Keyword Clustering: How to Group Keywords Into Pages (Free Tool)

Published: 23 October 2026 | Last updated: 23 October 2026 | 18 min read

By Graeme Whiles

You've just finished your keyword research.

There are 600 rows in the spreadsheet, and every one of them looks like a page you could write.

'Keyword clustering'. 'What is keyword clustering'. 'How to do keyword clustering'. 'Keyword clustering SEO'.

Four keywords. Four briefs. Four articles.

However, Google doesn't see four topics there.

When I checked the US results in Ahrefs, each of the three longer searches shared three or four of its top 10 organic results with 'keyword clustering' itself. One page can rank for the lot. Four pages would end up competing with each other.

That's the problem keyword clustering solves.

In this guide, I'll show you what keyword clustering is, the three ways tools do it, the six-step process I use to turn a keyword list into a content plan, and a free keyword clustering tool you can run in your browser right now.

Short on time? Here are the key takeaways

• Keyword clustering groups keywords that one page can rank for: the output is a list of pages to build, each with a target keyword and the supporting keywords it should also rank for.
• The search results decide, not the words: two keywords belong together when Google already ranks the same pages for both. 'Keyword grouping' and 'keyword clustering' look like twins, and they share none of their top 10 results.
• Use the three-URL rule: if two keywords share three or more of their top 10 organic URLs, they go on one page. Two or fewer, and they get their own.
• Start free, then check the SERP: the free tool below does a fast first pass by shared words. The SERP check turns that draft into a plan.
• One cluster, one URL: map every cluster to a page before anyone writes a word, and keyword cannibalisation never gets started.

What is keyword clustering?

First, let me explain what I mean by 'keyword clustering', because it gets mixed up with topic clusters, keyword grouping and content clusters.

Keyword clustering is the process of grouping keywords that share the same search intent, so you can target each group with one page instead of one page per keyword. Each cluster becomes a page in your content plan: one target keyword, plus the supporting keywords that page should also rank for.

The reason it works is simple.

Pages that rank well rarely rank for just one keyword, because people phrase the same question in lots of different ways.

Ahrefs builds a whole metric on that idea. Its Parent Topic takes the #1 ranking page for a keyword and finds the query sending that page the most search traffic.

Keyword clustering just makes the same idea explicit before you write.

Keyword clustering vs keyword grouping vs topic clusters

These three terms get used as if they mean the same thing.

They don't.

• Keyword cluster: a group of keywords that one page should target. It's the smallest unit, and it answers 'what goes on this page?'
• Topic cluster: a group of pages. A pillar page covers a broad topic and links to cluster pages that each go deep on one part of it. It answers 'how do these pages fit together?' My guide to content cluster strategy covers how to build one.
• Keyword grouping: the older name for organising a keyword list, often by shared words rather than shared results. Wikipedia's history of keyword clustering describes lemma-based grouping (matching words by their dictionary form) coming before SERP-based clustering.

Here's the part that surprised me.

'Keyword grouping' gets 2,400 searches a month in the US, according to Ahrefs.

That's more than 'keyword clustering' at 1,600, so you'd assume one page could target both.

It can't.

On 23 October 2026, the top 10 organic results for the two terms in the US had zero URLs in common.

Google treats them as different questions, and so should your content plan.

The two ideas work together.

Keyword clusters tell you which pages to build. Topic clusters tell you how to connect them, and that's what builds topical authority over time.

Why keyword clustering matters

Keyword clustering isn't admin.

It's the step that decides how many pages you build, and whether those pages help or hurt each other.

• Fewer, stronger pages: one page per cluster instead of one per keyword, so a list of hundreds of keywords becomes a list of pages you can actually build.
• No cannibalisation by design: when two pages target the same intent, they compete for the same results. Clustering first means every intent has one owner. My guide to keyword cannibalisation covers what happens when you skip this.
• Better briefs: each cluster hands a writer the target keyword, the questions to answer and the variations to cover.
• Cleaner internal linking: clusters show which pages belong together, which is the starting point for any internal linking strategy.
• Honest forecasts: you can add up a cluster's search volume and forecast one page, rather than counting the same traffic three times across three pages.

There's an AI search angle too, which I'll come back to below.

Free keyword clustering tool

I built this tool for the first pass I'd otherwise do by hand in a spreadsheet.

Paste your keywords, with search volume if you have it, and it groups the keywords that share the same core words. It picks the highest-volume keyword in each group as the target, keeps keywords with intent modifiers such as 'tool', 'best' or 'examples' in their own groups, and gives you a CSV.

It runs entirely in your browser.

No sign-up, no API key and nothing sent anywhere.

Press 'Load example' to try it with 33 real keywords from the research behind this page.

How the tool works

The tool is lexical, which means it compares words, not search results.

