How to Do Keyword Clustering: Step by Step Guide (2026)
By RankTree Team · 2026-06-10
Part of the Keyword Clustering: The Complete Guide for SEO Success guide →
Most keyword research ends at the wrong place. You have a list of 800 terms with strong keyword data and no clear answer to the most important question: which keywords belong on the same page and which ones need their own?
Keyword clustering answers that question systematically and in a way that aligns with how Google actually evaluates content.
This guide walks through the complete keyword clustering process: from building your initial keyword list to organizing clusters into a publishable content architecture.
We cover the manual method, the tool based method and the specific workflow that works best for SaaS content teams building topical authority from scratch.
This page is part of our complete Keyword Clustering Guide If you are new to the concept, start there before working through this process.
Quick Answer:
Keyword clustering is done by grouping keywords based on search intent and SERP overlap, then mapping each group to a single page. The process includes keyword collection, intent tagging, SERP comparison, clustering and content mapping.
How to Do Keyword Clustering?
To do keyword clustering, group keywords based on search intent and SERP similarity. Start by collecting keywords, then analyze which queries show similar Google results. If multiple keywords rank for the same pages, group them into one cluster and target them with a single piece of content.
Why Keyword Clustering Is a Process Not Just Grouping?
Before getting into steps understand what keyword clustering actually produces because most guides frame it too narrowly.
Grouping keywords is step three in a five step process. Treating it as the whole process leads to clusters that are technically correct but strategically useless you have organized keywords into groups with no clear picture of what to write in what order or how pages should connect.
The full keyword clustering process produces:
A set of keyword groups (clusters) where every group maps to exactly one page
A content hierarchy showing which clusters become pillar pages sub pillar pages and cluster articles
An internal link map showing how every piece of content connects to every other piece
A prioritized publishing order based on volume difficulty and business value
When you finish this process you should be able to hand it to a writer and say: "Here is what to write here is what each page should cover and here is which pages link to which." That is what keyword clustering is actually for.
Step 1: Build a Keyword List Worth Clustering
Clustering bad keywords produces bad clusters. Before grouping anything build a list that covers the full search landscape around your topic.
Minimum list size: 200 keywords. Under that your clusters will be too thin to form meaningful patterns. Most SaaS content teams work with 500 to 1500 keywords per topic area.
Start with seed keywords. Choose 3 to 5 broad terms that define your core topic. Enter each into Ahrefs Semrush or Google Keyword Planner and pull broad match and phrase match results.
Supplement with free Google sources most tools miss:
Google Autocomplete Type each seed keyword into Google without pressing enter. The dropdown suggestions are real queries with significant volume.
People Also Ask Run live Google searches and expand the PAA section. Click several questions more appear as you expand surfacing long tail queries your tools underweight.
Related Searches At the bottom of each results page eight additional related queries appear. These often include intent angles and synonym variations tools miss.
Google Search Console If your site has existing content export impressions data. Keywords ranking position 8–20 with high impressions are prime clustering candidates you already have partial relevance.
Export your list to a spreadsheet with columns for: keyword monthly volume keyword difficulty a blank "Cluster" column and a blank "Content Level" column.
Step 2: Clean & Dedupe Your Data
Before you tag intent or check SERP overlap, clean your raw export. A messy keyword list produces messy clusters and wastes hours during the review pass.
Remove near-duplicates like singular/plural or slight variations and merge their volumes. Exclude branded or irrelevant terms to avoid noise in clustering.
Normalize formatting by using lowercase, trimming spaces, and removing inconsistencies so tools don’t treat identical keywords separately.
Keep zero-volume keywords but tag them separately, as some still have real search demand.
A clean list of 500 keywords will always cluster better than a messy list of 800.
Step 3: Tag Every Keyword by Search Intent
This is the step most people skip and the step that determines whether your clusters will rank.
