Build a metric tree for Podcasts after a major redesign

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 has completed a major redesign of its Podcasts experience for podcast fans. The redesign may affect how listeners discover shows and episodes, evaluate recommendations, start playback, follow shows, continue listening, and return to podcast content over time. You are asked to define a metric tree that helps Spotify understand whether the redesign is improving the podcast experience and supporting the broader audio business.

Focus on the listener-side product experience, while recognizing that podcast success also connects to creators, recommendations, ads, retention, and monetization. The metric tree should make clear how top-level podcast success breaks down into measurable drivers and diagnostic sub-metrics, rather than listing isolated KPIs.

Your answer should be framed for a post-redesign evaluation: product leaders need to know if the redesign is working, where performance is improving or degrading, and what trade-offs may be emerging across discovery, engagement, satisfaction, and business outcomes.

The experience should consider:

- A clear primary success metric for Spotify Podcasts and why it is useful after a redesign.

- The denominator and population for each metric, such as podcast listeners, Spotify active users, new podcast users, or returning podcast fans.

- How the tree separates discovery, conversion to listening, consumption depth, retention, and monetization signals.

- Instrumentation needs across surfaces such as Home, Search, podcast show pages, episode pages, recommendations, library, and playback.

- Cohorts that may behave differently, including new vs. existing podcast listeners, heavy vs. casual listeners, markets, platforms, and content categories.

- Guardrail metrics for negative side effects, such as music engagement cannibalization, playback quality issues, ad load impact, creator outcomes, or user dissatisfaction.

- How the metric tree would help diagnose whether a change is caused by the redesign itself versus seasonality, content launches, marketing, or recommendation changes.

The goal is to construct a structured, decision-useful metric tree that Spotify could use to evaluate the health and impact of the redesigned Podcasts experience, identify where user workflow friction remains, and guide follow-up product decisions without jumping directly to solutions.