How to Cluster Keywords Using Google Search Console (Step-by-Step)

This guide walks through how to cluster GSC keywords effectively.

Export Queries From Search Console

Start by exporting:

Queries

Impressions

Clicks

Avg. position

This data reflects how your site actually performs, not estimates.

Clean & Prepare the Data

Before clustering:

Remove branded queries (optional)
Group similar variations
Identify local modifiers

This prevents noise in clustering results.

Group Queries by Search Intent

The goal is not grouping similar words — it's grouping shared intent.

Ask:

→Would one page satisfy these queries?
→Do they represent the same user goal?

Each intent should map to one primary page, not multiple supporting pages.

Identify Page Conflicts, Cannibalisation & Gaps

Look for:

Multiple pages ranking for the same cluster
Queries with impressions but weak clicks
Clusters with no dedicated page

These are optimisation opportunities.

Map Clusters to Existing URLs

Once queries are clustered by intent, mapping them back to the URLs they currently rank for helps identify:

Cannibalisation — multiple URLs competing for the same intent
Weak pages — candidates for consolidation or improvement
Content gaps — clusters with no dedicated page

This step transforms clustering from a keyword exercise into actionable page-level recommendations. In practice, this often means merging multiple intent-aligned clusters into a single, stronger page — reducing thin content and improving topical authority.

Prioritise Quick Wins

Focus first on:

Queries ranking positions 4–15
High impressions + low CTR
Strong local intent

Manual vs Automated GSC Clustering

Manual GSC clustering works for small datasets but becomes difficult at scale. See our article on semantic vs traditional clustering methods for a full comparison.

Automated tools help by:

Applying semantic logic
Prioritising opportunities
Generating content briefs

See how clustered GSC data turns into clear page decisions

See Example Output