How to Optimise Your Content or Website for LLMs (Large Language Models)

Search engines are no longer the only gateways to information Large Language Models (LLMs) like ChatGPT, Gemini, and Perplexity are becoming new discovery platforms.

These AI systems don’t “crawl” your website like Google; they reason through structured data, semantic cues, and contextual relevance.

Optimising for LLMs is about making your content machine-comprehensible, not just machine-readable. This guide breaks down how to structure, tag, and format your content so LLMs can understand, surface, and cite it.

1. Understand How LLMs Consume Information

LLMs use a mix of training data, retrieval-augmented generation (RAG), and web connectors to pull in real-time information.

They rely on:

• Semantic structures (clear hierarchy of ideas)
• Linked data (entities, relationships, and context)
• Structured metadata (schema.org, JSON-LD, microdata)
• Citation signals (clear sources, canonical URLs, author authority)

Unlike SEO crawlers, LLMs don’t rely on backlinks alone they rely on knowledge integrity.

2. Build LLM-Readable Content Architecture

Use Semantic HTML Tags

• Use clear heading levels ( H1, H2, H3)
• Add descriptive alt text for images
• Avoid div-heavy layouts that hide structure

3. Link Entities, Not Just Pages

LLMs connect concepts, not just URLs.
Use entity-based linking like:

• “AI content strategy” → link to your main hub page
• Mention specific tools (ChatGPT, Jasper, Perplexity) with consistent anchor text

4. Include Structured Data

Use JSON-LD schema for:

• Article – guides and blogs
• FAQPage – Q&A content
• HowTo – step-based tutorials

5. Write for Dual Readability: Humans + Machines

LLMs summarise and interpret content, not just index it.

Element	Human Purpose	Machine Purpose
Headings	Scannability	Topic segmentation
Lists & Tables	Clarity	Knowledge structuring
Quotes & Citations	Authority	Attribution
FAQs	Engagement	AI snippet extraction

Pro Tip:
End each post with a short AI summary section (like the one below). This helps models like ChatGPT, Gemini, and Perplexity quote you accurately.

6. Optimise Metadata for AI Retrieval

Traditional SEO titles still matter but so do AI context cues.

Checklist:

• Use clear, factual titles (avoid clickbait)
• Keep meta descriptions concise and educational
• Add canonical URLs and Open Graph data
• Include author and brand identity (LLMs prioritise trust)

7.Create FAQ + Schema Blocks for LLM Snippets

LLMs often pull structured answers from Q&A formats. You can use a WordPress “FAQ” block or paste this schema below using a plugin like Rank Math or Yoast:

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is LLM optimization?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "LLM optimization is the process of structuring and formatting your content so large language models like ChatGPT and Gemini can easily interpret, summarize, and cite it."
      }
    },
    {
      "@type": "Question",
      "name": "How does LLM optimization differ from SEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "SEO focuses on ranking in search engines, while LLM optimization focuses on making your content understandable and referenceable by AI reasoning systems."
      }
    }
  ]
}

8. Track and Improve Your AI Visibility Metrics

LLM optimisation is measurable. Monitor these performance indicators:

Metric	Description	Target
Generative Impressions	Frequency of your content in AI results	+50% MoM
LLM Mentions	Times your site is cited by AI models	3–5 per quarter
Knowledge Graph Links	Number of connected entities	Increasing
Engagement Duration	Average reading time on optimised pages	>3 minutes