What are topic clusters?

They’re groups of related content organized around a pillar page, with supporting articles that cover subtopics and link together to signal depth and authority.

How do I build topic clusters with AI?

Use AI to group keywords by intent and entity, then have humans refine clusters, assign pillars/support pages, and create briefs with shared schema and linking plans.

How do I structure internal links in a cluster?

Link supports to the pillar and to relevant siblings using clear anchors; ensure the pillar links back out to key supports to reinforce the hub-and-spoke model.

What mistakes should I avoid?

Over-fragmenting clusters, forcing unnatural anchors, ignoring search intent differences, and publishing without E-E-A-T or schema to support your claims.

How do I measure cluster performance?

Track rankings and traffic at the cluster level, AI Overview/assistant citations for pillar/support pages, engagement, and conversions tied to the cluster’s user journey.

How often should I update clusters?

Quarterly—add new subtopics, merge or retire weak content, refresh stats and sources, and adjust linking as intent and SERPs evolve.

Do topic clusters help AI search?

Yes—clear topical coverage and links help AI systems understand your expertise footprint, increasing the likelihood of citations in AI answers and overviews.

How can I localize clusters?

Build parallel clusters per locale, localize keywords and examples, align schema with local data, and monitor AI/organic performance separately in each market.

Topic Clusters 2025: Step-by-Step Guide & Templates

Topic clusters give Google and AI assistants a clear map of what you know and sell.

Without them, content drifts, links break, and AI answers cite competitors.

This playbook shows you how to research, architect, write, and measure clusters built for AI Overviews, Perplexity, and SERPs.

You get entity-first planning, schema rules, internal linking blueprints, and KPIs tied to revenue.

Use it with our semantic strategy pillar at Semantic SEO that Scales: Entity-Led Strategy & KPIs and structured data pillar at Structured Data: The Complete Guide for SEO & AI.

What a topic cluster is (practical definition)

A topic cluster is a pillar page covering a core subject plus interlinked support pages that answer related questions and intents.

Each page is tied to explicit entities (@id), consistent schema, and a link structure that guides both users and crawlers.

Clusters serve awareness, consideration, and decision intents and connect to commercial CTAs.

Why clusters matter in AI search

Entity clarity: repeated @id anchors reduce ambiguity for assistants.
Answer density: supports cover granular intents, making citations more likely.
Link pathways: hubs and spokes help crawlers and LLMs find relevant answers fast.
Conversion: mapped CTAs lead readers from information to action.

Research: find topics and intents

Pull queries from Search Console, PAA, AI answers, sales calls, and support tickets.
Cluster with AI, then human-refine by intent: define, compare, how-to, troubleshooting, pricing/ROI.
Map entities per cluster: primary concept, related products/services, audiences, locations, authors.
Prioritize clusters tied to revenue, risk (YMYL), or strategic differentiation.

Architecture: pillars, supports, and links

Pillar: definitive guide to the topic; defines entities, frames use cases, links to all supports.
Supports: deep dives (how-to, checklist, comparison, objections, case study, FAQ, glossary terms).
Internal links: supports link back to pillar and to relevant siblings; pillar links to all supports; commercial pages linked where intent shifts.
Navigation: breadcrumbs mirror hierarchy; related modules surface siblings by entity.
Depth: keep supports within three clicks of home; avoid orphaned pages.

Entity and schema planning

ID map: create @id for Organization, products/services, authors, locations, and the core concept.
Schema: Pillar/Article with about/mentions; FAQ/HowTo on supports where eligible; Product/Service on commercial pages; BreadcrumbList on all.
Consistency: reuse IDs across cluster; align schema text with on-page definitions; add publisher/author.
Localization: one @id across locales; translate text and use inLanguage and hreflang.

Content briefs that enforce structure

Include in every brief:

Primary and supporting entities with IDs.
Intent and stage; target persona.
Required questions to answer in first 150 words; PAA/AI prompts.
E-E-A-T requirements: credentials, reviewers, sources.
Internal link targets (pillar, siblings, product/service, case study).
Schema type and about/mentions list.
Media: diagrams/tables for specs or steps.

Writing guidelines for cluster pages

Answer-first intros; define the entity/topic immediately.
Short paragraphs, scannable bullets, descriptive headings.
Use examples, scenarios, and data; cite sources.
Add FAQs and HowTo steps where relevant; keep on-page Q&A visible.
Keep tone direct and clear; avoid fluff and jargon.

Internal linking blueprint

Pillar ↔ supports: reciprocal links high on page; ensure no support is hidden.
Sibling links: connect related supports (e.g., "keyword clustering" ↔ "internal linking strategy").
Commercial ties: link supports to product/service pages with intent-aligned anchors.
Navigation aids: breadcrumbs, related content modules, and in-line contextual links using entity-rich anchor text.
Periodic crawl: monthly check for broken/redirected links and orphaned supports.

Structured data checklist per cluster

Article/BlogPosting: headline, author Person, publisher Organization, datePublished/dateModified, image, about/mentions, BreadcrumbList.
FAQ/HowTo: questions/steps visible; match schema; add images for steps when helpful.
Product/Service: offers, identifiers, brand, about/mentions linking to pillar/support where relevant.
Local/Events (if applicable): LocalBusiness/Event schema tied to the cluster; correct geo, hours, eventStatus.
WebSite with searchAction; Sitelinks Searchbox for branded navigation.

AI readiness and prompt bank

Prompts: "What is [topic]?", "How to implement [topic]?", "Best [topic] tools", "Common mistakes in [topic]", "Pricing for [topic] solutions".
Run monthly in AI Overviews and assistants; log citations and accuracy.
Fix misstatements by tightening definitions, adding schema, and improving anchors.

