What is Generative Engine Optimisation (GEO)?

Generative Engine Optimisation (GEO) is the practice of making your content more likely to be cited, referenced, or summarised by AI-powered search tools: Google AI Overviews, ChatGPT web search, Perplexity, Microsoft Copilot, and Claude.

Where traditional SEO focuses on ranking in a list of links, GEO focuses on being the source an AI system draws from when it generates an answer. The goal is not just a link in position three; it is being the authority that an AI cites when summarising what is true about a topic.

Why GEO matters now

AI search tools are changing how people get information. A growing proportion of searches do not result in a click to any website: the AI answers the question directly, sometimes without showing the user a list of results at all.

This creates a new challenge. A site that ranks number one in organic search but is never cited by AI tools is invisible to a growing segment of users. Conversely, a site that is consistently cited in AI answers gains brand impressions, traffic, and authority signals even when it does not rank first organically.

The research is unambiguous on one point: SEO is still the foundation. 99% of pages cited in Google AI Overviews are already in the organic top 10. 87% of ChatGPT citations correlate with Bing's top organic results. You cannot win GEO without first winning SEO.

GEO is built on top of SEO, not instead of it.

How GEO differs from SEO

SEO	GEO
Goal: appear in a ranked list of links	Goal: be cited as a source in an AI-generated answer
Measured by: ranking position and CTR	Measured by: citation frequency across AI platforms
Primary signals: authority, relevance, technical health	Primary signals: verifiability, specificity, structure
Time horizon: months	Time horizon: weeks to months (some changes work quickly)
User action: click through to the page	User action: brand impression even without a click

What AI systems look for when choosing sources

Different AI platforms have different citation models, but they share common requirements:

Verifiable, specific claims

AI systems prefer content with specific, attributable facts. "Studies show that redirect chains reduce link equity" is vague and not citable. "Each additional redirect hop reduces the PageRank passed to the destination by approximately 15%, according to research by..." is specific, attributable, and citable.

Write in verifiable facts, not vague assertions.

Named, credentialled authors

AI models that evaluate E-E-A-T (Experience, Expertise, Authoritativeness, Trust) weight content from named experts over anonymous or team-authored content. Author bios with specific credentials, not "the editorial team", are a meaningful GEO signal.

Direct, extractable answers

AI systems pull passages they can present verbatim. Content structured around direct answers to specific questions is far more extractable than flowing prose. Open every major section with a 40 to 60 word direct answer to the question in the heading.

Question-format headings

AI systems are trained to match queries to content. H2 headings written as questions mirror how users phrase searches and how AI systems categorise content.

Original data and primary research

Content that contains original statistics, survey results, or case studies is cited at significantly higher rates than content that summarises other sources. If you can produce original data, it becomes a citation magnet.

Short, self-contained paragraphs

AI systems extract passages that make sense independently. Paragraphs of 2 to 4 sentences that answer a specific point are more extractable than long flowing paragraphs that require context from surrounding text.

Platform-specific GEO signals

Google AI Overviews

Pages cited in AI Overviews are almost always already in the organic top 10 for that query. The additional signals Google uses for AI Overview citation include: semantic completeness (does the page fully answer the query without requiring the user to look elsewhere?), entity density (how many related entities does the page mention?), and structured data.

FAQPage schema is particularly effective: Google frequently pulls FAQ answers verbatim into AI Overviews.

ChatGPT / SearchGPT

ChatGPT's web search mode uses Bing's index. Ranking in Bing is a prerequisite. Beyond that, ChatGPT favours content updated within the past 30 days, specific statistics, and direct answers. Ensure GPTBot and OAI-SearchBot are allowed in your robots.txt.

Perplexity

Perplexity runs its own crawler and rewards freshness more aggressively than any other platform. Content published or significantly updated recently gets a meaningful boost. Answer the query in the first 100 words. Allow PerplexityBot in robots.txt.

Claude (Anthropic)

Claude rewards verifiable credibility: named authors, cited primary sources, and specific data. Vague content from high-authority domains performs worse than specific, well-sourced content from lower-authority domains. Allow ClaudeBot and Claude-SearchBot in robots.txt.

Grok (xAI)

Grok pulls from Bing's index plus X (Twitter). An active, linked presence on X is a direct Grok citation signal. Submit new content via IndexNow to accelerate Bing indexing, which flows through to Grok.

The robots.txt requirement

All AI crawlers must be allowed in your robots.txt to be eligible for citation. Blocking any of them cuts you out of that platform's citation pool entirely:

User-agent: GPTBot
Allow: /

User-agent: OAI-SearchBot
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: Claude-SearchBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Google-Extended
Allow: /

Check your robots.txt is not inadvertently blocking these agents. Use Crawly's robots.txt generator to build a correctly configured file.

Off-page GEO signals

94% of AI citations come from sources other than the brand's own website. Brands cited through third-party sources are 6.5 times more likely to be cited than through their own domain alone.

The highest-impact off-page GEO assets:

• Wikipedia presence: AI models are trained heavily on Wikipedia. A Wikipedia article about your brand or key people is the single highest-leverage off-page asset for AI citation
• Press and earned media: news articles and industry publication mentions are weighted heavily by all AI citation models
• Reddit: Reddit is the third most cited domain in Google AI Overviews. Genuine participation in relevant communities creates citable third-party mentions
• LinkedIn: feeds directly into Bing's social signals, which flow through to ChatGPT and Grok

llms.txt

An emerging convention: a file at yoursite.com/llms.txt that tells AI crawlers what your site is about and which pages are most important. Think of it as a sitemap for AI systems rather than traditional search crawlers.

It is not yet a confirmed ranking signal for any major platform, but Perplexity has confirmed it uses llms.txt files. For sites where accurate AI representation matters, implementing one is low-effort and low-risk. See what is llms.txt for a full explanation.

How to measure GEO performance

Traditional rank tracking does not capture AI citations. To measure GEO:

1. Run target queries weekly: search your target questions in ChatGPT, Perplexity, and Google AI Overviews. Log which sources are cited.
2. Track brand mentions: monitor whether your brand appears in AI-generated answers even without a direct citation
3. Monitor Google AI Overview appearances: Google Search Console shows which of your pages are being cited in AI Overviews in the Insights section

GEO is still a new discipline and measurement tools are developing rapidly. For now, manual monitoring is the most reliable approach.

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GEO starts with strong technical foundations: AI crawlers need access, content needs to be structured, and robots.txt needs to allow the right agents. Run a free crawl to check your site's technical readiness for AI citation.