Analyze why Wrapped usage is growing but revenue is flat

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 Wrapped is seeing increased usage, particularly among audiobook listeners, but revenue has remained flat. You are asked to investigate this as a root-cause analysis problem: usage engagement is moving in a positive direction, yet monetization is not following.

Assume Wrapped is a highly seasonal, shareable experience that can influence listening behavior, retention, subscriptions, ad exposure, audiobook discovery, and creator engagement. The issue may involve differences between traffic quality, user segments, monetization surfaces, attribution windows, or changes in the audiobook business model.

Your task is to frame the anomaly clearly, identify the most likely areas to investigate, and explain how you would use data to distinguish between product, user, market, instrumentation, and monetization causes. Focus on diagnosing the problem rather than proposing a full growth strategy.

The experience should consider:

- How “Wrapped usage” and “revenue” should be defined, including numerator, denominator, time window, and attribution logic

- Segmentation by audiobook listeners, free vs premium users, geography, tenure, device, acquisition source, and engagement depth

- Whether usage growth is driven by low-monetizing cohorts, one-time visits, sharing behavior, or existing high-engagement users

- Instrumentation checks for event tracking, revenue attribution, ad logging, subscription conversion, and audiobook purchase/listen data

- Hypotheses across product engagement, ad inventory, subscription impact, audiobook monetization, pricing, licensing, and seasonality

- Comparison against prior Wrapped cycles, non-Wrapped periods, and relevant audio categories such as music, podcasts, and audiobooks

- Guardrail indicators such as retention, churn, listening hours, conversion rate, ARPU, ad load, creator payouts, and user satisfaction

The goal is to demonstrate a structured RCA approach that can separate real business underperformance from measurement artifacts, isolate the affected user and revenue segments, and identify what evidence would be needed before deciding on mitigation or follow-up action.