Build AEO-Compatible Websites

When someone asks Claude, ChatGPT, Perplexity, or Gemini about your industry, does your business get mentioned? For a growing number of potential customers, AI assistants have replaced Google as the first place they turn for recommendations, comparisons, and research.

This shift changes the game for how businesses get discovered. Traditional SEO optimised your website for Google's link-based ranking algorithm. AI Engine Optimisation (AEO) optimises your website for how large language models retrieve, evaluate, and cite information.

The difference is fundamental. Google ranks pages. AI models synthesise answers. Google rewards backlinks and keyword density. AI models reward structured data, entity clarity, and authoritative content they can confidently reference. If your website isn't built for this new reality, you're invisible to a growing audience — even if you rank on page one of Google.

This guide covers everything you need to make your website AEO-compatible: what AI engines look for, a practical checklist you can implement today, common mistakes to avoid, and how to measure whether it's working.

How AI Engines Discover Content

Understanding how AI platforms find and use your content is the foundation of AEO. There are two main mechanisms at play, and they work differently from how Google crawls the web.

Training Data vs Retrieval-Augmented Generation (RAG)

Training data is the massive corpus of text that LLMs learn from during their initial training phase. If your website content was included in a model's training data, the model may "know" about your business — but this knowledge is frozen at the training cutoff date and can be imprecise or outdated.

RAG (Retrieval-Augmented Generation) is what makes AI assistants useful in real time. When a user asks a question, the system searches live sources — web pages, knowledge bases, APIs — retrieves relevant content, and feeds it to the model as context for generating an answer. This is how Perplexity, ChatGPT with browsing, and Claude with web search actually work.

Google's own AI features (AI Overviews and AI Mode) use a related technique called query fan-out: when you ask a complex question, the system generates multiple related sub-queries concurrently, retrieves results for each, and synthesises them into a single answer with clickable source links. This means your content can surface in AI answers even for queries you didn't directly target — as long as it contains relevant, specific information that addresses part of the user's broader question.

AEO matters most for RAG. When an AI platform searches the web for answers, your content needs to be structured in a way that makes it easy to retrieve, parse, and cite.

How LLMs Decide What to Cite

AI models don't just grab the first result. They evaluate content on several dimensions:

• Entity clarity — Can the model confidently identify what your business is, what it does, and where it operates?
• Structural coherence — Is the content organised with clear headings, logical flow, and well-defined sections?
• Factual density — Does the content contain specific, verifiable claims rather than vague marketing language?
• Authority signals — Is the content published by a credible source with consistent identity across the web?
• Freshness — Is the content recently published or updated, with clear timestamps?

The recommendation layer in AI assistants works like a well-read colleague making a suggestion. They don't recommend the loudest brand — they recommend the one they can most confidently describe and justify.

Social Platforms Are Reshaping AI Search

There's a second shift happening alongside the rise of AI assistants, and it compounds the AEO challenge: social platforms are becoming search engines in their own right, and AI models are increasingly drawing from them as source material.

Reddit, LinkedIn, and Instagram are no longer just places people scroll for entertainment. They're where people actively search for recommendations, compare products, vet service providers, and form opinions. Nearly 40% of Gen Z now prefers TikTok or Instagram over Google for search. LinkedIn has become the default research layer for B2B purchasing decisions. And Reddit — with its long-form discussions and community-vetted answers — has become one of the most heavily weighted sources in AI training data and RAG pipelines.

This matters for AEO because AI models don't just pull from your website. They synthesise answers from across the web, and social platforms are a significant part of that web. When someone asks an AI assistant "What's the best CRM for small businesses in Europe?", the model may reference a Reddit thread, a LinkedIn post from an industry expert, or an Instagram carousel that went viral in a niche community — alongside (or instead of) your website.

The practical takeaway: AEO isn't just about your website. Your off-site presence — particularly on Reddit, LinkedIn, and Instagram — is part of the information ecosystem that AI models draw from when deciding whether to mention your business. A strong social presence creates multiple touchpoints that reinforce your entity clarity and authority across the sources AI models trust.

The AEO Checklist

Here are seven areas to focus on, each with specific actions you can take to make your website more visible to AI platforms.

