Keyword research exports often contain dozens of phrases that describe the same search need. Publishing one page per phrase produces thin pages that compete with each other. This browser-based clusterer groups phrases by meaningful shared terms, giving you a fast first pass at which keywords may belong on one page. Because lexical similarity is not the same as matching search results, review every cluster by intent before finalising a content plan.
It removes common stop words, compares the meaningful terms in each phrase, and groups phrases whose word sets overlap above your selected threshold.
No. SERP clustering groups keywords when the same URLs rank for them and requires live search-result data. This tool uses lexical similarity, which is faster and private but needs human review.
Start with balanced. Use broad for messy lists with many variations, or strict when you only want phrases with strong word overlap.
It exposes phrases that may deserve one comprehensive page instead of several near-duplicates. Cannibalisation still depends on intent and your existing site, so the clusters are planning suggestions rather than automatic decisions.
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