What API and data model would support a new Music workflow for commuters at global scale

Problem Statement Description

Product context: Spotify is an audio streaming company; its products include music, podcasts, audiobooks, playlists, recommendations, creator tools, subscriptions, and ads.

Spotify is exploring a new music experience designed specifically for commuters who listen during predictable, time-constrained journeys across global markets. The workflow may need to support moments such as starting a commute, resuming listening across devices, adapting to trip duration, handling poor connectivity, blending music with other audio formats, and preserving personalization without creating extra user effort.

Your task is to define the API and data model that would enable this commuter-focused music workflow at global scale. Assume the product must work across mobile, car, wearable, voice, and connected-device contexts, while supporting Spotify’s personalization, discovery, retention, monetization, and creator ecosystem goals.

This is a Technical PM design question, so focus on translating the user experience into technical requirements, platform contracts, data entities, system behaviors, and trade-offs. You are not expected to write production code, but you should be precise enough that engineering, data science, design, and privacy teams could evaluate feasibility and implementation risk.

The experience should consider:

- Core commuter user journeys, including session start, continuation, interruption, offline/low-connectivity use, and completion.

- API requirements for client apps, playback systems, personalization services, recommendations, ads, and analytics.

- Data model entities such as commute context, listening session, user preferences, content eligibility, device state, and playback history.

- Reliability, latency, caching, offline behavior, and graceful degradation across regions and network conditions.

- Privacy, consent, location sensitivity, data minimization, and user control over commute-related signals.

- Globalization needs, including market-specific content rights, language, transportation patterns, device mix, and monetization models.

- Observability, experimentation, event instrumentation, debugging, and success measurement for the workflow.

- Product and technical trade-offs between personalization depth, implementation complexity, user trust, and platform scalability.

The goal is to present a clear technical product proposal for the APIs and data model needed to power this commuter music workflow, including the key requirements, boundaries, risks, and rollout considerations that would allow Spotify to build and scale the experience responsibly.