Debug a spike in complaints from students on Discover Weekly

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 seen a sudden spike in complaints from students about Discover Weekly, the personalized weekly playlist intended to help listeners find new music they are likely to enjoy. Your task is to investigate what may be driving the increase, determine whether it reflects a true product issue or a measurement/support artifact, and frame how the team should respond.

Focus specifically on the student segment, which may include users on student plans, college-aged listeners, campus-heavy geographies, or listeners with student-like usage patterns. Complaints could relate to recommendation quality, playlist freshness, repeated tracks, irrelevant genres, explicit content, localization, app performance, availability timing, or changes in listening context such as semester schedules, exams, travel, or social trends.

You are not expected to jump to a fix. The interview is about how you structure the RCA: defining the anomaly, narrowing the affected population, validating the data, generating hypotheses, identifying what evidence would confirm or reject each hypothesis, and deciding what immediate mitigations or follow-ups are appropriate.

The experience should consider:

- How to define the complaint spike, including baseline period, complaint rate denominator, support channel coverage, severity, and whether volume or rate changed

- Segmentation by student plan status, age proxy, geography, device, platform version, acquisition cohort, listening intensity, and playlist engagement history

- Instrumentation checks across support tickets, in-app feedback, skips, hides, saves, playlist starts, completion, retention, and recommendation-service logs

- Hypotheses across recommendation model changes, catalog/licensing shifts, playlist generation timing, app/client bugs, experimentation, seasonality, and external music trends

- Differences between subjective dissatisfaction and measurable degradation in Discover Weekly quality or usability

- Evidence needed to distinguish a broad Spotify issue from a student-specific issue

- Short-term mitigation options, communication needs, and escalation paths if the issue affects trust in personalization

- Prevention mechanisms such as monitoring, alerting, experiment guardrails, and post-launch checks for key listener segments

The goal is to demonstrate a clear, disciplined RCA approach for a personalized music discovery product: isolate the problem, validate the signal, prioritize likely causes, protect the student listener experience, and help Spotify make a confident decision on whether to roll back, patch, communicate, or continue investigating.