What is GEO? Generative Engine Optimisation explained.

Your buyer typed a question into ChatGPT. An AI generated an answer that named three companies in your category. Yours was not one of them. That is the problem GEO exists to solve.

What GEO actually is

GEO stands for Generative Engine Optimisation. It is the practice of building the signals, content, and authority that make a brand appear in AI-generated answers. across ChatGPT, Perplexity, Claude, Google AI Overviews, Gemini, and every AI platform that comes after them.

The discipline was first defined in a 2023 Princeton University research paper examining how content characteristics affect citation rates in AI-generated responses. Since then it has become one of the fastest-growing areas in marketing. because AI search has become one of the fastest-growing ways buyers discover brands.

ChatGPT now has over 900 million weekly active users. Google AI Overviews appear on roughly 13 billion queries per month. Around 93% of AI search sessions end without a website click, meaning the AI answer itself is often the entire discovery moment. If your brand is not in that answer, you were not in the consideration set.

How GEO differs from SEO

SEO is about ranking in a list of links. GEO is about being cited in a generated answer. That difference sounds small but it changes everything about what you optimise for.

In SEO, position 1 gets roughly 28% of clicks. Positions 2 through 10 share the rest. In GEO, there are no positions. There is cited or not cited. Early in the response or late. Described positively or neutrally or not at all.

The signals that drive SEO rankings. backlinks, domain authority, keyword density. are weak predictors of AI citation. The signals that drive AI citation are different: entity consistency, structured data, citation-ready content, external authority signals, and the accuracy of how AI systems currently understand your brand.

This matters because a brand can be doing everything right in SEO and still be invisible in AI search. The two disciplines are not interchangeable. They overlap in places. good SEO remains the foundation for AI indexing. but GEO requires its own strategy, its own content architecture, and its own tracking.

Why it matters more for B2B than most brands realise

B2B buyers use AI differently to consumers. They are not asking AI for a restaurant recommendation or a product to buy. They are using AI to research categories, compare vendors, draft shortlists, and prepare for procurement conversations. These are high-intent, research-heavy queries. exactly the moment when being cited, and being cited well, has the most commercial impact.

Research from Seer Interactive found that AI-referred traffic converts at 4.4 times the rate of organic search traffic. The buyers who arrive via an AI citation have already been pre-qualified by the AI's answer. They know who you are, roughly what you do, and why someone recommended you. That is a fundamentally different conversation than a cold website visit from a search click.

Being absent from AI answers does not just mean missing traffic. It means being absent from the conversation that shapes your buyer's shortlist before they ever reach your website.

What GEO actually involves

Good GEO is not a single tactic. It is a layered programme of foundational work, content production, and external authority building. The core elements are:

Entity consolidation

AI systems build their understanding of a brand from every signal they can find. your website, Wikidata, Crunchbase, LinkedIn, directories, press coverage, and more. If those signals are inconsistent, incomplete, or contradictory, the AI builds an inaccurate picture of your brand and cites it. or does not cite it at all. Entity consolidation is the process of auditing and aligning all those signals so AI systems build one accurate, consistent picture. It is the foundation everything else builds on.

Structured content

AI systems extract and cite content that answers specific questions with specific answers. That means FAQ schema on solution pages, definitive guides that establish category authority, comparison pages that address evaluative queries, and case studies restructured to lead with a clear problem, named outcome, and methodology. Content written for humans to read linearly is often invisible to AI extraction. Content structured for extraction and citation is not.

External authority signals

AI systems corroborate brand claims by looking for external sources. A brand that only talks about itself is less citable than a brand mentioned positively across trade publications, review platforms, and independent commentary. External placement articles, Clutch reviews, and thought leadership in trade press are not just PR. they are GEO signals.

Schema markup and LLMs.txt

Structured data tells AI crawlers what your pages contain and how to categorise them. Schema markup on key pages. Organisation, Article, FAQ, HowTo. makes content easier to extract and cite. LLMs.txt is a newer convention that tells AI systems explicitly what to index and how to understand your site's structure. It is particularly effective for ChatGPT and Perplexity, and less relevant for Google which has its own crawling approach.

How to know if GEO is working

GEO is only useful if you can measure it. That means tracking brand presence in AI responses. not traffic from AI referrals, which is partial and delayed, but actual citation events in actual AI responses to actual buyer queries.

The right measurement framework tracks: brand detection (cited or not cited), position (early, mid, or late in the response), sentiment (positive, neutral, or negative), and competitor presence (which competitors appear in the same responses). Tracking these across a defined set of buyer-language prompts at 30, 60, and 90 days shows what is working and where the gaps are.