Clustering groups related keywords together so each blog article targets one clear topic. No more three posts competing for the same search.
Writing one article per keyword instead of one article per topic is how sites end up competing with themselves in search results. Clustering groups related keywords together first, so your content plan targets topics, not just terms.
Clusters show which keywords belong together in a single article and which deserve their own. That's the difference between a content plan and a keyword pile.
When related keywords are covered by one strong article instead of several weak ones, your pages stop competing against each other in search results.
Generate an article directly from a cluster, so the main keyword and its supporting terms are handled together.
Clustering takes your full keyword list, groups it by topic, and hands each group back as a candidate for a single well-targeted article.
Run clustering on your full project list or a selection.
Related keywords are grouped by topic, each cluster a candidate for one article.
Send a cluster to article generation and cover the topic in one well-targeted post.
One article per topic. Cannibalisation avoided. Straight into generation.
Keywords that mean the same thing are grouped, so you write once instead of three times.
Two of your own pages stop competing for the same search, which is the most common self inflicted SEO problem.
A cluster becomes a brief and then an article without an export step.
Keywords that mean the same thing are grouped, so you write once instead of three times.
Two of your own pages stop competing for the same search, which is the most common self inflicted SEO problem.
A cluster becomes a brief and then an article without an export step.
No overlap, Sized to write and Reorderable.
It's grouping keywords that mean roughly the same thing or belong to the same topic, so you write one article that covers the group instead of scattering the topic across posts.
Search engines reward pages that cover a topic well. Clustering also prevents cannibalization, where several of your own pages compete for the same query and all rank worse for it.
Keywords are analyzed for semantic similarity and grouped automatically. You review the result and can adjust before acting on it.
Yes, directly. The cluster's keywords inform the article so the main term and supporting terms are covered together.
You can re-run clustering after imports, and new keywords are grouped into the structure.
Most useful from a few dozen keywords up, but even small lists benefit from seeing which terms belong in the same article.
Most questions about clustering come down to what it actually does and how it prevents keyword cannibalization. Here are the ones we hear most.