What Search Intent means
The conventional four types are informational, navigational, commercial investigation and transactional. Matching content to intent is more predictive of performance than matching keywords.
Conversational queries make intent easier to read, because people state it explicitly rather than compressing it into three words.
Why it matters for AI search
Intent determines your zero-click exposure. Informational queries are heavily answered by AI Overviews; transactional ones far less so.
It also determines what content should exist. A comparison query needs an honest comparison, not a product page, and models are good at telling the difference.
See it in action
The four intent types and their exposure to AI answers.
Exposure tracks intent almost exactly.
If your traffic is weighted to informational queries, you're most exposed. That's not a reason to abandon them — but it should change how you value them.
How to get it right
Working with intent
- Classify your priority queries by intent before deciding what content to build
- Match the content format to the intent — comparison queries need comparisons
- Model zero-click exposure by intent segment rather than sitewide
- For informational intent, optimize for citation since the click may not come
- For transactional intent, protect the conversion path; it's less exposed
Common questions
How do I identify intent for a query?
Look at what currently ranks. If results are comparison pages, the intent is commercial investigation regardless of how the query reads.
Can one query have mixed intent?
Frequently. Many queries serve two intents, which is why results often mix formats. Cover the dominant one and address the secondary within the page.
Does intent matter more or less with AI?
More. Conversational queries state intent explicitly, and models select content matching it. Format mismatches are penalised more sharply than in classic search.
Related concepts
These come up alongside Search Intent constantly.