• It cleans each keyword: filler words like 'what', 'is', 'how' and 'to' are ignored, so 'what is keyword clustering' and 'keyword clustering' match.
• It reduces words to a stem: 'clusters', 'clustering' and 'clustered' all become 'cluster'. British and American spellings match too, so 'optimisation' and 'optimization' land in the same group.
• It scores the overlap: shared words divided by all the distinct words in both keywords. 'Keyword clustering' and 'keyword clustering SEO' share two of three words, a score of 0.67.
• It applies your settings: Loose groups keywords that score 0.4 or more, Balanced 0.55 and Tight 0.75. Soft compares each keyword with the group's main keyword, while Hard makes it match every keyword already in the group.
• It keeps intent apart: with the modifier setting on, 'keyword clustering tool' can't join 'keyword clustering', because one searcher wants a tool and the other wants an explanation.

The Soft and Hard settings borrow their names from SERP clustering tools, which I'll explain in a moment.

What the tool can't do

I'll be straight with you.

This tool can't see Google, so it can't tell you whether two keywords really belong on one page.

It only knows whether they look alike.

That's a real limitation.

Keyword Insights tested 17 clustering tools and found SERP-based tools scored 70 to 95 out of 100, while pattern-matching tools scored 11 to 35.

That's a vendor running its own test, and its own tool came top, so read it with that in mind.

The direction still matches what I see in client work.

The good news?

You don't need a paid tool to close the gap.

You need the SERP check in step four, which you can do by hand for any group you're unsure of.

Use the tool to get from hundreds of rows to a short list of candidate groups in seconds.

Then let the search results make the final call.

The three types of keyword clustering

Every clustering tool uses one of three methods, or a mix of them.

The method matters more than the brand.

SERP-based clustering is the oldest automated method, not the newest.

Wikipedia credits the term and its first principles to Russian SEO expert Alexey Chekushin in 2015, the same year the SERP-based tool Just-Magic launched in Russia.

The idea hasn't changed since.

Search each keyword, pull the top 10 results, and group the keywords whose results overlap enough. That minimum overlap is called the clustering level. In SE Ranking's Keyword Grouper, it's an accuracy setting from 1 to 9 matching URLs.

Soft, moderate and hard clustering

SERP tools also let you choose how strictly every keyword in a group has to match.

• Soft: each keyword only has to match the group's highest-volume keyword. You get bigger groups and fewer leftovers, but two keywords in the same group might not match each other.
• Moderate: each keyword has to match at least one other keyword in the group, but not necessarily the main one.
• Hard: every keyword has to match every other keyword. You get smaller, tighter groups and more keywords left over.

SE Ranking's guide recommends soft clustering for a general view of a niche, and hard clustering when you need to separate lots of different search intents.

I start with soft when I'm planning content for a new site.

I switch to hard when I'm mapping keywords onto pages that already exist, because a wrong merge there means rewriting a live page.

How to do keyword clustering in six steps

This is the process I use for client content plans.

The free tool covers step three.

Steps four to six are where the judgement comes in.

1. Build one master keyword list

Clustering is only as good as the list you feed it.

I pull from four places.

• Keyword tools: Ahrefs Keywords Explorer or Semrush's Keyword Magic Tool, starting from your main topics.
• Google Search Console: the queries you already get impressions for, which show how Google sees your site today.
• Competitor gaps: the keywords your competitors rank for and you don't. My guide to content gap analysis walks through how to find them.
• Real questions: People Also Ask boxes, Reddit threads and sales calls, for the phrasing a keyword tool won't show you.

Keep the search volume column.

It decides which keyword leads each cluster later.

2. Clean the list before you cluster it

A messy list produces messy clusters.

• Remove duplicates: including close variants that only differ by capital letters or spacing.
• Remove what you'll never target: competitor brand names, locations you don't serve and products you don't sell.
• Split by market and language: SE Ranking recommends grouping each language separately, and UK and US results differ too, so cluster each market's list on its own.

3. Run a first-pass grouping

Paste the cleaned list into the tool above, or into any clustering tool you already pay for.

I start with Soft and Balanced, with intent modifiers kept apart.

Then I scan the output for two things.

• Groups that are too big: a group that mixes 'how to' searches with product searches needs splitting, so try Hard or Tight.
• Leftovers that look related: if obvious matches sit in 'didn't fit a group', try Loose, or add synonyms for words your audience uses interchangeably.

The output is a draft, not a plan.

4. Run the SERP check

This is the step most guides skip, and it's the one that matters.

For any group you're unsure of, search the main keyword and the doubtful keyword in a private browser window, set to the right country. Compare the top 10 organic results, and ignore the ads, AI Overviews, People Also Ask boxes and videos.

Then count the URLs that appear in both.

I call this the three-URL rule: if two keywords share three or more of their top 10 organic URLs, they belong on one page.

Two or fewer, and they get their own.

