Keyword Clustering & Topical Map Builder
Groups a raw keyword list into intent-based clusters, maps them into a hub-and-spoke topical architecture, and flags which clusters need one page versus many.
Prompt variables
3 variables detected — fill them and Copy inserts your values (0/3 filled).
Take my raw keyword list and turn it into a topical map I can hand to a content team. Work in these passes:
**Pass 1 — Intent labeling:**
Tag every keyword: informational / commercial-investigation / transactional / navigational. Where a keyword is ambiguous, note the two plausible intents — ambiguity changes page strategy.
**Pass 2 — Clustering:**
Group keywords that one page could satisfy together. The test is NOT shared words — it is shared intent: "best crm for startups" and "startup crm comparison" cluster together; "crm" and "crm definition" do not. Name each cluster by its head term. Important caveat to act on: you cannot see live SERPs, so mark every cluster where you are less than confident one page can rank for all terms with [VERIFY-SERP] — the reader should spot-check those against actual results before committing.
**Pass 3 — Topical map:**
Arrange clusters into hubs and spokes:
- **Hub pages** — broad head-term clusters that link down to spokes
- **Spoke pages** — specific clusters that link back up and sideways
- For each page: working title, primary keyword, supporting keywords, intent, funnel stage, and 2-3 internal links (which hub/spokes it connects to)
**Pass 4 — Prioritization:**
Order the build sequence by (a) business value for {{business}}, (b) how much of the cluster is realistically winnable for a site with {{site_authority}} authority, (c) dependency — hubs whose spokes give them meaning come after 2-3 spokes exist.
Output as a Markdown table per pass. Do not invent search volumes — if I did not supply them, leave the column out entirely.
Business and what it sells: {{business}}
Site authority (new / established / strong): {{site_authority}}
Keyword list:
{{keywords}}
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