Measurement and KPIs

Coverage: % supports published and linked; schema coverage per template.
Eligibility: rich result detections (Article/FAQ/HowTo/Product) per cluster.
AI citations: assistant mentions of pillar/supports; share vs competitors.
CTR: before/after schema/link updates; segment by intent.
Conversion: leads/bookings/cart adds from cluster entry pages; assisted conversions.
Disambiguation: drop in branded query modifiers; improved Knowledge Panel/answer accuracy.

Maintenance and refresh cadence

Quarterly: refresh stats, screenshots, offers, and bios; update schema dates.
Prune or merge thin supports; redirect while keeping IDs stable.
Add new supports for emerging queries; retire overlapping pages.
Crawl monthly for missing schema, broken links, duplicate IDs.
Re-run prompt bank monthly; annotate changes.

Case snapshots

SaaS cluster on "AI search optimization"

Built pillar + 8 supports (ranking factors, workflow, metrics, prompts, technical checklist).
Added about/mentions tying to products and integrations; Product/SoftwareApplication schema on commercial pages.
Result: AI Overviews cited pillar and two supports; CTR +12%; demo requests +10% from cluster entry pages.

Clinic cluster on "Physiotherapy"

Pillar for city + supports for conditions, exercises (HowTo), practitioner bios (Person), booking FAQs, events.
LocalBusiness schema per clinic; Event schema for workshops; FAQs for access/insurance.
Result: stable local pack, event carousel inclusion, assistants recommending correct hours and practitioners.

Ecommerce cluster on "Hiking backpacks"

Pillar + supports (fit/how-to pack, comparisons, care, regional checklists, brand stories).
Product schema with offers and identifiers; accessories linked via isRelatedTo; HowTo/FAQ on care pages.
Result: Product rich results returned; +9% add-to-cart from cluster pages; AI answers citing correct specs.

Governance and roles

Strategy: SEO leads entity map, clusters, and prompt bank.
Content: writers/SMEs follow briefs; editors enforce E-E-A-T and answer-first.
Engineering: maintains schema templates, @id reuse, and link modules; CI for validation.
Analytics: dashboards for coverage, citations, CTR, conversions; alerts for errors.
PR/Brand: sameAs alignment; consistent naming in external mentions.

90-day rollout plan

Weeks 1–2: research entities/intents; draft cluster map and ID list; pick first pillar.
Weeks 3–4: write pillar and 3–5 supports; implement schema and links; validate in staging.
Weeks 5–6: publish pilot cluster; set dashboards and prompt bank; annotate launch.
Weeks 7–8: expand supports; add FAQs/HowTos; optimize anchors and CTAs.
Weeks 9–12: localize if needed; add commercial tie-ins; refresh and prune weak pages.

Common mistakes to avoid

Overlapping clusters competing for the same terms.
Thin supports that add no new value.
Missing or inconsistent @id across cluster pages.
Generic anchors ("click here") instead of entity-rich links.
Ignoring AI answers; failing to adjust content when assistants misstate facts.

Prompt bank for cluster QA

What is [topic]?
How do I implement [topic]?
Best tools for [topic]?
Common mistakes in [topic]?
Pricing/ROI for [topic] solutions?
Who are the experts on [topic] at [brand]?
Run monthly across AI Overviews and assistants; log citations and correctness; fix definitions and schema when wrong.

Analytics and dashboards

Coverage: % of planned supports live and linked; schema coverage per template; duplicate ID count.
Eligibility: rich result detections per cluster (Article/FAQ/HowTo/Product).
AI citations: assistant mentions by pillar/support; share vs competitors; prompt logs stored.
Performance: impressions/CTR and conversions per cluster entry page; assisted conversions.
Freshness: timers for stats, offers, bios, and screenshots; alerts for stale items.
Link health: orphaned supports, broken/redirected anchors, average link depth.

Experiments to run

FAQ/HowTo add: add structured FAQs to a subset of supports; measure CTR and citations vs control.
Anchor optimization: test entity-rich anchors vs generic on sibling links; monitor CTR and crawl depth.
Module placement: move related-content modules higher on page for half the cluster; compare engagement and AI citations.
Content refresh: update stats and definitions on select supports; track salience scores and AI answer accuracy.
Localization: localize one cluster with stable IDs; measure rich results and citations by locale.

Cluster governance

ID map: store @id, sameAs, owner, last updated; required for all entities in the cluster.
Standards: required fields per template; about/mentions rules; naming conventions.
CI: lint for required schema fields and duplicate IDs; rendered checks for JS sites.
Change log: record launches, refreshes, redirects, and schema updates with validation links.
Cadence: weekly error review, monthly prompt tests, quarterly cluster audits and pruning.

Migration and cleanup

Inventory existing content; group by topic/entity; mark duplicates and thin pages.
Choose winners for pillar/support; redirect redundant URLs while keeping IDs stable.
Update anchors to point to new structure; remove orphaned paths.
Validate schema and links post-migration; monitor CTR and citations.

Internal linking deep dive

Anchor strategy: include entity + intent ("AI search metrics framework") not generic text.
Module rules: related modules keyed to shared entities; avoid duplicate links on the same page.
Depth control: ensure every support is linked from pillar and at least one sibling; add footer/locator links for large clusters.
Crawl checks: monthly crawl to find broken anchors, redirects, or missing reciprocal links.

Structured data QA (detailed)

Article/BlogPosting: headline, author Person, publisher Organization, datePublished/dateModified, image, about/mentions, BreadcrumbList.

Topic Clusters: Growth Playbook with Checklists for Teams