Google’s algorithm matches content to intent, as explained in Google Search Central documentation on helpful content and ranking systems.. A page answering an informational question will not rank for a transactional query regardless of quality. Assign one of four intent types to every keyword:
Intent | What the User Wants | Example |
Informational | To learn something | "what is keyword clustering" |
Commercial | To compare options | "best keyword clustering tool" |
Transactional | To take action | "keyword clustering tool free trial" |
To find a specific brand | "RankTree login" |
How to determine intent: Run the keyword as a live Google search. If the top five results are how articles or definitions are informational. Listicles and comparison pages commercial. Product and pricing pages transactional.
The mistake that kills clusters: grouping "best keyword clustering tool" (commercial) with "what is keyword clustering" (informational). These serve completely different users. One page cannot satisfy both intents well.
Step 4: Group Keywords by SERP Overlap
This is the core clustering step and the methodology determines output quality.
Semantic clustering groups keywords by meaning similarity. Fast but regularly wrong.
SERP based clustering checks whether Google shows the same pages for two keywords. If the top ten results for Keyword A and Keyword B share five or more of the same URLs they belong in the same cluster.
If fewer than five overlap they likely need separate pages even if the words look nearly identical.
A real example: "vaporizer parts" and "vaporizer accessories" are semantically almost identical. But their Google results share only 11% URL overlap meaning Google treats them as separate topics requiring separate pages.
A semantic tool would have combined them costing you one content opportunity.
The 5 overlap rule: Five or more shared URLs in top ten results = same cluster same page. Fewer than five = separate pages.
For lists under 200 keywords: Check manually. Open Google incognito search each keyword note the top five URLs and check overlap with related keywords. Takes 8 to 15 hours for 500 keywords.
For lists over 200 keywords: Use a SERP based clustering tool RankTree Keyword Insights or Ahrefs' Parent Topic clustering.
Always do a manual review pass on your highest volume clusters afterward. Tools miss nuance where intent is ambiguous.
Step 5: Assign Cluster Hierarchy
Once you have your keyword groups, you need to decide what type of content each group becomes.
This is where most clustering guides stop and where the most strategic work actually happens.
Not all clusters are equal. Some groups represent broad topics that should anchor an entire content section.
Others represent specific sub-topics. Others answer one narrow question. Recognizing which is which determines your entire content architecture.
The Three Content Levels
Pillar Pages target the broadest head terms with the highest search volume. They provide a high-level overview of a major topic and link down to every sub-pillar and cluster page below them.
Typical search volume: 1,000+ monthly searches
Keyword specificity: Broad, high-level
Word count: 3,000–5,000 words
Example: "Keyword Clustering" (2,980 vol)
Sub-Pillar Pages target specific sub-topics within a pillar. They go deeper than the pillar on their specific angle and link both up to the pillar and down to their cluster articles.
Typical search volume: 300–2,000 monthly searches
Keyword specificity: Mid-level, addresses one aspect of the pillar topic
Word count: 1,800–2,500 words
Example: "How to Do Keyword Clustering" (this page)
Cluster Articles answer one specific question or cover one narrow topic. They link back up to their sub-pillar and pillar.
Typical search volume: 50–500 monthly searches
Keyword specificity: Specific, long-tail
Word count: 1,200–1,800 words
Example: "How to Do Keyword Clustering in Python"
How to Assign Levels?
Use these three factors together:
Search volume higher volume generally signals a broader topic that warrants pillar or sub-pillar treatment. Low-volume specific questions are cluster articles.
Specificity how narrow is the topic? "Keyword research" is broad (pillar). "Keyword research for SaaS companies" is mid-level (sub-pillar). "How to export keyword data from Ahrefs to Google Sheets" is narrow (cluster article).
Keyword difficulty high difficulty keywords typically signal pillar-level competition where established authority already dominates. Low difficulty often signals a cluster article opportunity where you can win with targeted, specific content.
Add the content level assignment to the "Content Level" column in your spreadsheet.
