Free Keyword Clustering Tool

Group a keyword list into topics by the words the keywords share. Fast, private, and honest about the method — this is word overlap, not semantic AI.

Runs entirely in your browser — nothing is uploaded

Read this before you use the output. This groups keywords by the words they share. It is not semantic clustering and there is no AI involved. It will never put “seo agency” and “search engine optimisation firm” together, because they have no words in common — even though they mean the same thing. Real semantic clustering needs a language model or SERP-overlap data. Treat these groups as a fast first sort, then use your judgement.

Your keywords

One keyword per line. Works best with 20 or more.

Smallest group

Raise this to get fewer, larger groups.

How the grouping works, so you can judge the output: each keyword joins the group of the longest phrase it shares with other keywords — up to three words. Phrases rather than single words, because single words split families that belong together: “google business profile optimisation” shares “optimisation” with “wordpress speed optimisation”, and matching on one word would file it there instead of with your other Google Business Profile terms. Common words like “the” and “for” are ignored.

What this tool does not do: Groups by shared words, not meaning. It will never put "seo agency" and "search engine optimisation firm" together — real semantic clustering needs a language model or SERP data.

How to use this tool

Paste at least 20 keywords, one per line.
Adjust the minimum group size to get fewer, larger groups.
Read the groups as a first sort, then merge and split them by hand.
Export as CSV to carry into a content plan.

What is Keyword Clustering Tool?

Clustering exists to answer one question: how many pages does this keyword list actually need? Keywords that mean the same thing belong on one page competing for all of them, not on three pages competing with each other.

What this does is group keywords by the rarest meaningful word they share. That catches the obvious families — everything containing "pricing", everything containing "wordpress" — quickly and predictably.

What it cannot do is recognise that two phrases mean the same thing in different words. Proper semantic clustering compares which pages already rank for each keyword, or uses a language model. Both cost money, and neither can run in your browser. Tools that call string matching "AI clustering" are describing this same technique with a better name.

Best practices

Clean and de-duplicate the list first.
Treat the output as a draft; merge groups that clearly mean the same thing.
One page per cluster, targeting the whole group rather than one keyword.
For a serious content plan, verify clusters against what actually ranks for each term.

Frequently asked questions

Is this AI clustering?

No, and it says so at the top of the page. It groups by shared words. Semantic clustering needs a language model or SERP-overlap data, neither of which a free browser tool has. Calling this AI would make the output look more trustworthy than it deserves.

Why are some keywords ungrouped?

They share no significant word with enough other keywords. That often means they are genuinely separate topics — or that your list is too short for patterns to emerge. Try 50 or more.

How do I do this properly?

The accepted method is SERP overlap: if two keywords return largely the same top results, Google treats them as the same intent, so they belong on one page. That requires ranking data from a paid tool. This is the fast approximation you do first.