I went straight for engagement metrics and kind of forgot about the bigger picture for a bit.
Start by clarifying the goal of Discover Weekly: to drive user engagement and retention through personalized music discovery. Then, structure your answer around a metrics framework that covers user acquisition, engagement, retention, and business impact, while also considering counter-metrics and experimentation.
Pro tip: Emphasize that success metrics should be tied to the feature's specific goal and Spotify's overall business objectives, and mention the importance of guardrail metrics to ensure that improvements in one area don't harm another.
Confirm that Discover Weekly aims to help users discover new music they love, thereby increasing engagement and retention. This aligns with Spotify's mission to connect fans with artists.
Identify metrics for each stage: awareness (e.g., % of users who know about Discover Weekly), activation (e.g., % who listen to at least one track), engagement (e.g., number of tracks played, saves, skips), retention (e.g., weekly active users of the feature, impact on overall retention), and business impact (e.g., subscription conversions, ad revenue).
Select a primary metric that best captures the feature's value, such as weekly active users of Discover Weekly or number of saved tracks per user per week, and explain why it's the most representative.
Identify potential negative side effects, such as users skipping too many tracks or reduced listening to other playlists, and propose guardrail metrics to monitor them.
Describe how you would test and measure these metrics, including A/B testing, cohort analysis, and long-term tracking to establish causality and avoid confounding factors.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.