Three isn't a magic number. It's the example SE Ranking uses to explain its accuracy setting, and it's where the line usually sits for the informational topics I work on. For commercial keywords, where the same big sites tend to rank for everything, I raise it to four or five.

Here's the check I ran for this page, using Ahrefs' SERP overview for the US on 23 October 2026.

• What is keyword clustering: 4 shared URLs, so it goes on the same page.
• How to do keyword clustering: 4 shared URLs, same page.
• Keyword clustering SEO: 3 shared URLs, same page.
• Keyword clustering tool: 2 shared URLs (ryrob.com and explodingtopics.com), so it needs its own page.
• Keyword grouping: 0 shared URLs, its own page.

The free tool got all five right on its default settings.

The catch? It kept 'keyword grouping' apart only because the words are different. If I'd told it 'grouping' and 'clustering' were synonyms, it would have merged them, and the search results say that would have been a mistake.

5. Pick the target keyword and page type

Every cluster needs one target keyword. It goes in the title, the H1 and the URL, and the rest of the cluster shapes the headings and FAQs.

The default is the highest-volume keyword in the group.

That's what the free tool picks, and it's how SE Ranking names its groups too.

However, the biggest keyword isn't always the best target.

Take this page.

In the example list, 'cluster keyword' has the most searches at 1,800 a month. Ahrefs gives the same Parent Topic, 'keyword clusters', to both 'cluster keyword' and 'keyword clustering', so volume alone doesn't settle it.

I went with 'keyword clustering'. It names the process people are trying to learn, and Ahrefs gives it a higher traffic potential (1,400 a month) than 'cluster keyword' (1,000).

Then look at what's ranking to choose the page type.

A SERP full of guides needs a guide. A SERP full of tools and lists needs a tool or a list, however good your guide is.

6. Map every cluster to one URL

Before anyone writes a word, give every cluster a home.

• One existing page fits: update it with the cluster's missing keywords and questions rather than building a new page.
• Two existing pages fit: you've found cannibalisation. Merge them or re-target one. If you have Search Console data paired by query and URL, my free keyword cannibalisation checker scores each conflict and suggests which page should win.
• No page fits: it goes into the content plan, with a brief built from the cluster. My guide on how to write a content brief covers what to include.

The result is a keyword map: one row per cluster, and one URL per row.

It's the document that stops your site competing with itself.

A keyword clustering example

Here's what the free tool did with the 33-keyword example list on its default settings, and what each group became in my plan.

• Cluster keyword (8 keywords, 6,750 searches a month): the guide you're reading, targeting 'keyword clustering' for the reasons in step five. 'What is keyword clustering', 'how to do keyword clustering' and 'keyword clustering SEO' all sit here.
• Keyword clustering tools (5 keywords, 4,200 searches a month): a separate page. The SERP is lists and tools, and 'keyword clustering tool' fails the three-URL rule against the guide.
• What is a topic cluster (4 keywords, 4,200 searches a month): already covered by my content cluster strategy guide, so the job is updating that page, not writing a new one.
• Keyword grouping and keyword grouping software (2 groups, 4,100 searches a month): a different topic in Google's eyes, because 'keyword grouping' shares none of its top 10 results with 'keyword clustering'.
• Pillar pages, examples and templates (3 groups): future pages inside the topic cluster, not part of this guide.
• Keyword clustering in Python (2 keywords): a developer audience with different needs, so it stays out of this plan for now.
• Two leftovers: 'topic cluster content strategy' belongs with the content cluster strategy guide, and 'keyword clustering examples' became a section of this guide instead. You're reading it.

Thirty-three keywords became one page to write now, one page to update and a short list of future pages.

That's the point of clustering.

It turns a list of searches into a list of decisions.

Keyword clustering tools worth knowing

If you cluster keywords every month, a SERP-based tool will save you hours.

These are the ones I'd look at, and what each actually does.

• Ahrefs Keywords Explorer: groups any keyword report by Parent Topic, so keywords whose top-ranking page shares the same main query sit together. Ahrefs says this needs a Standard plan or higher.
• Semrush Keyword Strategy Builder: turns up to five seed keywords into topics and clusters, analysing up to 10,000 keywords and suggesting pillar pages and subpages. It needs a paid SEO Toolkit plan, with 10 structuring actions a month on Pro, 30 on Guru and 50 on Business.
• SE Ranking Keyword Grouper: SERP-based, with soft and hard methods and the 1 to 9 accuracy setting.
• Keyword Insights: SERP-based clustering with a content workflow built around the clusters.
• Keyword Cupid: SERP-based clustering for a list you already have. LowFruits' review notes that it doesn't do the initial keyword research itself.
• The free tool on this page: lexical, instant and private. Best for a first pass, or for lists too small to justify paying for SERP credits.

What about ChatGPT?

