Semantic Search
Semantic search interprets the meaning and intent behind a query rather than matching exact keywords. Using vector embeddings, it represents words and passages as numerical relationships, so it can return results that are conceptually related even when they share no literal terms with the search.
Why It Matters
It powers modern search and AI answer engines, matching content to intent instead of strings. Optimizing for meaning and topical depth, not just keywords, is what makes content retrievable in this model.
Common Mistake
Still writing for exact-match keywords and ignoring intent. Stuffing a page with a target phrase while leaving the surrounding topic thin gives semantic systems little real meaning to latch onto.