Keyword Clustering

Grouping keywords by topics to optimise a single page for an entire cluster of queries.

In brief

Keyword clustering is the process of grouping semantically related search queries into clusters. The goal is to create a single page that will rank for all queries in the cluster, rather than creating dozens of separate pages for each keyword.

What is Keyword Clustering

Modern SEO is built on the principle: one page – one topic (cluster). Clustering helps understand which queries are so similar they can be grouped together, and which are so different they need separate pages. Without clustering, you risk cannibalisation or a bloated site with thin pages.

Clustering methods

  • By SERP (hard clustering) – two queries are in the same cluster if they share ≥3 identical URLs in top 10. The most reliable method, based on actual ranking data.
  • Semantic (soft clustering) – based on lexical analysis, synonyms, LSI terms (faster but less accurate).
  • Manual – expert grouping in Excel/Google Sheets (for small projects).

Example: queries 'SEO audit', 'site SEO audit', 'SEO website check' would be in the same cluster because their SERP overlap by 80%.

How to use clusters in optimisation

  • Title – include the main (most frequent) keyword of the cluster.
  • H1 – main keyword or a close variant.
  • H2 / H3 – other keywords from the cluster and their variations.
  • Content – naturally incorporate all keywords while answering related questions.
  • Internal links – use anchors from the cluster when linking to this page.
Automatic clustering tools: Rush Analytics, Topvisor, Serpstat, KeyCollector (with clustering module).

Common questions

Between 3 and 50 queries per page. Too small (1‑2) is inefficient; too large is hard to cover comprehensively.
Split them into separate clusters. SERP‑based clustering will separate them automatically if the top 10 results differ.
Yes. For example, 'buy iPhone 15', 'iPhone 15 price', 'iPhone 15 specs' would be one cluster (commercial page). 'iPhone 15 reviews' might go to a separate article cluster.
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Keyword Clustering — What is it?