Predicting Listening Preferences

Increasing ease of discovering new content and curating a personalized listening experience,
playing what you want when you want

NOTE: A Non-Disclosure Agreement prevents me from discussing some of the finer details about this project

Bose was looking to expand its footprint into the music management and content provider space and was exploring what an application of this direction could look like and how it could differentiate itself from other existing products in the marketplace. I was brought on to assist in a series of design sprints, create speculative designs, and conduct user testing on app prototypes. The app was intended to aggregate listening services into a single, coalesced space. It would include various types of multimedia and would curate playlists or audio choices based on machine learning about users’ lifestyles.

I joined a small internal Bose team that had been assigned to work on the project as a design leader and external voice. We ran a series of sessions following The Design Sprint methodology created at Google Ventures, with each weeklong session tackling a different problem we had hypothesized in our initial discussions. After the conceptual work had been done and we had tested out various aspects of a potential platform, I designed a working prototype that aggregated all of the ideas into a unified product. We ran a series of user tests with this unified product, iterating on the feedback after each series of tests. This process continued through the duration of the project resulting in a complete speculative app which was taken back internally to be used for future internal research and design concepts.



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User Research, UX Design, Wireframing, Prototyping

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