Investigate why conversion fell after a Audiobooks launch 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 has launched Audiobooks globally, adding a new content and monetization surface alongside music, podcasts, ads, and creator tools. Shortly after launch, the team observes a meaningful drop in conversion. For this case, treat “conversion” as the key business action tied to Audiobooks, such as users moving from discovery to purchase, trial, paid access, or completion of a checkout flow.

You are the PM asked to investigate the decline. The issue may involve listener behavior, creator/catalog supply, pricing or entitlement confusion, payments, recommendations, launch sequencing, regional rollout differences, or interactions with existing Spotify subscription flows. The product operates at global scale, so the investigation must account for market, platform, language, content, and payment variability.

Frame how you would diagnose the problem before jumping to fixes. Your task is to define the anomaly clearly, identify where in the funnel conversion changed, validate whether the data is trustworthy, and narrow the root cause through segmentation and evidence.

The investigation should consider:

- The exact conversion metric, denominator, time window, baseline, and expected post-launch behavior.

- Funnel breakdowns across discovery, audiobook detail pages, sampling/previews, pricing or entitlement screens, checkout, payment success, and post-purchase access.

- Segmentation by country, platform, app version, acquisition source, user type, subscription status, language, catalog availability, and new vs. returning users.

- Instrumentation checks, including event firing, attribution changes, experiment exposure, deduplication, payment reporting delays, and dashboard definitions.

- Product hypotheses around UI confusion, recommendation quality, price sensitivity, content relevance, creator/catalog gaps, and competition with existing listening habits.

- Operational hypotheses around rollout timing, localization, licensing restrictions, payment failures, app performance, customer support volume, and regional compliance constraints.

- Evidence needed to prioritize causes, quantify impact, and distinguish correlation from causation.

- Immediate mitigation options, longer-term prevention mechanisms, and how you would communicate findings to product, data, engineering, marketing, and creator-facing teams.

The goal is to demonstrate a structured RCA approach for a complex global launch: clarify what fell, where it fell, who was affected, whether the measurement is valid, what evidence supports each hypothesis, and what decisions the team should be able to make from the investigation.