SEO & GEO/AEO

Verified against ChatGPT · 2026-07-25

Turn a messy keyword list into intent-based content clusters

Paste a raw keyword export and get it grouped into distinct content clusters by search intent, not shared words — so you know how many pages to actually build, which keywords would cannibalize each other, and which cluster is the pillar.

ChatGPTClaudeGemini

The prompt

Ready to copy — highlighted parts are example details you can swap.

Act as an SEO information architect. Site context: we sell CRM software aimed at small teams under 20 people

Raw keyword list:
best crm for small business (2400)
crm software comparison (1900)
free crm for startups (1600)
crm pricing (880)
how to choose a crm (720)

1. Group these into distinct content clusters, where a cluster means keywords one single page could realistically satisfy without cannibalizing another page on the same site. Use search intent as the primary grouping signal, not shared words — "crm pricing" and "crm software comparison" look similar but serve different intents and should NOT be forced into one cluster unless you can justify it.
2. Name each cluster with the page title it implies — outcome-first, not just the seed keyword.
3. For each cluster, state the dominant intent (informational / commercial-investigation / transactional) and the single keyword that should be the page's primary target. The rest become secondary targets the page ranks for through topical depth, not separate H1s.
4. Flag cannibalization risks: any two keywords in my list that look like they'd want the same page, where I should pick one primary target and fold the other in rather than building two competing pages.
5. Flag anything you can't confidently cluster — ambiguous keywords where intent depends on the searcher's stage — and tell me what additional context would resolve it.
6. Suggest the pillar-cluster hierarchy: if any clusters are naturally subtopics of a broader pillar page, name the pillar.

Output as a table: Cluster name | Primary keyword | Secondary keywords | Intent | Suggested page type.
Customize the highlighted detailsoptional — the prompt above already works

Why this works

Clustering by intent instead of shared words is the difference between building a site architecture and building a pile of similar pages — two pages chasing the same intent split ranking signals between them (cannibalization) instead of compounding into one authoritative result. The pillar-cluster structure this produces mirrors how search engines increasingly reward topical depth: a hub page surrounded by well-linked subtopic pages signals comprehensive coverage of a subject in a way isolated thin pages don’t, because semantically related queries get treated as one intent cluster even when the phrasing differs. Explicitly flagging ambiguous keywords instead of forcing a confident-sounding cluster prevents the most common failure mode in DIY keyword clustering: architecture decisions made on a guess that only surface as a problem once two pages are already live and competing.

What you get back

Cluster name | Primary keyword | Secondary keywords | Intent | Suggested page type "Best CRM for Small Business" | best crm for small business | free crm for startups | Commercial-investigation | Comparison/listicle "CRM Pricing Explained" | crm pricing | — | Commercial-investigation | Pricing breakdown page Cannibalization risk: "crm software comparison" and "best crm for small business" want the same page — merge, pick "best crm for small business" as primary. Pillar: "CRM Pricing Explained" is a natural subtopic of "Best CRM for Small Business" — link it as supporting content, not a competing target.

Verified against

ChatGPT GPT-5.1 · 2026-07-25

Gemini Gemini 3 Pro · 2026-07-18

Changelog

  • 2026-07-25 Initial publish, verified against ChatGPT and Gemini.

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