Topic Clusters
Topic clusters are content structures with 1 hub page (2000+ words) covering a main topic broadly, and 8-15 spoke pages (1500+ words each) covering subtopics in depth. This structure signals comprehensive topic coverage and topical authority to AI systems.
Definition
Topic clusters organize related content around a central hub page using a hub-spoke structure. The hub page (2000+ words) provides a comprehensive overview of the main topic, while spoke pages (1500+ words each) dive deep into specific subtopics. All pages are connected through strategic internal linking: the hub links to all spokes, spokes link back to the hub, and related spokes link to each other. This structure helps AI systems understand that you have comprehensive topic coverage, demonstrating topical authority. AI systems recognize topic clusters through internal link patterns, content depth, and semantic relationships between related pages.
Examples
Hub: "Complete Guide to AI Citation Optimization" (2000+ words) → Spokes: "Schema Markup for AI", "E-E-A-T Signals", "Internal Linking Strategy", etc.
Hub: "SEO Fundamentals" → Spokes: "Keyword Research", "On-Page SEO", "Link Building", "Technical SEO", etc.
Hub: "Content Marketing Strategy" → Spokes: "Blog Writing", "Social Media Content", "Video Content", "Email Marketing", etc.
How to Apply
- 1.Create 1 comprehensive hub page (2000+ words) covering the main topic broadly
- 2.Identify 8-15 subtopics that deserve detailed spoke pages (1500+ words each)
- 3.Link hub page to all spoke pages in relevant sections
- 4.Link spoke pages back to hub page in introduction or conclusion
- 5.Link related spoke pages to each other where contextually relevant
- 6.Maintain consistent terminology and definitions across the cluster
Related Tools
Related Tools
Complement your analysis with these AI citation optimization tools: