Search intent (also called user intent or query intent) is the underlying goal or purpose behind a search query — what the user is actually trying to accomplish. Matching content to search intent is the foundation of both traditional SEO and AEO.
The four categories of search intent
Informational: User wants to learn.
“How does RAG work” / “What is AEO” / “Why does AI give different answers”
Navigational: User wants to reach a specific destination.
“[Brand] login” / “[Brand] pricing page” / “Anthropic documentation”
Commercial investigation: User is comparing options before deciding.
“Best AI visibility tools” / “[Brand A] vs [Brand B]” / “Alternatives to [Competitor]”
Transactional: User is ready to act.
“[Brand] free trial” / “Buy [Product]” / “Sign up for [Service]”
Why intent matching is critical for AI citation
AI engines are very good at detecting intent and matching it to appropriate content types. A marketing landing page will not be cited in response to an informational query — the engine detects the mismatch. A detailed how-to guide will not be cited as the primary source for a transactional query.
Creating content that precisely matches the intent of your target queries is a prerequisite for citation. If your content doesn’t match what the user is trying to accomplish, it won’t be selected regardless of how well it’s structured.
Intent and content format mapping
| Intent type | Best content format for AI citation |
|---|---|
| Informational | Guides, explainers, glossary entries, FAQs |
| Navigational | Optimized product/brand pages |
| Commercial investigation | Comparison pages, case studies, reviews |
| Transactional | Pricing pages, sign-up flows, product pages |
Search intent is effectively synonymous with query intent. The two terms are used interchangeably in the industry, with “query intent” being more common in AI/LLM contexts and “search intent” more common in traditional SEO contexts.