Protected: Discovery Patterns : Search and Browse — Kristine October 30, 2025 There is no excerpt because this is a protected post. Continue Reading
Search and Browse Patterns October 30, 2025 Netflix, driven by subscriptions, is obsessed with engagement to ensure retention. Its user flow is one of passive discovery; it “pushes” content via personalized… Continue Reading
Product Sense Pushups: Discovery Patterns — Search and Browse October 30, 2025 Netflix: Personalized but PassiveOn Netflix, I often catch myself saying, “I’ll just see what’s recommended.” The platform’s confidence in knowing me feels flattering—but also… Continue Reading
Product Sense Pushups: Discovery Patterns — Search and Browse October 30, 2025 Finding What You Didn’t Know You Wanted Netflix, YouTube, and Airbnb each choreograph discovery differently, as “finding” means something different for their business models…. Continue Reading
Product Sense Pushups: Discovery Patterns — Search and Browse October 30, 2025 Recommendations The Netflix recommendation algorithm provides the user with personalized suggestions while also highlighting the content that is generally popular across the platform. Thus,… Continue Reading
Discovery Patterns — Search and Browse October 30, 2025 Netflix, YouTube, and Airbnb all help people “find stuff,” but the way they do it fits the kind of choice the user is making…. Continue Reading
Discovery Patterns: Netflix, YouTube, and Airbnb October 30, 2025 Finding the “right” thing looks different when each platform defines success differently. Netflix optimizes for time spent watching; YouTube for ad inventory and repeat engagement; Airbnb for conversion… Continue Reading
Pushups — Discovery Patterns October 30, 2025 Netflix Netflix’s recommendation algorithms try to maximize the time you spend on the platform. This is because they make all their money form subscriptions,… Continue Reading
Discovery Patterns — Search and Browse October 30, 2025 Netflix Netflix releases on a recommendation discovery model which is designed to keep users watching for as long as possible. By minimizing search and… Continue Reading