It'll group a keyword list in seconds, but it groups by meaning, not by what Google ranks. In Keyword Insights' test, ChatGPT scored 47 out of 100. That's fine for brainstorming, not for a content plan.

If you want more free tools like this one, they're all on my free SEO tools page.

Keyword clustering and AI search

Clustering matters more now that AI answers sit above the results, not less.

Google's guide to AI features and your website says AI Overviews and AI Mode may use a 'query fan-out' technique, running several related searches across subtopics to build one response.

In my view, a page that covers a whole cluster, with each sub-question answered clearly, gives those searches more reasons to land on it.

The same topic spread across four thin pages does the opposite.

I wouldn't change how you cluster for AI search.

I'd make sure each cluster page answers its supporting questions directly, in their own sections, so both Google and AI tools can lift the answer cleanly. My guide to answer engine optimisation covers the formatting side.

Common keyword clustering mistakes

• Clustering by words alone: keywords that look alike can need different pages, as 'keyword grouping' shows.
• Ignoring intent modifiers: 'best', 'tool', 'pricing' and 'examples' usually change the page type, even when the topic stays the same.
• Mixing markets: clustering UK and US keywords together when their search results differ.
• Building a page per cluster without checking what exists: the fastest route to cannibalisation.
• Treating clusters as permanent: search results move, so re-check your biggest clusters when rankings stall.
• Chasing every leftover: a keyword that fits no group isn't automatically a page. Some are sections on a bigger page, and some aren't worth targeting at all.

Final Thoughts

Keyword clustering is the step between keyword research and a content plan.

Skip it, and you write four pages where one would rank.

Build one clean list. Run a first pass with the free tool. Check the doubtful groups against the search results with the three-URL rule, then give every cluster one target keyword and one URL.

The content plans that win aren't the ones with the most pages. They're the ones where every page has a job no other page is doing.

If you'd like help turning a keyword list into a content plan that ranks, that's part of my SEO consulting work, and my monthly SEO retainer keeps the plan moving month to month.

Get in touch, or email me directly.

Author Bio

Graeme Whiles is an independent SEO and AEO consultant at GWContent. He has worked with enterprise and SaaS brands, including Originality.ai, Connecteam, 6sense, Practice Better, and Peppr, growing organic traffic and AI search visibility across some of the most competitive categories in B2B. He also built Three Putt Golf Clothing from a blank domain as a live proof of concept for his methodology.

Keyword Clustering Frequently Asked Questions

What is keyword clustering?

Keyword clustering is the process of grouping keywords with the same search intent so one page can target the whole group. Each cluster gets one target keyword, usually the highest-volume one, plus supporting keywords that shape the page's headings and FAQs. The best clusters are confirmed by checking that Google already ranks the same pages for each keyword.

What is an example of a keyword cluster?

'Keyword clustering', 'what is keyword clustering', 'how to do keyword clustering' and 'keyword clustering SEO' form one cluster. In the US, each of the longer searches shares three or four of its top 10 organic results with 'keyword clustering'. 'Keyword clustering tool' doesn't belong, because it shares only two and Google shows tools and lists for it.

How do you do keyword clustering?

Build one master keyword list, clean it, and run a first-pass grouping with a clustering tool. Then check any doubtful groups against the search results: if two keywords share three or more of their top 10 organic URLs, they go on one page. Finally, pick a target keyword for each cluster and map every cluster to one URL.

What is the difference between keyword clustering and topic clusters?

A keyword cluster is a group of keywords that one page targets. A topic cluster is a group of pages: a pillar page on a broad topic, linked to cluster pages that each cover one part of it in depth. Keyword clustering tells you which pages to build, and topic clusters tell you how to connect them.

How many keywords should be in a keyword cluster?

There's no fixed number. A cluster holds every keyword that shares search intent and enough top-ranking results with the main keyword, which might be two keywords or fifty. If a cluster mixes different page types, such as guides and tools, it's too broad and should be split.

What is the best free keyword clustering tool?

For a quick first pass, a lexical tool like the free GWContent keyword clustering tool groups keywords by shared words instantly, in your browser. For final decisions, SERP-based clustering is more accurate, and you can do it for free by hand by comparing the top 10 results for any keywords you're unsure of.

Can ChatGPT cluster keywords?

Yes, ChatGPT can group a keyword list by meaning in seconds, but it can't see which pages Google ranks for each keyword. In Keyword Insights' test of 17 clustering tools, ChatGPT scored 47 out of 100, behind the SERP-based tools. Use it for brainstorming, then confirm clusters against the search results.

What are the four types of keywords?

Keywords are usually sorted by search intent into four types: informational (looking for an answer), navigational (looking for a specific site), commercial (researching options before buying) and transactional (ready to act or buy). Keywords with different intents rarely belong in the same cluster, even when they share most of their words.