
Muse App
UX/UI Design, 2022Objective
Define challenges and patterns affecting consumers when choosing from a dense list of concerts / music events with several modes of characterization. Understand and fill the gap between two primary contrasting user types.
Application
A mobile app experience connecting users to music events bridged by user customization and external social connection, creating a personalized expereinces for both the music connoisseur and the casual fan.
Task flow
Discover page
Discover page

Task flow
“Near me” ︎︎︎ Genre preferences
“Near me” ︎︎︎ Genre preferences

Task flow
“Near me” ︎︎︎ Show details
“Near me” ︎︎︎ Show details

Task flow
Onboarding
Onboarding

Personas / Opportunities
With a general idea of the issue at hand, I wanted to get a better idea of how it would impact two very diferent use cases:
1. Someone with a more curated and specific list of shows they would see, or within a specific genre-- someone who is going to shows for the music
2. For a user with a less rigid set of preferred genres, and open to different types of events, more inclined to go to shows for the environment / social aspect
With a general idea of the issue at hand, I wanted to get a better idea of how it would impact two very diferent use cases:
1. Someone with a more curated and specific list of shows they would see, or within a specific genre-- someone who is going to shows for the music
2. For a user with a less rigid set of preferred genres, and open to different types of events, more inclined to go to shows for the environment / social aspect


Bridging the user types

Data mapping
In order to understand how the needs and restrictions of both users could be adhered to, I mapped out how data from user engagement could be utilized. This map allowed visibility into a flow of data that would allow for the needs of both of these users to be met, where users could diverge from their own preferred genres by opting to search for a show, and these search patterns and other engagment behavior would be used to inform an algorithmic refresh of the user’s preferences.
In order to understand how the needs and restrictions of both users could be adhered to, I mapped out how data from user engagement could be utilized. This map allowed visibility into a flow of data that would allow for the needs of both of these users to be met, where users could diverge from their own preferred genres by opting to search for a show, and these search patterns and other engagment behavior would be used to inform an algorithmic refresh of the user’s preferences.

Info architecture

Wireframes




Style
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Final screens
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