Build a metric tree for Mobile Downloads after a major redesign

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 recently shipped a major redesign of its Mobile Downloads experience, a feature used by members who want to save shows, films, and other content for offline viewing. This is especially important for binge watchers who plan viewing sessions around commutes, travel, limited connectivity, data caps, or shared household bandwidth.

You are asked to build a metric tree that helps the product team understand whether the redesigned Downloads experience is working. The metric tree should connect the user journey from discovering downloadable content, initiating downloads, managing downloaded titles, and eventually watching offline, while also reflecting Netflix’s broader priorities around retention, personalization, content discovery, streaming quality, and global usability.

Focus on defining a clear north-star or top-level outcome for Mobile Downloads, then break it into actionable input metrics, diagnostic sub-metrics, and guardrails. The goal is not to evaluate the redesign with a single vanity metric, but to create a structure that helps teams identify where performance improved or degraded after launch.

The experience should consider:

- The key user segments and cohorts, including binge watchers, frequent travelers, low-connectivity users, new versus returning download users, and markets with different device or network constraints.

- The full denominator for each metric, such as eligible mobile users, users exposed to the redesign, users who viewed downloadable content, users who initiated downloads, and users who completed offline playback.

- Instrumentation across the redesigned workflow, including impressions, taps, download starts, completion, failures, storage issues, expiration events, offline play starts, and playback completion.

- Funnel metrics that show conversion from download discovery to successful offline viewing, not just download volume.

- Quality and reliability measures, including download speed, failure rate, playback errors, app crashes, storage limitations, and network-related interruptions.

- Engagement and retention signals that indicate whether downloads support more viewing, more completed sessions, and continued subscription value.

- Guardrails for unintended harm, such as cannibalizing streaming engagement, increasing support contacts, worsening app performance, confusing users, or creating content licensing issues.

- Decision usefulness: how the metric tree would help isolate whether a post-redesign change is due to discoverability, usability, content availability, technical performance, or user behavior.

Your goal is to describe a practical metric tree that a Netflix product team could use to monitor the redesigned Mobile Downloads experience, diagnose movement in business and user outcomes, and make confident product decisions after launch.