Build a metric tree for Ad-supported Plan after a major redesign at global scale

Problem Statement Description

Product context: Netflix is a streaming entertainment company; its products include subscription video, original films and series, recommendations, profiles, games, and ad-supported plans.

Netflix has completed a major redesign of its Ad-supported Plan across global markets. The redesign may affect how members discover content, tolerate ad breaks, continue binge sessions, and perceive value versus both ad-free Netflix tiers and competing entertainment options. You are asked to define how the business and product teams should evaluate whether the redesigned plan is succeeding.

Focus on building a metric tree that connects high-level business outcomes to user experience, ad monetization, content engagement, and platform health. The target segment includes binge watchers, whose behavior may be especially sensitive to ad load, interruption timing, recommendation quality, and streaming reliability across long viewing sessions.

This is a metrics interview question, so the emphasis is not on proposing new features. The expected scope is to define useful metrics, clarify denominators and cohorts, identify instrumentation needs, and explain how the tree would support decision-making after launch at global scale.

The metric tree should consider:

- The north-star or top-level outcome for the Ad-supported Plan and how it differs from ad-free subscription success.

- Clear metric definitions, including numerator, denominator, time window, and whether metrics are member-based, profile-based, session-based, or impression-based.

- Cohorts such as new subscribers, downgraders from ad-free plans, returning members, binge watchers, regions, devices, content types, and maturity of ad markets.

- User experience signals around discovery, playback, ad interruptions, session continuation, completion, churn risk, and satisfaction.

- Ad business metrics such as inventory, fill, ad exposure, revenue quality, advertiser demand, and user tolerance, without optimizing ads at the expense of retention.

- Instrumentation needed to measure ad delivery, skipped or failed ad events, playback quality, content engagement, plan changes, and downstream retention.

- Guardrail metrics for streaming quality, customer support contacts, cancellations, paid plan cannibalization, privacy compliance, and regional localization issues.

- How the metric tree would help teams diagnose trade-offs and make launch, iteration, or rollback decisions after the redesign.

The goal is to produce a structured, decision-ready metric framework that Netflix leadership and product teams could use to judge whether the redesigned Ad-supported Plan improves sustainable member value and business performance globally, especially for high-engagement binge watchers.