Step 6: Map Internal Links Before Writing
Most teams skip this and regret it when they have 50 published pages and no record of how they connect.
Internal links are how authority flows between pages and how Google understands your site's topical structure. Map them before writing begins not as an afterthought.
The basic pattern:
Pillar Page → links DOWN to all sub pillars
Sub Pillar → links UP to pillar DOWN to clusters
Cluster → links UP to sub pillar
Add "Links To" and "Linked From" columns to your spreadsheet. Before writing begins document which existing pages will link to each new piece and which pages each new piece will link to.
This prevents two silent ranking killers: orphan pages (no internal links pointing to them receive no authority) and broken link chains (pillar links to sub pillar sub pillar never links back authority loop is incomplete).
Step 7: Prioritize Publishing Order
You cannot publish everything at once. Score each cluster on three factors (1–3 each):
Business value: 3 = direct trial/purchase intent 2 = tool awareness 1 = pure educational
Volume opportunity: 3 = 1000+ combined monthly searches 2 = 100–1000 1 = under 100
Ranking difficulty: 3 = KD under 20 2 = KD 20–50 1 = KD 50+
Priority score = Business value × Volume opportunity × Ranking difficulty
Clusters scoring 18–27 publish first. Clusters scoring under 9 publish after you have domain authority in the topic area.
One rule for new sites: Complete one pillar's full cluster set before starting the next pillar. A site with complete coverage of one topic outranks a site with partial coverage across five topics. Depth before breadth.
Validate Before Writing 4 Question Check
Run this check on every cluster before handing it to a writer:
Do all keywords share five or more overlapping URLs in Google's top ten?
Do all keywords share the same intent type?
Could one well written page realistically rank for all of them?
Does this cluster connect to a pillar or sub pillar above it in your hierarchy?
If any answer is no split the cluster. More tighter clusters consistently outperform fewer broader ones.
How RankTree Automates This Process?
For keyword lists under 200 terms the manual spreadsheet approach is workable. For SaaS content teams managing 500 to 2000+ keywords the manual workflow takes 15+ hours before a single word is written SERP overlap checks alone run 8 to 15 hours for 500 keywords.
RankTree runs SERP based overlap analysis across your full keyword list simultaneously assigns intent classifications, generates the three level content hierarchy and maps internal link relationships all from a single CSV upload.
What takes 15+ manual hours finishes in under 5 minutes with the complete content architecture ready for your editorial team.
Track Performance After Publishing
Publishing is the beginning not the end. Monitor clusters in Google Search Console:
Rising impressions low clicks → Title tag or meta description problem not content
Consistent position 8–20 → Content needs more depth or stronger internal links
Strong position low volume → Expand the cluster with more long tail cluster articles
Re cluster every six months and immediately after any major Google core update. You may also read the Google core update. Search intent shifts over time clusters correct today may need splitting or merging after algorithm changes.
Once your keywords are clustered the next step is turning those clusters into an actual site structure folders hub pages and internal linking rules. See How to Group Keywords into Content Silos for the full walkthrough.
Final Word
Done correctly keyword clustering produces a complete content blueprint what to write how pages connect and in what order to publish.
The seven step process here takes longer than a simple grouping approach. It also produces content architecture that Google can understand and reward.
Start with one pillar topic. Complete all steps. Publish the full cluster before moving to the next topic. Then repeat.
FAQs
How many keywords should be in one cluster?
5 to 25 keywords. Fewer than 5 is usually too narrow for a dedicated page. More than 25 almost always means the cluster needs splitting.
Should I cluster before or after keyword research is complete?
After. Clustering a partial list produces clusters that need reorganizing when new keywords are added. Complete your research for a topic area first.
How often should I re cluster?
Every six months as standard and immediately after major Google core updates.
What is the difference between keyword clustering and topic clusters?
Keyword clustering is the research process organizing search terms by intent and SERP overlap. Topic clusters are the published content structure built from that research. One is the input the other is the output.