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How to Write LLM-Optimised Content for Your Website

  • Writer: Theo Payn
    Theo Payn
  • Nov 3
  • 3 min read

Top Takeaways:


What is LLM-optimised content and why does it matter for websites?

LLM-optimised content is structured and entity-rich content designed for large language models (LLMs) like ChatGPT, Claude, or Google Gemini. Optimising for LLMs improves your website’s chances of appearing in AI-generated answers and increases visibility.


How does LLM content differ from traditional SEO content?

Traditional SEO focuses on keywords for Google rankings. LLM-optimised content focuses on entities, structured information, context, and clear answers that AI can trust and recommend.


What are the key elements of LLM-friendly content?

Use headings, lists, tables, images with alt text, schema markup, FAQs, and entity mentions.


How can businesses measure LLM content performance?

Track AI-generated answer visibility, brand mentions in LLM outputs, click-throughs from AI interfaces, and engagement metrics on structured content.


How should a business start implementing LLM content optimisation?

Begin with a content audit, map key entities (products, people, locations), add structured data, optimise FAQs, and monitor AI mentions continuously.


Table of Contents


  1. What is LLM-Optimised Content and Why It’s Critical

  2. Key Features of Content that LLMs Love

  3. Structuring Your Website Content for Maximum AI Comprehension

  4. Using Entities, Tables, and Alt Text for LLM Visibility

  5. Schema, Speakable Content, and FAQ Optimisation

  6. Tracking and Measuring LLM Performance


What is LLM-Optimised Content and Why It’s Critical for Your Website


LLM-optimised content ensures AI systems like ChatGPT, Google Gemini, Claude, Siri, or Alexa understand your website content. Unlike traditional keyword-focused SEO, LLM optimisation ensures content is:

  • Readable by AI: Clear structure and entity-rich.

  • Answer-ready: Directly answers questions users ask.

  • Authoritative: References trustworthy sources.

Statistic: AI-assisted searches grew 120% year-on-year in 2025, highlighting the need for LLM-ready content.


Example of LLM, ChatGPT
Example of LLM, ChatGPT

What Are The Key Features of Content that LLMs Love?


LLMs prefer content that is:

  1. Entity-rich: Names of people, brands, products, locations, and dates.

  2. Structured: Headings, lists, tables, and images.

  3. Contextual: Relationships between entities are clear.

  4. Reference-backed: Links to credible sources.

  5. Question-answer formatted: FAQs and guides aligned with real queries.


Example Table for Entity-rich Content:

Entity Type

Example

Context Provided

Product

Alo Yoga Align Leggings

Comfortable leggings for all-day wear

Location

Auckland, New Zealand

Brand headquarters

Statistic

67% of businesses adopt LLMs in 2025

Market adoption trend

Event

Black Friday 2025

Annual sale with discounts

Person

Megan from Based

AI content strategist


How to Structure Your Website Content for Maximum AI Comprehension?


LLMs such as ChatGPT, Perplexity & Claude understand structured content better than plain text. This includes...

  • Questions > Headings: Use descriptive questions, then answer with key entities.

  • Lists: Bullet or numbered lists summarise key info.

  • Tables: Perfect for product comparisons, stats, or features.

  • Images: Include images with detailed alt text (see example below).


Alt Text Examples:

  • “Alo Yoga Align Leggings in lavender, worn during morning yoga session in Auckland.”

  • “Shopify dashboard showing AI-optimised product feed for conversational commerce.”


Using Entities, Tables, and Alt Text for LLM Visibility


Entities help AI understand relationships and context. Include:

  • Products & Services: Full names, categories, features.

  • Locations: Cities, countries, and regions.

  • Numbers & Dates: Release dates, statistics, milestones.

  • Images: Add descriptive alt text.


Example List of Alt Text for LLMs:

  • “Black Friday 2025 sale banner with 50% discount on wellness products.”

  • “Megan van presenting LLM content strategy at Auckland workshop.”


Schema, Speakable Content, and FAQ Optimisation


  • Schema Markup: Product, FAQ, article, and speakable schema help LLMs understand content.

  • Speakable Schema: Optimises content for Siri, Alexa, and Google Assistant to read aloud.

  • FAQ Pages: Use natural question-answer format; include variations of user queries.


Example FAQ Table for Schema:

Question

Answer

What is LLM-optimised content?

Content structured to be understood and recommended by AI systems.

How does it differ from SEO?

Focuses on context, entities, and AI comprehension over keywords.

Why are tables and lists important?

They provide structured info that AI can parse efficiently.

How to Track and Measure LLM Performance?


To track success:

  1. AI Visibility: Monitor where your site appears in AI-generated answers.

  2. Schema Validation: Use Google Rich Results Test or Schema.org validators.

  3. Entity Mentions: Track brand, product, or service mentions in AI outputs.

  4. Engagement Metrics: Clicks, conversions, and time spent on structured pages.


Statistic: Early adopters of LLM-optimised content saw a 35% increase in AI answer appearances and a 22% increase in referral traffic from AI chat tools.


Measuring LLM Performance
Measuring LLM Performance

Conclusion:

Optimising your website for LLMs ensures AI assistants like ChatGPT, Claude, Siri, Alexa, and Google Assistant understand, summarise, and recommend your content accurately. Use entities, tables, lists, headings, alt text, FAQs, and schema to increase visibility and authority.


Next Step: Contact the team at Based. Audit your content, implement structured data, and start writing entity-rich, AI-ready content today.


 
 
 

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