Product Sense: Redesign Search

Interviewer

Our users complain that search on our e-commerce site is slow and gives irrelevant results. How would you approach fixing this?

Candidate

First, I'd define what 'slow' and 'irrelevant' mean quantitatively. I'd look at: p50/p95/p99 search latency, click-through rate on first result, bounce rate after search, and conversion rate from search vs browse. I'd talk to users and support to understand specific pain points. 'Irrelevant' could mean: (1) results don't match query intent (e.g., searching 'apple' returns fruit when they want laptops), (2) results are out of stock, (3) results aren't personalized. For speed: add a dedicated search service with Elasticsearch or Typesense. Cache popular queries with Redis. Implement search-as-you-type with debouncing. For irrelevant results: improve the ranking model. I'd start with simple signals: text relevance (BM25), popularity, recency, availability. Then add personalization based on user's browsing history. I'd also add synonyms and typo tolerance. And analyze search logs for common failed searches - those are product opportunities.

Interviewer

The product manager wants to ship a new search algorithm in 2 weeks. What do you do?

Candidate

I'd propose a phased approach. In 2 weeks, we can: (1) Add typo tolerance and synonyms (configuration change), (2) Implement result deduplication, (3) Add a simple popularity boost to ranking. These are high-impact, low-risk changes that can ship quickly. Meanwhile, I'd propose a parallel track for the more complex ranking model with A/B testing, which would take 4-6 weeks. This way we deliver immediate value while building toward the longer-term solution.