Up to 1,000 keywords, groups by shared words, filler words removed, runs in your browser, free, no sign-up.
Planning site pages from a keyword list, grouping keywords before a content calendar, drafting topic clusters.

Grouping by intent is where most clustering tools fall apart — they cluster by words, not meaning. How does yours handle near-duplicate keywords with different search intent, like "checker" vs "generator" terms? Asking because I plan content for a tools site and intent splits decide the page structure.


This looks like a useful and simple tool for organizing keywords into topic clusters. I like that it’s free and doesn’t require signing up. It should be a good starting point for planning website pages and content, although checking search intent and results afterward is still important. https://www.tpt.it.com
Planning content around health topics means starting with a messy list of hundreds of keyword variations, so a fast first-pass clustering like this is genuinely useful for mapping out pillar pages and supporting articles. I also appreciate the honesty that it groups by shared words only and that the groups should be treated as a draft — that sets the right expectation, since search intent still needs a manual check. One question: can the clusters be exported, for example to CSV, so they can be sorted and assigned to writers in a spreadsheet?

Grouping by intent is where most clustering tools fall apart — they cluster by words, not meaning. How does yours handle near-duplicate keywords with different search intent, like "checker" vs "generator" terms? Asking because I plan content for a tools site and intent splits decide the page structure.


This looks like a useful and simple tool for organizing keywords into topic clusters. I like that it’s free and doesn’t require signing up. It should be a good starting point for planning website pages and content, although checking search intent and results afterward is still important. https://www.tpt.it.com
Planning content around health topics means starting with a messy list of hundreds of keyword variations, so a fast first-pass clustering like this is genuinely useful for mapping out pillar pages and supporting articles. I also appreciate the honesty that it groups by shared words only and that the groups should be treated as a draft — that sets the right expectation, since search intent still needs a manual check. One question: can the clusters be exported, for example to CSV, so they can be sorted and assigned to writers in a spreadsheet?
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