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Music Streaming App UX Research

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  • Project:  Music Streaming App — Foundational Research
  • Role:  UX Researcher
  • Date:  Spring 2025
  • Scope:  Survey (n=17), Competitive Scan, Personas & Empathy Maps
Objective

Understand behaviors, pain points, and switching triggers for music streaming users in order to inform MVP features, pricing direction, and discovery/playlists strategy.

This study began with a 20‑question survey (15 required) distributed via social posts and DMs over two weeks. Responses were synthesized into themes and translated into actionable recommendations for the product team.

View the Survey Research Slides (PDF)
Music research cover zoom
Usage frequency chart zoom
Platforms used chart zoom
Key Questions
  • Who uses streaming apps today and in what contexts?
  • What drives satisfaction with discovery and playlists?
  • What pain points would motivate switching or churn?
Methods
  • 20‑question survey (7 sections), fielded for two weeks via social channels.
  • Light competitive scan of Spotify, Apple Music, Amazon Music, YouTube Music, Pandora.
  • Persona + Empathy Mapping from synthesized patterns.
Participants
  • n = 17 (Texas 14, California 2, Mexico 1)
  • Age: 18–44 skew; 65% female
  • Primarily daily listeners on mobile (88%)
Top Insights
  • Discovery & Playlists: Users lean on app‑curated playlists; only ~30% frequently create their own. Improve recommendations and themed mixes.
  • Interruptions & Access: Ads and unreliable offline access are the biggest breakpoints—especially when commuting, at work, and at the gym.
  • Switching Triggers: Lower price (47%) and uninterrupted access (29%) dominate; consider tiered pricing and strong offline.
  • Devices & Contexts: Mobile‑first, car & gym primary contexts → prioritize hands‑free controls and downloaded playback.
Opportunities
  • AI‑assisted "Sounds like…" recommendations; DJ‑style curated sets.
  • Built‑in music recognition (beyond Shazam parity) to capture “what’s playing” → add to playlist.
  • Playlist UX: clearer controls (repeat/skip), visible track length, easy artist‑only mode.
  • Optional social layer (opt‑in) to follow friends/creators without adding friction.
Persona: Oscar (41) — Tech‑savvy DJ & Engineer

Time‑constrained, values efficient access by mood/activity. Uses music to focus and unwind. Seeks automation and low decision‑fatigue.

  • Needs: quick mood presets, daily auto‑mixes, repeat/artist‑only modes.
  • Pain: interruptions, weak offline, repetitive recommendations.
  • Opportunity: DJ‑style curated sets; ambient/focus tracks surfaced contextually.
Persona: Mia (19) — Culinary Student on the Go

Busy schedule balancing school/work. Music for energy and culture. Wants guidance and easy organization.

  • Needs: hands‑free controls, downloaded playlists, genre discovery by region.
  • Pain: time pressure, hard to find artists, ads breaking flow.
  • Opportunity: creator‑curated lists, "window" (muted) ads that don’t pause playback.
Impact

These findings shaped the MVP focus on: offline reliability, recommendation quality, and a simple tiered plan. The result is a research‑backed roadmap centered on real‑world contexts (commute/work/gym) and low‑effort discovery.

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