Search intent explained: the four types and how to read them

The four are not a ladder the customer climbs in order. Our guide to mapping a journey from search data shows people looping between informational and commercial searches until something gives them enough confidence to make a transactional one. A single person can make all four in an afternoon. What matters for a website is that each query type wants a different page, and Google has already decided which type a query is before your page enters the contest.

Google's Search Quality Rater Guidelines, the public document its human raters use to judge results, do not use the industry's four words. They describe user intent as Know (the user wants information), Know Simple (a short factual answer that fits in a sentence or two), Do (the user wants to accomplish a goal or engage in an activity, which includes buying and downloading), Website (the user wants a specific site or page) and Visit-in-person (the user wants a nearby physical place). The two schemes line up closely: Know is informational, Website is navigational, Do covers transactional and much of commercial, and Visit-in-person is the local, map-pack intent that the four-type model tends to bury under "navigational".

That extra category matters in Australia because so much demand is local. "Gp near me" at 110,000 searches a month and "medical centre near me" at 60,500 are Visit-in-person queries. The page that wins them is not a page at all in the traditional sense, it is a Google Business Profile with the right category, hours and reviews, sitting in the map pack above every organic result. A business that reads those queries as informational and writes a guide about choosing a GP has misread the intent and built for the wrong stage. The raters' Know Simple category is also the seed of the featured snippet and, increasingly, the AI answer: a query with a short factual answer gets one, and the page that states it plainly gets cited.

Here are twelve queries we looked up in July 2026 for pages on this site, with their real Australian monthly volume and the intent our platform assigned. The pattern repeats in every category we map: the transactional and navigational near-me terms carry the volume, and the informational and commercial terms carry the questions a business must answer to be the one chosen when the volume arrives.

The table is the whole discipline in one place. Every page on a site should be able to say which intent it serves, and a page that tries to serve two usually serves neither. When we plan a site from a topical map, each node carries its intent, which is how the architecture decides itself: questions become guides, comparisons become comparison pages, actions become service pages, and places become profiles.

Intent also settles a newer question: what should sit behind a login. The rule is simple once the intents are labelled. Every pre-purchase intent (informational, commercial, transactional, navigational to your brand, Visit-in-person) must be open and indexable, because the searcher has not chosen you yet and cannot be asked to log in to find out whether they should. Google and the AI engines can only cite what they can read. Post-purchase intent is different. The customer who already has an account is searching for how to use what they bought, what their report says, what the members-only material covers, and that content can sit behind a login where it is more valuable gated: it deepens the relationship, it is the reason to keep the account, and every visit is first party data you own.

The mistake runs in both directions. Gating pre-purchase answers starves the open site of the pages that win the searcher in the first place. Leaving post-purchase knowledge open gives away the thing that makes the account worth having. Our client portal guide takes this split and turns it into a site architecture, and the paywall SEO guide in the same series covers how Google treats the content that sits behind the wall.

AI engines read intent the same way and then act on it more aggressively. ChatGPT, Google AI Overviews and AI Mode, and Perplexity answer Know and Know Simple queries directly, citing the pages that state the answer plainly, which is why answer-first structure and a definition in the first paragraph matter more than ever. For commercial queries they build the comparison themselves from sources they trust, so the honest comparison page with real numbers is the one that gets cited rather than the sales page. For transactional and Visit-in-person queries they increasingly hand off to a map, a booking link or a product listing, which means the profile and the service page still do the work. The intent discipline does not change; the penalty for getting it wrong gets larger, because an engine that has already answered the question sends no click at all to the page that answered it badly. Our guides on getting cited by AI in Australia and answer engine optimisation go further.

Reading intent is included in every keyword and topic research engagement, and it is the second step, after the journey map, of the data layer our SEO service is built on. Our Snowball SEO platform labels the intent of every term it returns, which removes the hours of manual results-page reading other agencies bill for and leaves the budget for the pages themselves.