I learned this the hard way on a book platform I'm working on. While semantic search is useful for discovery, we found that prioritizing exact matches is critical. It seems users get pretty frustrated if they type a specific title and get a list of conceptually similar results instead of the actual book. We ended up having to tune the ranking to heavily favor literal string matches over the vector distance to keep people from bouncing.

I remember eBay 30 years ago when it would showed you whatever you typed in. Compared to 2026 where it only shows you everything except the thing you typed in.

Especially with small datasets it’s more important to be exact at the expense of a user having to fix a typo.