Google's Search Generative Experience (SGE) — now evolved into AI Overviews — has fundamentally changed how search results work. Instead of displaying ten blue links, Google synthesises answers from multiple sources into a single AI-generated response. For Melbourne businesses, this means your SEO strategy needs to evolve beyond targeting individual keywords to clustering content around search intent.
What Is Search Intent Clustering?
Search intent clustering is the practice of grouping keywords not by topic alone, but by the underlying motivation behind the search. Instead of creating one page per keyword, you create comprehensive content hubs that address an entire cluster of related queries sharing the same intent.
There are four primary intent types, and understanding them is essential for any Melbourne business investing in content:
Informational intent: The searcher wants to learn something. "How does SEO work," "what is schema markup," "why is my website slow." These queries trigger AI Overviews most frequently because Google can synthesise a comprehensive answer.
Navigational intent: The searcher wants to find a specific website or page. "SEO Melbourne contact page," "Google Search Console login." Less affected by AI Overviews since the user already knows where they want to go.
Commercial investigation: The searcher is researching before a purchase decision. "Best SEO agencies Melbourne," "Semrush vs Ahrefs comparison," "how much does SEO cost." AI Overviews are increasingly appearing for these queries, making them a critical battleground.
Transactional intent: The searcher is ready to buy or take action. "Hire SEO consultant Melbourne," "SEO audit quote," "book SEO consultation." These queries are less affected by AI Overviews because Google recognises the user wants to interact with a business, not read an answer.
How to Build Intent Clusters (Step by Step)
Step 1 — Keyword research with intent mapping: Use Semrush, Ahrefs, or Google Keyword Planner to pull all keywords related to your core service. Then manually categorise each keyword by intent type. A Melbourne plumber might group "how to fix a leaking tap" (informational), "emergency plumber Southbank" (transactional), and "plumber vs handyman for bathroom renovation" (commercial investigation) into different clusters.
Step 2 — Create pillar content for each cluster: Build one comprehensive page that serves as the authoritative resource for each intent cluster. This page should answer the primary question and all related sub-questions. For the informational cluster above, that pillar page might be a complete guide to common plumbing issues — covering causes, DIY fixes, and when to call a professional.
Step 3 — Build supporting content: Create additional pages that go deeper on subtopics within each cluster, linking back to the pillar page. Each supporting page should target specific long-tail variations while reinforcing the pillar page's topical authority.
Step 4 — Implement internal linking: Connect all pages within a cluster using contextual internal links. This creates a clear topical hierarchy that helps Google understand the relationship between your content pieces. The pillar page links down to supporting pages; supporting pages link back up to the pillar and across to related supporting pages.
How AI Overviews Change the Strategy
AI Overviews don't just summarise one page — they synthesise information from multiple sources. This creates both a threat and an opportunity:
The threat: If your content is the sole source for an AI Overview, Google extracts your answer and users may never visit your site. This is the "zero-click" problem scaled up by AI.
The opportunity: Google's AI needs authoritative, well-structured content to build its responses. Pages that are clearly organised with headers, concise definitions, data-backed claims, and structured markup are disproportionately cited. If your content cluster is the most comprehensive and best-structured resource on a topic, Google's AI will reference your pages repeatedly — and the citation links do drive traffic.
Practical adaptation: Structure your content so that each H2 section contains a concise, self-contained answer in the first paragraph, followed by detailed supporting information. This gives Google clean extraction points for AI Overviews while providing enough depth that users click through for the full picture.
Content Structure Template for AI Overviews
- H2: Clear question or topic (matches a common query)
- First paragraph: Direct 40-60 word answer (Google extracts this)
- Supporting paragraphs: Data, examples, expert context (drives click-through)
- Internal links: Connect to related cluster content (builds topical authority)
- Schema markup: FAQ, HowTo, or Article schema for structured data signals
Measuring Cluster Performance
Traditional keyword rank tracking doesn't capture the full picture of intent cluster performance. Track these metrics instead:
Topic visibility: Use Semrush's Position Tracking or Ahrefs' Rank Tracker to monitor rankings across all keywords in a cluster simultaneously. A rising tide across the cluster — even if no single keyword hits #1 — indicates growing topical authority.
Search Console impressions by cluster: Group your Search Console data by intent cluster to see total impressions and clicks for each topic area. This reveals whether Google associates your domain with that topic.
AI Overview citations: Manually check your target queries in an incognito window to see if your content appears in AI Overviews. Tools like Semrush's SERP Features report are beginning to track AI Overview appearances, though coverage is still developing.
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Melbourne Business Case Study: Intent Clustering in Practice
Consider a Melbourne accounting firm targeting small business clients. Here's how intent clustering transforms their content strategy from scattered keyword targeting to a cohesive, AI-visible content ecosystem:
Cluster 1 — Tax return queries (Informational intent): Pillar page: "Complete Guide to Small Business Tax Returns in Australia." Supporting pages: "Tax deductions for Melbourne home office workers," "BAS lodgement deadlines 2026," "Sole trader vs company tax implications," "FBT obligations for small employers." Each supporting page links to the pillar and to related supporting content.
Cluster 2 — Hiring an accountant (Commercial investigation intent): Pillar page: "How to Choose a Small Business Accountant in Melbourne." Supporting pages: "Accountant vs bookkeeper — which do you need," "How much do accountants charge in Melbourne," "Questions to ask before hiring an accountant," "Cloud accounting software comparison for Australian businesses."
Cluster 3 — Engagement queries (Transactional intent): Service pages: "Small Business Tax Returns Melbourne," "BAS and GST Services," "Business Structure Advisory." These pages are optimised for direct conversion rather than information provision — they feature clear calls to action, pricing signals, and trust indicators.
Tools and Workflow for Building Intent Clusters
Keyword grouping tools: Semrush's Keyword Magic Tool allows you to export keyword lists and filter by intent type (it automatically classifies keywords as informational, commercial, navigational, or transactional). Ahrefs' Keywords Explorer provides similar functionality. For a free alternative, use Google Keyword Planner to pull keyword ideas, then manually classify intent based on the SERP features that appear for each query — if Google shows a knowledge panel, the intent is informational; if it shows shopping results, the intent is transactional.
Content gap analysis: Once you've mapped your intent clusters, compare your existing content against the full cluster map. Identify which clusters have strong pillar content but weak supporting pages, which clusters exist only as thin pages that need expansion, and which clusters have no content at all. Prioritise building out clusters where you already have some authority — it's faster to strengthen an existing cluster than to build one from scratch.
Internal linking audit: Use Screaming Frog's internal linking report to visualise your current link structure. Effective clusters should show a clear hub-and-spoke pattern with the pillar page receiving the most internal links within the cluster. If your internal links are scattered randomly, Google can't identify your content hierarchy — and AI Overviews can't determine which page represents your most authoritative content on each topic.
Intent Clustering Workflow (Quarterly Process)
- Week 1: Pull all target keywords from Semrush/Ahrefs, classify by intent, group into clusters
- Week 2: Audit existing content against cluster map — identify gaps and thin content
- Week 3-8: Create or expand pillar content for priority clusters (one pillar per 2 weeks)
- Week 9-12: Build supporting content for each pillar (2-3 supporting pages per cluster)
- Ongoing: Implement internal linking, monitor AI Overview citations, iterate based on Search Console data
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