Turn a keyword list into a pillar-and-spoke plan.
Paste your keywords and get clean topic clusters, plus the pillar page and supporting spokes for each one. Free, no login, and it runs entirely in your browser.
You have the map. Now check it against reality.
A cluster is a guess until you know which of those keywords you already rank for.
Murkuz connects your Google Search Console to Claude or ChatGPT, read-only, so you can paste a cluster into the chat and ask which of those terms already bring you impressions, which page is answering them, and which ones sit just off page one. Search_Analytics returns the rows and Keyword_Rankings returns the positions, both from your own property. The pillar you pick stops being a guess.
What is keyword clustering?
Keyword clustering groups a long list of related search terms into tight topic groups. Instead of writing a separate thin page for every keyword variation and watching them compete with each other, you target each cluster with one strong pillar page and a set of supporting spoke articles. It is the fastest way to turn a raw keyword export into an actual content plan.
Semantic vs lexical vs SERP-overlap clustering
There are three common ways to cluster keywords, and each has a trade-off:
- Lexical (what this tool does): groups keywords by shared words. It is instant, private, and needs no API. Great for a fast first pass on a list you already have.
- Semantic: uses embeddings to group by meaning, so "car" and "automobile" land together even without shared words. More accurate, but needs a model call.
- SERP-overlap: groups keywords that return the same URLs in Google. This is the most intent-accurate method because it uses Google's own judgment, but it needs live SERP data for every keyword. Murkuz can fetch that snapshot per keyword for your agent, one keyword at a time.
How to turn clusters into a pillar-and-spoke plan
- Pick the broadest, highest-volume term in each cluster as the pillar page keyword.
- Make each remaining keyword a spoke article that targets one specific angle.
- Link every spoke up to the pillar, and link the pillar down to each spoke.
- Publish the pillar first, then the spokes, so the hub has something to point to.
Keyword cannibalization and how clustering fixes it
When several of your pages chase the same keyword, Google cannot decide which one to rank, and they split each other's authority. Clustering surfaces these overlaps immediately: any keywords that land in the same cluster should be consolidated onto one page or clearly differentiated as a pillar plus distinct spokes. Fixing cannibalization is one of the highest-ROI SEO moves, and it starts with a clean cluster.
Frequently asked questions
What is keyword clustering?+
Keyword clustering is the process of grouping a list of related keywords into tight topic groups so you can target each group with one strong page instead of many thin, competing pages. Each cluster becomes a pillar page plus a set of supporting spoke articles that link back to it.
How does this keyword clustering tool group keywords?+
This tool clusters by shared meaningful terms (lexical overlap). It strips stop words, compares the token overlap between every keyword, and greedily groups keywords that share a strong core. It runs entirely in your browser, so nothing is uploaded and results are instant. Search-intent clustering needs live SERP data for every keyword, which this tool does not fetch. Murkuz can pull a SERP snapshot per keyword for your agent, but the grouping is then your agent's work, not a Murkuz feature.
Is this keyword clustering tool free?+
Yes. It is completely free, needs no login, no email, and no credits. Paste your list, click Cluster, and get your pillar-and-spoke plan. You can also export the clusters to CSV.
What is a pillar-and-spoke content structure?+
A pillar page is a broad hub article that targets the main topic. Spoke articles are narrower pages that each target a specific sub-topic and link back to the pillar. This structure helps search engines understand your site architecture and distributes authority across related content. This tool suggests the pillar target keyword and the spokes for each cluster automatically.
How does keyword clustering fix keyword cannibalization?+
Cannibalization happens when several of your pages compete for the same query, so Google cannot decide which to rank. Clustering surfaces those overlaps: keywords that belong in one cluster should live on one page (or a pillar plus clearly differentiated spokes), not spread across duplicates. Consolidating them removes the internal competition.
How many keywords can I cluster at once?+
You can paste a large list (thousands of lines) since the clustering runs locally in your browser. Very large lists may take a moment to process. There is no artificial cap and no paywall.
You clustered the keywords. Now see which ones you own.
Murkuz puts your own Google Search Console rows inside Claude or ChatGPT, read-only, so you can ask which keywords in a cluster already earn impressions, which page ranks for them, and which sit just off page one. Search_Analytics and Keyword_Rankings answer, with the property and the date window attached.
Free tool, no login. Murkuz is the connected version: your own search data, answered inside Claude.