How would you measure product-market fit for Discover Weekly among students

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 wants to understand whether Discover Weekly has strong product-market fit specifically among students. This segment may have distinct listening patterns, budget sensitivity, social discovery behaviors, commute/study use cases, and high exposure to competing discovery surfaces such as TikTok, YouTube Music, Apple Music, and campus/social recommendations.

Your task is to define how you would measure product-market fit for Discover Weekly in this student segment. Focus on what “fit” should mean for a personalized weekly music discovery product, how to distinguish casual usage from meaningful reliance, and how the measurement system would help Spotify decide whether to invest further, adjust the experience, or investigate gaps.

The answer should be framed as a metrics problem, not a feature proposal. You should clarify the target population, define the key metric or metric set, explain how data would be instrumented and segmented, and identify guardrails that prevent misleading conclusions.

The experience should consider:

- Who counts as a “student” and whether the measurement should differ by geography, plan type, age band, school calendar, or new vs. existing Spotify users.

- What user actions signal real value from Discover Weekly, such as listening depth, saves, playlist follows, repeat engagement, skips, shares, or downstream listening.

- How to define denominators clearly, including eligible users, exposed users, active Spotify users, and users who actually open Discover Weekly.

- How to separate Discover Weekly impact from general Spotify engagement, seasonality, marketing, exams, vacations, or broader music trends.

- Which cohorts should be tracked over time to assess retention, habit formation, and continued relevance of recommendations.

- What instrumentation is needed across impressions, starts, skips, saves, follows, completion, downstream artist engagement, and subscription or ad-supported behavior.

- Which guardrail metrics matter, such as recommendation quality, user satisfaction, listening diversity, churn, ad load tolerance, and cannibalization of other Spotify surfaces.

- How the metrics would support a decision on whether Discover Weekly has achieved product-market fit among students.

The goal is to produce a clear measurement framework that Spotify leadership could use to evaluate whether Discover Weekly is genuinely valuable, differentiated, and habit-forming for students, while avoiding vanity metrics and ensuring the results are actionable for product and business decisions.