TWEEDL Music
Hear, Dope, ShareMusic Popularity Engine
Overview
TWEEDL needed an iOS/Android music app developed to help artists better understand and engage with their audience..
Problem / Opportunity
Although there are more channels than ever that allow music artists to broadcast their music, there was nothing laser focused on providing artists direct feedback on whether or not their music was resonating with their target audience in a way that was easy for listeners and granular for artists.

Goals
User
Provide a quick and easy way to browse music and give fast, prominent feedback (Nah, Dope or non-vote) on whether they thought a song was successful or not.
Customer
Get audience feedback for artists as soon as possible on a per track basis (as opposed to followers), gain actionable insight on their audience preferences and grow that audience.
Business
Provide a platform for the music industry as a whole to truly understand and predict what music will be successful.

Process
A basic hi-fi click thru prototype had been researched, created and validated with representative users. We used a combination of iterative IA work, interaction design, detailed prototyping, focus group and internal and external stakeholder feedback to shape a Minimum Viable Product to test as soon as possible in the marketplace.

Solution
We created a React Native app for iOS/Android as well as a dedicated website for Artists to upload their work and leverage it in the mobile app. This allowed users to quickly browse tracks from new and established artists in 30 second “chunks” or listen in a more typical “Leanback” mode. As they listened they were asked to vote Nah, Dope or simply pass on voting on tracks. If they Doped a song, they were encouraged to promote the song on social media and directly to their friends.

Results
Instead of trying to infer if their audience likes a song via mixture of metrics such as the number of listens, length of listen, subscriptions/follows, secondary likes or dislikes, artists were given direct and almost immediate feedback on specific songs as well as growing their fanbase via as much sharing as possible. This also helps the business determine which kind of music is trending within an audience via their focused feedback.

Personal Contribution
I worked closely with the clients and our creative agency team to shape Provisional Personas, Information Architecture task flows, content inventories, low and high fidelity wireframes, click thru mockups and interactive prototypes as well as visual design.

Gallery
- Provisional Personas
- Personas
- UX Dialogues
- Analysis of Voting Approach
- Doping IA
- User Journey / Touchpoints
- IA Structure
- Overall Project Structure
- Expanded IA
- Content Label Inventory
- Task Flows for Discovery
- Task Flows for Artist Registration
- Task Flows
- Basic Layout Wireframes
- Section Wireframes
- Possible Variations on Components
- General Wireframes
- Web based Music Upload Wireframes
- Uploading Button States
- Visual Style Tile Collages
- Style Tiles Reference
- Click thru Hifi Voting States
- Hifi Visual Click Thrus
- Hifi Visual Click Thrus
- App Screenshot of Browsing
- App Screenshot of Player
- App Screenshot Voting Choice
- App Screenshot Voting Summary
- App Screenshot Sharing
- App Screenshot Voting Summary in Discovery mode
- App Screenshot Voting in Discovery mode
- App Screenshot user Profile
- App Screenshot Browsing
- App Screenshot Becoming an Artist
- App Screenshot browsing by Genre
- Problematic Sharing Flow Brainstorming
- Buffer like Instagram Sharing Solution
- Problematic Original Mockup of Trending Feed
- Trending Sketch Layout Analysis
- Trending category layout reference
- Trending category layout reference
- Trending category layout reference
- Trending category layout Analysis