Cluster your keywords by topic in seconds
Paste up to 500 keywords and instantly group them into topical clusters. Detect search intent, find content opportunities, and plan your SEO strategy.
Why keyword clustering matters for SEO
Publishing one page per keyword is outdated. Modern SEO requires grouping semantically related keywords into clusters and creating comprehensive content that covers the entire topic. This approach builds topical authority faster and ranks for more keywords per page.
Rank for more keywords per page
A single well-structured article can rank for dozens of related keywords when they share the same search intent. Clustering reveals which keywords belong together.
Build topical authority
Search engines reward websites that demonstrate comprehensive expertise on a topic. Keyword clusters help you map out complete content strategies that cover every angle.
Avoid keyword cannibalization
Without clustering, you risk creating multiple pages targeting the same intent — confusing search engines about which page to rank. Clusters prevent this by grouping overlapping keywords.
How our keyword clustering algorithm works
Our tool uses semantic similarity analysis to group keywords that share common topics, modifiers, and search intent — so you can create content strategies based on data, not guesswork.
Tokenization and normalization
Each keyword is broken into meaningful tokens, with stop words removed and terms normalized. This ensures 'best AI writer' and 'top AI writing tool' are recognized as related.
Semantic similarity scoring
Keywords are compared pairwise using cosine similarity on their token sets. Keywords sharing core terms above our threshold are grouped into the same cluster.
Search intent classification
Each cluster is analyzed for intent signals — transactional (buy, pricing), commercial (best, review), navigational (login, app), or informational (how, guide, what).
Cluster naming and ranking
Clusters are automatically named based on the most frequent meaningful terms and ranked by size, helping you prioritize high-opportunity topic areas first.
From keyword clusters to published articles — automatically
UnlimitedVisitors takes your keyword clusters and generates complete, SEO-optimized articles for each one. Schema markup, internal linking, and AI-readiness built in.
Frequently asked questions
What is keyword clustering?
Keyword clustering is the process of grouping semantically related keywords together based on shared topics and search intent. Instead of creating one page per keyword, you create one comprehensive page per cluster — which ranks for more keywords and builds topical authority faster.
Is this keyword clustering tool free?
Yes, 100% free with no signup required. You can cluster up to 500 keywords at once. There are no daily limits or hidden restrictions.
How many keywords can I cluster at once?
You can paste up to 500 keywords per batch. For larger keyword lists, simply run the tool multiple times. Most SEO campaigns work with 100-300 keywords per topic area.
What is search intent detection?
Search intent is the goal behind a search query. Our tool classifies each cluster as informational (learning), commercial (comparing), transactional (buying), or navigational (finding a specific page). This helps you match content format to user expectations.
How do I use keyword clusters for content planning?
Each cluster represents one content piece. Informational clusters become blog posts or guides. Commercial clusters become comparison pages or reviews. Transactional clusters become product or landing pages. Create a content calendar with one piece per cluster.
Does keyword clustering help with AI search optimization?
Yes. AI search engines like ChatGPT and Perplexity prefer comprehensive content that covers a topic thoroughly. Keyword clustering ensures your content addresses all related subtopics, making it more likely to be cited in AI-generated answers.
What's the difference between keyword grouping and clustering?
Keyword grouping is manual — you sort keywords by hand. Keyword clustering uses algorithms to automatically detect semantic relationships between keywords. Clustering is faster, more accurate, and scales to hundreds of keywords that would be impractical to group manually.