MOODIFY
Mobile Application | Music For Every Moment
PROJECT DETAILS
Challenge: Create a music recommendation experience based on a user's mood
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Solution: Develop an ontology and design a user interface for the application
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Role: Ideation, Research, Prototype, Wireframe, Logo Design
TOOLS
Overview
Moodify is a new startup that provides a service for music recommendation via the combination of moods/feelings and tempo. The reasoning behind creating this application is to provide a service that can be used as an actual music player and have the right music for the right moment.
Moodify aims to use Spotify’s APIs to create a mobile application that uses a user’s Spotify account, combined with research and Spotify’s knowledge base, to suggest songs to either create or maintain a certain mood, like happiness or anger.
PROJECT GOALS
1. Become the go-to music application
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2. Improve the usage of Spotify
Project Design
Moodify is a solution to a better music recommendation application that is available to users. It is created to enhance the usability of Spotify and to get users to create playlists catered to their tastes and moods. In order to create an application that any person can use, the decision was to emulate a user interface that everyone is used to.
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The color palette is black and blue because it was easier on the eyes and have a neutral connotation to it. It would also look similar to Spotify to indicate that this application relies on Spotify to work. Moodify’s goal is not to take users from Spotify, but simply to enhance the usability. Similar to TweetLonger to Twitter, Moodify is an extension to Spotify.
Low Fidelity Wireframes
By creating low fidelity wireframes first, any problems with the design elements can be seen easily and worked out, like if an element was needed or if a certain element was in the most intuitive location. It also made prototyping a lot easier and quicker. The wireframes helped with communication between team members as to what would be functional, feasible, and still address the users' needs.
research methods
1. Customer Interviews
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2. Persona
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3. Competitive Analysis
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4. Information Architecture
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5. Prototype Testing
The target audience, or the main users, will be anyone with a Spotify premium account who is openminded about music and craves to find new music to jam out to at the perfect moment. The first group of users to be targeted would be anyone from 16 to 28 because they will be the trendsetters and have the means to spread the word about the application.
1. Customer Interviews
I know Spotify has premade playlists for certain moods, but I want to be able to create a playlist specifically for me.”
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I want the ability to create the perfect playlist depending on how I’m feeling. I’m a very emotional kind of person, and I don’t think there’s anything right now that speaks to me.”
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2. Persona
4. Information Architecture
3. Competitive Analysis
5. Prototype Testing
During the first round of protypes, lots of comments about the typeface being very plain and simple and how it’s a little hard to read the menu near the bottom of the screen were given. This version of Moodify did not appeal to some people because some people wanted to see the album cover, see their friends’ playlists, and it wasn’t “exciting” enough.
The interface is cleaned up a bit by condensing the menu icons on the button in a group of its own, the song player is rounded off to emulate the similar curves in the rest of the screens, and fixing the informational hierarchy by utilizing type size and color. To create more visual interest, as well as information, album covers were added next to the song title.
visual design
To pay homage to Spotify, this application will have a similar style and feel. Replacing the bright green with softer shades of blue to remain a neutral vibe and letting the music and feeling shine.
teammates
The team consisted of a dedicated developer, a flex developer who also worked on researching the rule set and Spotify APIs, and a designer(me). It was our first time using Protégé, Spotify APIs and software we used, we had issues with many of them. After learning that the API did not offer the functionality we needed, we found a new wrapper to use that was robust, well modeled, and well documented. However, after some research, we then also found that it was incompatible with Android systems, so we had to again choose another wrapper. Our ambitious goal was to create a mobile application that would work on both Android and iOS devices, but that quickly became impossible due to the timeframe and the lack of manpower.
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My role in this team was to design the interface for our application. As my teammates worked on the back-end development, I decided it would be optimal to work in an agile project management to incorporate user feedback on the ease of use and functionality.
reflections
It's okay to scope down.
We scoped down our project when we realized that our original idea had elements that were not necessary for the AI. In the beginning, we were planning to create an Android app with a music player in it. Due to time constraints, we decided on having the application output a recommended playlist in Spotify instead. We removed a lot of the overhead of what an actual music app has, such as logging in, music player, and anything that relates to looking into a specific song, artist, or album. As a result of removing the overhead of making an actual music application, my designs for an actual music application were not used in the end, but I'm glad I had the opportunity to work on my research and design skills.
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If we decide to work more on this project, I want to conduct more rounds of user testing to indicate what features worked or didn't work. I would also want to see our application come into fruition as we originally envisioned.
