Product design question

Consider Amazon Prime's search engine. How would you enhance user experience while searching for videos?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Whether the candidate can identify specific search UX gaps for a video product distinct from Amazon's core retail search.

Clarify the use case: searching for something to watch is exploratory and mood-based, unlike retail search which is usually intent-driven for a known item.
Name pain points: results dominated by exact title matches instead of thematic or mood-based matches, and weak filtering by attributes like runtime, genre mix, or cast.
Prioritize natural language and intent-based search, for example letting users search 'funny movie under 90 minutes' rather than exact titles only.
Propose surfacing rich metadata in results (ratings, similar titles, why recommended) directly in search results, not just after clicking in.
Define success as search-to-watch conversion rate and reduced time spent browsing after a search before starting playback.

Distinguishes exploratory video search from transactional retail search, since Amazon's core search UX doesn't map directly to this need.
Proposes natural language, intent-based search as a concrete fix matching how people actually decide what to watch.
Defines success with a time-to-play metric, capturing decision friction, not just search result relevance.

Treating video search the same as product search without adjusting for browsing versus intent-driven behavior.
Focusing only on search relevance without addressing decision friction after results appear.

How would you handle search when a user doesn't know exactly what they want to watch?
What would you measure to know natural language search is actually helping over keyword search?