I went straight into user needs and worked outward from there.
Start by clarifying the user problem and business goals for visual search on Netflix, then outline a high-level design process from user research to prototyping. Focus on how visual search can enhance content discovery and engagement, and discuss trade-offs and success metrics.
Pro tip: Anchor your answer in Netflix's unique content and user behaviors—emphasize how visual search can reduce decision fatigue and increase time spent on the platform, not just replicate existing solutions.
Ask questions to understand the target users, business objectives, and constraints (e.g., mobile vs. TV, content library). Define what success looks like for visual search on Netflix.
Identify key user needs and pain points in content discovery, such as difficulty finding specific scenes or actors. Validate the opportunity for visual search through data or assumptions.
Sketch the end-to-end user flow: how users initiate a visual search (e.g., upload image, screenshot, camera), how results are presented, and how it integrates with existing UI. Consider edge cases like low-quality images.
Discuss the technology stack (e.g., computer vision, ML models) and trade-offs between accuracy, speed, and cost. Address privacy and data storage concerns.
Define success metrics (e.g., search success rate, engagement, retention) and outline a plan for testing, learning, and iterating on the design.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.