Executive summary
Commercial intent mapping classifies every query by its distance from a purchase, then concentrates optimisation on the transactional and commercial-investigation clusters. The result is a prioritised keyword universe where each term is tied to a page type and a revenue role rather than a raw volume number.
What this helps you decide
Where each query belongs on the intent spectrum and which page type should serve it.
Business problem
Teams spread effort evenly across informational and transactional queries, so budget is consumed by traffic that never converts. Without an intent map, money pages are starved while blog posts over-rank.
Step-by-step process
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1
Assemble the query universe
Pull queries from Search Console, your rank tracker, paid-search terms and AI-answer prompts into one sheet. Include volume, current URL and current position so every row is decision-ready.
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2
Label intent using the Commercial Intent Matrix
Tag each query as informational, commercial-investigation, transactional or navigational. Use SERP evidence: if the SERP shows product pages and shopping units, the intent is commercial regardless of the words.
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3
Attach the correct page type
Map transactional queries to product or service pages, commercial-investigation queries to comparison and alternative pages, and informational queries to guides that feed the money pages via internal links.
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4
Score revenue proximity
Weight each cluster by conversion rate and average order value, not by volume. A 200-search 'best X for Y' term often beats a 20,000-search definition query on revenue.
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5
Find the gaps
Flag high-value commercial queries where you have no dedicated page or rank beyond position 10. These become the build-and-optimise backlog.
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6
Sequence the work
Order the backlog by revenue proximity multiplied by achievability, so the first pages shipped are both winnable and lucrative.
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7
Review quarterly
Re-pull SERPs and AI answers each quarter; intent drifts as Google and AI engines change which page types they reward.
Worked example
Checklist
- Every target query has an intent label backed by SERP evidence
- Each intent cluster is tied to a specific page type
- Revenue proximity is scored, not raw volume
- Unserved commercial queries are on a build backlog
- The map has a quarterly review date
Common mistakes
- Judging intent from the words alone instead of the live SERP
- Prioritising by search volume rather than revenue proximity
- Pointing transactional queries at blog posts that cannot convert
30-minute experiment
KPIs to track
- Share of commercial queries served by a fit-for-purpose page
- Revenue-weighted keyword coverage
- Conversions from mapped money pages
FAQs
How is commercial intent different from keyword difficulty?
Difficulty estimates how hard a query is to rank for; commercial intent estimates how close the searcher is to buying. You need both, but intent decides whether ranking is even worth chasing.
Do informational queries still matter?
Yes, but as feeders. They build topical authority and internal links into money pages rather than being the conversion event themselves.
Recommended next steps
Where this fits - and what's next
The SearchScore path from a problem you feel to visibility you can measure.