Search Intent Mix

Why it matters

Two sites with identical click totals can have completely different commercial value. A site whose traffic is 80% informational has an audience but very little buying intent in front of it; a site whose traffic is 50% transactional is much closer to revenue.

Search Intent Mix turns the question "what kind of demand are we capturing?" into a chart you can hand to marketing, product or finance.

How it's built

• Each query is run through an intent classifier that combines lexical signals (buy / pricing / discount / demo → transactional, vs / comparison / best → commercial, how / what / why / guide → informational, login / dashboard / contact → navigational) with brand-token detection (anything matching the site's brand matcher → brand).
• Each query is bucketed exactly once. Brand is checked first, then transactional, then commercial, then navigational, then informational; queries that match no rule fall into the informational bucket as a default.
• Clicks, impressions, CTR and average position are aggregated per bucket across the selected window.

How to read it

• Look at share of clicks per intent, not absolute numbers. A 5-point shift away from transactional toward informational quarter-over-quarter is meaningful even if total clicks are flat.
• Compare impressions vs clicks share per bucket. If transactional has 15% of impressions but only 6% of clicks, your high-intent SERP listings are losing the click — usually a title/meta or SERP-feature problem.
• Use it to scope content briefs. If you've identified "we under-rank on commercial intent" you'll prioritise comparison and "best X" pages over yet another how-to article.

Data requirements

• GSC Performance daily data with query strings (anonymised queries are dropped).
• Brand terms configured for the site so the classifier doesn't mis-bucket brand traffic into navigational or informational.