Keyword Clustering: How to Group Keywords Into Content
Keyword Clustering: How to Group Keywords Into Content
Keyword clustering is grouping search queries by shared intent so one page can rank for many of them. The two methods are SERP-based clustering (queries share the same page in Google's top 10) and semantic clustering (queries share embedding similarity). SERP-based is more accurate for ranking decisions; semantic is faster and better for brainstorming.
Keyword clustering groups semantically similar queries so one page ranks for many. SERP-based vs semantic methods — LemRank.
Frequently asked questions
How many keywords should one cluster have?
5–30 is typical. Fewer than 5 and clustering saves little; more than 30 and intent usually starts to split.
What threshold should I use for semantic similarity?
0.75 cosine similarity is a common starting point. Higher (0.80+) creates tighter clusters; lower (0.65) broader.
Do I need to cluster if I use a keyword tool that provides parent topics?
Parent topics are a rough form of clustering. Verify with SERP overlap before committing content decisions.
How often should I re-cluster?
Quarterly for active projects. SERPs shift enough over three months that some clusters merge or split.
Can clustering fix existing cannibalization?
It surfaces the problem, but the fix is content consolidation. See the [cannibalization fix playbook](/help/how-to-fix-keyword-cannibalization).