Does this do semantic clustering?

No. It clusters on shared words. Semantic clustering requires an embedding model or live search result comparison, neither of which runs in a purely local tool like this.

Where do single keywords go?

Anything below the minimum group size is listed under Ungrouped at the end of the output so you can review them individually.

Can I group by two words instead of one?

Not directly, but grouping by first word and then re-running the largest group by last word gives a similar two-level view.

Keyword Grouping Tool

Paste a keyword list and group it by shared words, first word, last word or a custom pattern to see your natural content clusters.

Your input

Everything you type is processed in this browser tab. Nothing is uploaded, logged or stored.

Results

Fill in the fields and choose Run tool to see results here.

About this tool

A flat list of four hundred keywords tells you nothing about how many pages you need. Grouping tells you everything. This tool clusters a pasted keyword list by the words the phrases share, revealing where one page can serve twenty phrases and where a phrase stands alone and needs its own treatment.

How it works

Each keyword is tokenised into words. In shared-word mode the first meaningful word longer than three characters becomes the group key, which usually captures the head term. First-word mode groups by prefix, which is ideal when your list is dominated by modifiers such as best or cheap. Last-word mode groups by suffix, which surfaces format patterns such as review, template or near me. Groups smaller than your minimum are collected in an ungrouped bucket so nothing disappears.

1Paste your keyword list, one phrase per line.
2Choose whether to group by shared word, prefix or suffix.
3Set the minimum group size to filter out one-off clusters.
4Generate, then export the grouped output as TXT or CSV.

Example

Input

best running shoes, running shoes for flat feet, cycling shoes review

Output

— Running (2) — best running shoes, running shoes for flat feet · — Cycling (1) —

When to use it

Deciding how many pages a keyword export should turn into.
Finding modifier patterns that deserve a dedicated comparison page.
Splitting a large list between writers by theme.
Auditing an existing site's keyword coverage for gaps and overlaps.

Tips

Clean and deduplicate the list first so groups reflect real distribution.
Try all three modes on the same list; each reveals a different structure.
Where a group is huge, re-run grouping on just that group with last-word mode.

Limitations

Grouping here is lexical, not semantic. Two phrases that mean the same thing with different words — trainers and sneakers, for example — land in different groups. It also has no view of search results, so it cannot tell you whether two phrases genuinely share intent.

Frequently asked questions

Does this do semantic clustering?: No. It clusters on shared words. Semantic clustering requires an embedding model or live search result comparison, neither of which runs in a purely local tool like this.
Where do single keywords go?: Anything below the minimum group size is listed under Ungrouped at the end of the output so you can review them individually.
Can I group by two words instead of one?: Not directly, but grouping by first word and then re-running the largest group by last word gives a similar two-level view.