Free SEO tool

Keyword Clustering Tool

The Keyword Clustering Tool groups a list of keywords into related clusters (topic groups) automatically. Paste keywords, one per line, choose a sensitivity level, and the tool organizes them by shared, meaning-bearing words — instantly, in your browser. No signup, no upload: your keyword data never leaves your device.

100% private — runs in your browser

Instant results, no signup

Clusters up to 20,000 keywords

Your keywords

One keyword per line. Duplicates and blank lines are removed automatically.

Clustering sensitivity

Tight Balanced Broad

Advanced: fine-tune threshold

Similarity: 35% Higher = stricter matches, more clusters.

Clustering…

Privacy by design: every calculation runs in your browser. Your keyword list is never sent to a server, stored, or shared — it never leaves your device.

Why marketers use it

Key features

Everything you need to turn a raw keyword export into an organized topic map — free, fast and private.

Private by design

All clustering runs in your browser. Your keyword list is never uploaded, logged or stored — it even works offline.

Instant results

Thousands of keywords are clustered in seconds by an indexed matching engine — no queue, no processing credits.

Adjustable sensitivity

Tight, Balanced and Broad presets — plus a fine-tune slider — control how closely keywords must match to group.

Smart cluster labels

Every cluster is auto-named from its most meaningful shared words, so results read like a content plan, not raw data.

Copy & export

Copy all results, or download clusters as spreadsheet-ready CSV or TXT — including per-cluster copy buttons.

Free, no signup

No account, no email gate, no daily limits. Cluster up to 20,000 keywords per run, as often as you like.

Benefits

Why cluster your keywords?

Keyword clustering is the bridge between research and strategy — here is what it unlocks.

Plan smarter site architecture

Clusters map naturally to pages and topic hubs, so your site structure matches how people actually search.

Prevent keyword cannibalization

Grouped keywords make it obvious which terms belong on one page — instead of competing across several.

Build content briefs faster

Each cluster is a ready-made brief: one primary topic plus the variations a single article should cover.

Triage research at scale

Turn a messy 5,000-row keyword export into an organized shortlist before you spend paid-tool credits.

How it works

How to use the Keyword Clustering Tool

Paste your keywords

One per line, straight from your keyword tool export. Duplicates and blank lines are cleaned automatically.

Choose a sensitivity

Tight groups only close variants, Balanced suits most research, Broad builds wider topic groups.

Click “Cluster keywords”

Words are weighted by how rare they are in your list, and keywords with enough overlap group instantly.

Review and export

Scan the labelled clusters, check the Unclustered group, then copy or download as CSV/TXT.

KEYWORD-LIST.TXT — 12 KEYWORDS

best running shoes for flat feet
running shoes for flat feet
flat feet running shoes women
trail running shoes
best trail running shoes 2026
waterproof trail running shoes
how to clean running shoes
cleaning white running shoes
running shoe size guide
running shoes size chart
marathon training plan
beginner marathon training plan

A worked example

Paste the 12 running-related keywords shown here and click Cluster keywords on the Balanced setting — or simply press “Load example” in the tool above. You get five tight clusters with nothing left unclustered:

flat feet · 3trail running · 3clean running · 2marathon training · 2running size · 2

Generic words like “running shoes” appear in almost every keyword, so they carry little weight. Rare, meaning-bearing words like flat feet, trail and marathon decide the groups — exactly how a human would sort them.

Avoid these

Common keyword clustering mistakes

Pasting comma-separated lists

The tool expects one keyword per line. It detects comma-separated pastes and offers to convert them for you.

Mixing unrelated projects

Clustering two niches at once weakens the rarity weighting. Run one niche, market or client at a time.

Mixing languages in one run

Word-root matching is tuned for English. Cluster each language separately for the sharpest groups.

Expecting synonyms to merge

Grouping is by shared words, not meaning: “cheap flights” and “low-cost airfare” won’t cluster. Merge pure synonyms by hand.

Treating the output as final

Automatic clusters are a huge head start, not a finished keyword map. Sanity-check groups against search intent.

Ignoring the Unclustered group

Unmatched keywords are often unique long-tail opportunities — sometimes the easiest wins in your whole list.

FAQ

Frequently asked questions

It normalises each keyword, reduces words to their root form (so “shoes” matches “shoe”), and weights every word by how rare it is within your list. Keywords whose weighted word overlap clears your chosen sensitivity threshold are grouped together and given a descriptive label. The logic is deterministic and runs entirely in your browser — no AI service or API is involved.

No. The tool is 100% client-side: your keywords are processed by JavaScript running on your own device and are never sent anywhere. It even works offline once the page has loaded.

Up to 20,000 keywords per run. Lists over 10,000 show a heads-up because processing may take a few seconds, especially on older phones. For very large projects, split your list by topic or country and run each batch separately.

A keyword lands in Unclustered when it doesn’t share enough meaningful words with any other keyword in your list at the current sensitivity. That’s intentional — it’s better than forcing bad matches. Try the Broad setting, or treat those keywords as unique long-tail opportunities that may deserve their own pages.

No. It clusters by shared terms only, with no external data, which is what keeps it free, instant and private. For SERP-overlap clustering or volume data, pair the output with your keyword research platform — the exported CSV drops straight into a spreadsheet alongside your metrics.

Yes. Any language works because clustering is based on shared words. Word-root matching and stopword handling are optimised for English, so clusters in other languages rely on exact word matches and may be a little looser — the Broad setting usually helps.

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