Glossary
Vector Search
Vector search retrieves content by comparing embeddings, matching passages on meaning rather than exact wording. It lets an engine surface a relevant passage even when the buyer's phrasing shares no keywords with the page, which is why AI answers often quote content that never targeted the query as written.
In plain terms
The engine looks for pages that mean the same thing, not pages that use the same words.
Why it matters for B2B
Keyword lists stop being a plan. Coverage of a genuine concept — clearly explained, in one place — is what makes a page findable across the long tail of phrasings buyers actually use.
How to apply it
- Cover a concept completely on one page instead of splitting it across near-duplicates.
- Write plainly; jargon-dense text matches fewer real questions.
- Consolidate overlapping pages so retrieval is not split between them.
Related terms
Back to the full glossary (25 terms).
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