Build Clear Entity Definitions
LLMs favour clean entity definitions, consistent terminology, and clear relationships. If your brand identity changes across pages, models struggle to decide which version is correct.
Your core pages should answer who you are, what you do, and why you are different. A concise, repeatable statement gives AI systems a stable foundation for understanding your brand.
Use Structured Data the Right Way
Schema markup, knowledge graphs, and concise FAQs help models retrieve accurate facts. Structured data reduces ambiguity and improves retrieval confidence.
Well-formed markup also strengthens model citations by making key facts easy to verify and attribute.
- Organisation and Product schema where relevant
- FAQ and HowTo schema for support content
- Consistent canonical URLs for key entities
Create a Semantic Hierarchy
A structured content hierarchy reduces ambiguity and strengthens recommendation weight. Pillar pages should connect to supporting evidence and citations.
Use internal linking to show how topics relate, and keep your sitemap current so AI crawlers can discover updates quickly.
Key Takeaways
- 1Consistency across entities is more valuable than volume.
- 2Structured data clarifies facts for AI retrieval and citation.
- 3Semantic hierarchy guides models to the right information.