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Vector Search

A search method that finds content based on semantic similarity rather than exact keyword matching.

Understanding Vector Search

Vector search uses embeddings to find content that is conceptually similar to a query, even without matching keywords. This is how AI systems like Perplexity and ChatGPT with browsing find relevant sources. For AI visibility, vector search means your content can be discovered based on meaning and context, making comprehensive, semantically rich content more valuable than keyword-stuffed pages.

Related Resources

Related Terms

RAG (Retrieval-Augmented Generation)Embeddings

Helpful Checklists

AI SEO Audit ChecklistChatGPT Optimization ChecklistStructured Data Implementation ChecklistProgrammatic SEO Launch Checklist

Templates

Robots.txt for AI Crawlersllms.txt File TemplateOrganization Schema (JSON-LD)Article Schema (JSON-LD)

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