Commercial music streaming services represent the fastest growing sector of the music recording industry, accounting for 32% of all digital revenue in 2014. User studies emerging from the field of Music Information Retrieval (MIR) research are currently being used to guide the strategic development of recommendation systems and new methodologies for the navigation of large music collections. This project serves to test the generalizability of seven user personas, constructed in prior research, and seeks to identify the significance of design implications for various user types. Approximately 1,000 users of music services were surveyed in order to determine behaviors and preferences when interacting with such services. Using a stratified sampling framework, key characteristics were extracted to classify users into specific persona subgroups. Such findings can inform designers of MIR systems and music streaming services in the development of targeted approaches, rather than a universal service model.