflect a possible user for my finished product. This Persona is a social, young professional who enjoys listening to and discovering new music. However, she struggles with her Spotify algorithm and having a reliable way to share songs and playlists with her friends.

The Persona allowed me to think of an actual person when moving throughout the project, acting as a north star to anchor any design decisions I made.

Utilizing both the Affinity Diagram and my User Persona, I conducted several other exercises as part of of the Ideation phase. These included an 'I Like, I Wish, What If?' exercise to identify possible features, a Competitor Analysis to understand pros and cons of similar products, a Storyboard to visualize an actual scenario our Persona might encounter, and finally the Feature Prioritization Matrix shown above to rank functionality ideas.

3. Prototyping

Prior to working in Figma, I began the prototyping process by first mapping out three key workflows in Miro: 
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1. Onboarding
   
   The onboarding workflow, first and foremost, includes a tutorial of Muse including example screens, overlayed text, and tooltips to showcase how to navigate the app.
   
   Second, onboarding includes how to connect your music streaming service account. One of the tenants of Muse is it is streaming service agnostic; you can connect with friends whether you use Spotify, Apple Music, or SoundCloud. This means Muse is not a streaming platform itself, but a social media platform that seamlessly links out to your preferred streaming app. As a result, users would connect their streaming account as part of the onboarding process.
   
   Finally, onboarding asks users to follow an initial group of their favorite artists. Artists can use Muse to post not just their own music, but whatever songs or albums they're currently listening to. Users will be asked to follow some of their favorite artists to establish an initial Home Feed.

   
   

2. Posting A Song
   
   Muse is intended to be primarily a feed of songs posted by users. Creating a post can incorporate a number of different elements, but at its core users would start by selecting a song or album. They can then add some color to their post by adding a caption, a location, or even a photo they want to associate with the song.
   
   Their song and post will then appear on their followers' feed where it can be liked or commented on.

   
   

3. Submitting A Music Request
   
   Users may also submit a request to prompt their followers for music recommendations. They can post something like "Feeling down today, gimme some sad songs" or "What's everyone's favorite Drake song?" and followers can respond directly with a song recommendations. These posts would be more informal and appear at the top of users' feeds (like Instagram stories) so as not to add noise to the main feed.
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Once I had these workflows documented and ensured they flowed logically from screen-to-screen, I moved to Figma to design the low-fidelity prototype. This prototype draft included all the necessary screens and interactions so users could begin actually testing.

4. Testing & Iteration

I conducted initial rounds of user testing with my completed lofi prototype using the three primary workflows mentioned above. I met with 15 to 20 testers (both virtually and in-person) and asked them to complete various high-level tasks. I was careful to not to ask leading questions or indicate where to click to progress through the workflows so the results were as authentic as possible. For example, I used phrasing like "Show me how you would post a song" rather than "Now click on the New Post button at the top of the screen."

Many of the elements users navigated successfully were functionalities they had experienced in other apps, specifically social media features like curating their home feed and making a post. However, some tasks they struggled were activities unique to Muse: submitting a request to their friends for music and integration with their music streaming service. I focused on simplifying the language and flow associated with these workflows in addition to optimizing how they were explained in the onboarding tutorial.

These improvements were incorporated as I transitioned to the hifi design. The hifi design incorporated colors and gradients I had identified in a Mood Board in addition to a high amount of imagery to keep the app focus on songs and albums. Once the hifi prototype was completed, I conducted a second round of user testing to further refine the usability of the app.

5. Results & Takeaways

Given the scope of this app's functionality, there is plenty more work to do. In light of the massive market share existing apps like Instagram and Spotify hold in the social media and music streaming space, respectively, I believe the key to this product's success would be its integration with these apps. As such, my immediate next step would be to spend more time fully testing and optimizing the integration interfaces. Ensuring users fully understand what the integrations do is paramount to Muse's usability.

Beyond this, there are a number of promising features that arose from user research that I would love to explore. One such example in incorporation of live shows and concerts. How might users be able to share a concert they are attending or have attended beyond just posting an Instagram story? How might you find out that a friend is going to the same concert as you and enable you to connect beforehand?

This is just one of the many powerful connections the Muse community might enable.