1. Structured Data & Schema Markup

Schema markup is machine-readable metadata you add to your HTML that tells AI systems exactly what your content represents. Google's own AI guide notes that structured data isn't strictly required for AI features — but it remains one of the strongest signals for helping AI systems understand your content with precision, and it's critical for rich results that feed into AI Overviews.

Example of minimal Organization schema:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://yourcompany.com",
  "logo": "https://yourcompany.com/logo.png",
  "description": "One clear sentence about what you do.",
  "address": {
    "@type": "PostalAddress",
    "addressLocality": "Luxembourg",
    "addressCountry": "LU"
  },
  "sameAs": [
    "https://linkedin.com/company/yourcompany"
  ]
}
</script>

2. Entity Clarity

AI models think in entities — people, organisations, products, locations, concepts. Your website needs to make it unambiguous what entity you are and what you do.

The goal is disambiguation. If an AI model encounters your name, it should never confuse you with another entity. Consistent naming, clear descriptions, and explicit geographic context all help.

3. Content Structure

AI models extract information from well-structured content far more reliably than from walls of text. Structure is not just for readability — it's for machine parseability.

4. Authority Signals

AI models assess whether your content is trustworthy enough to cite. Authority isn't just about backlinks — it's about consistency, transparency, and demonstrated expertise.

5. Non-Commodity Content

Google's own AI optimisation guidance makes one point louder than any other: AI systems prioritise non-commodity content — expert or experienced perspectives that go beyond common knowledge. Content that simply repackages widely available information (think "7 Tips for First-Time Homebuyers") provides nothing unique for an AI model to cite when dozens of other pages say the same thing.

This is the single biggest mindset shift from traditional SEO to AEO. SEO rewarded coverage breadth — write about every keyword. AEO rewards depth and originality — write about what only you can say.

6. Technical Foundations

The technical quality of your website directly affects whether AI crawlers can access and parse your content.

7. Freshness & Updates

AI platforms favour recent content. A page last updated in 2021 is less likely to be cited than one updated this month, even if the core information hasn't changed.

What NOT to Do

AEO anti-patterns can actively harm your visibility. Tactics that worked for SEO in the 2010s can be counterproductive with AI engines.

AEO vs SEO: What's Different?

AEO and SEO share DNA, but they optimise for different systems with different priorities. Here's how they compare:

Dimension	Traditional SEO	AEO
Optimises for	Google's ranking algorithm	LLM retrieval and citation
Primary goal	Rank on page 1 of search results	Get mentioned in AI-generated answers
Key signals	Backlinks, keyword density, domain authority	Structured data, entity clarity, factual density
Content format	Keyword-optimised pages and blog posts	Well-structured, citation-ready content
User journey	User clicks a link, lands on your site	AI cites you in an answer; user may or may not visit
Measurement	Rankings, organic traffic, CTR	AI citation rate, brand mention frequency, recommendation share
Technical focus	Page speed, mobile-first, Core Web Vitals	Schema markup, semantic HTML, server-rendered content
Competition	10 blue links on a results page	Being the single source an AI chooses to cite

The two disciplines are complementary, not competing. Google's own AI optimisation guide confirms this directly: "The best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems." A website that's well-optimised for SEO has a head start on AEO. But AEO requires additional intentional work — non-commodity content, entity clarity, and off-site presence across social platforms — that traditional SEO alone doesn't cover.

How to Measure AEO Success

AEO is harder to measure than SEO because AI platforms don't provide analytics dashboards. But there are concrete KPIs you can track to understand your AI visibility over time.

The AEO KPI Framework

These six metrics provide a comprehensive view of your AI visibility:

Manual Testing

The most practical way to measure AEO today is manual testing. Build a set of 10–20 questions that your ideal customers would ask AI assistants, and run them across multiple platforms monthly:

• Ask Claude, ChatGPT, Perplexity, and Gemini the same questions
• Record whether your business is mentioned, how it's described, and whether your content is cited
• Track changes month over month as you implement AEO improvements
• Note which competitors appear in the responses and how they're positioned relative to you

Use the AEO Scanner

We built a free tool that automates this process. The AEO Visibility Scanner analyses your business across Claude, ChatGPT, Perplexity, and Gemini and generates a personalised report with scores, gaps, and actionable recommendations — including your AEO KPI dashboard.