Source: Lewis C. Lin’s Newsletter
Netflix's recommendation engine faces a choice: prioritize completion rates (a metric that shows user stickiness) or prioritize discovery and catalog diversity (which can reduce churn and boost long-tail content). Optimizing for one actively suppresses the other. A completion-focused algorithm narrows suggestions toward similar content; a diversity-focused one risks surfacing content users abandon, which tanks completion metrics that Wall Street monitors. Most platforms default to completion because it's measurable and immediate. But studios, creators, and subscribers have incentives tied to the underutilized 90% of Netflix's catalog.