I spent too long on the PMF framing and not enough time being concrete about metrics.
Start by defining what product-market fit means for a video feature targeting young adults, then outline a framework that combines quantitative metrics (engagement, retention) with qualitative signals (user feedback, social buzz). Emphasize the importance of benchmarking against Netflix's existing content and iterating based on data.
Pro tip: Don't just focus on vanity metrics like views; prioritize retention and repeat usage, as they are stronger indicators of long-term fit. Also, consider cohort analysis to see if young adults are adopting and sticking with the feature over time.
Clarify what PMF means in this context: are young adults not just trying but repeatedly using the feature and integrating it into their viewing habits? Establish clear hypotheses about target user needs and desired outcomes.
Select metrics that measure acquisition, engagement, retention, and referral. For a video feature, focus on metrics like daily/weekly active users, watch time per user, completion rate, and 30-day retention.
Gather user feedback through surveys, interviews, and social media listening to understand sentiment and uncover unmet needs. Look for organic sharing and word-of-mouth among young adults.
Compare the feature's performance against Netflix's existing benchmarks and industry standards. Analyze cohorts to see if young adults are adopting at a higher rate than other demographics.
Use A/B testing and rapid experimentation to refine the feature. Define success thresholds (e.g., 40% 30-day retention) and decide whether to double down, pivot, or kill the feature based on data.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.