Classic product sense question and I went way too broad at first.
Start by clarifying the goal of improving search—whether it's relevance, speed, personalization, or discovery—and then segment users and use cases. Structure your answer around a prioritized set of improvements, tying each to user value and business impact, and close with how you'd measure success.
Pro tip: Anchor your improvements in Yelp's unique data—reviews, photos, and local business attributes—and show how you'd balance short-term wins with long-term strategic bets like AI-driven personalization.
Ask clarifying questions to understand what 'improve' means (e.g., relevance, speed, personalization) and which user segments or business goals are prioritized.
Map key user journeys (e.g., finding a restaurant, service, or nightlife) and highlight common frustrations like irrelevant results, lack of filters, or poor ranking.
Generate a range of ideas (e.g., semantic search, personalized ranking, visual search) and prioritize using impact vs. effort or RICE, considering Yelp's data assets.
Propose metrics like CTR, conversion, query success rate, and time-to-result, and discuss potential trade-offs (e.g., relevance vs. diversity).
Suggest a phased approach: quick wins (e.g., better filters) and longer-term bets (e.g., AI-powered personalization), with A/B testing and iteration.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.