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Imagine your prospective B2B buyer does not look for you in Google. Instead they put a question to ChatGPT, Perplexity or Google AI Overviews and receive a ready answer with specific recommendations. If your company does not appear in that narrative, you lose the buyer before you even knew they were looking. That is why a new discipline emerged: GEO, or Generative Engine Optimization.
GEO is no longer theory. The term entered the academic literature in 2023 and has since moved from research papers into boardrooms. Major consultancies and search agencies now write about GEO as a new standard for online presence. This guide is a complete reference on the subject.
What is GEO? A definition
GEO (Generative Engine Optimization) is the set of practices and strategies aimed at increasing the frequency and quality of a brand, product or piece of content appearing in answers generated by AI language systems - ChatGPT, Perplexity, Google AI Overviews, Claude and Gemini among them.
Put simply: GEO is SEO for generative engines. Where conventional SEO optimises content for the ranking algorithms of search engines, GEO optimises the brand and its content for how AI systems understand, process and cite information.
A working definition: GEO is the strategic shaping of the knowledge AI systems hold about a brand, its expertise and its value to customers, in order to increase the frequency and quality of its citation in AI answers to category questions.
GEO vs SEO: the key differences
GEO and SEO are not competitors. They are two complementary approaches to online visibility. But they differ fundamentally in how they work.
- SEO optimises for a ranking algorithm; GEO optimises for a language model
- SEO measures positions in results lists; GEO measures Share of Voice within an AI narrative
- SEO rests on backlinks and on-page work; GEO rests on mentions and citations
- In SEO you can rank seventh and still be visible; in GEO you are either cited or you are not
- SEO has decades of history and tooling; GEO dates from 2023
- SEO is deterministic - the same keywords give the same results. GEO is probabilistic - AI gives different answers each time
How generative AI engines work
To understand GEO you have to understand how language models work. ChatGPT, Gemini and Claude are large language models trained on enormous corpora of text gathered from the web. Their knowledge of the world - including of your company - comes from what has been written about it online.
When a user asks ChatGPT for a company recommendation, the model does not search the web in real time unless web browsing is enabled. It generates an answer from patterns learned during training. Your AI visibility therefore depends on what was written about your company before the model was trained, not on your current Google position.
Perplexity works differently: it searches the web in real time and cites its sources. Google AI Overviews are a hybrid, drawing on the Google index but processing the results through an AI model. Every engine has its own logic, which means GEO has to be multi-channel.
Why GEO matters in B2B
The scale of AI tool use is growing, but public statistics vary by how they define a user, by market and by measurement period. For a B2B decision, what matters more than global reach is establishing whether buyers in a specific category use AI to discover, compare or verify suppliers.
In B2B the shift is especially significant. Decision-makers use AI for preliminary supplier research, comparing options and shortening the candidate list before first contact. A company unknown to an AI system can be eliminated from the buying process before it ever enters the buyer's field of view.
A strong Google position does not prove presence in ChatGPT answers. The size of the gap depends on the category, the market, the questions and the model, so a result from a small sample must never be generalised across all of B2B.
The pillars of GEO
1. Citation engineering
The most important GEO factor. An Ahrefs study of 75,000 brands found that brand mentions correlate with AI visibility roughly three times more strongly than conventional backlinks. The strongest citation signals are YouTube (correlation 0.74), Reddit, Wikipedia and large media outlets. Domain Rating, the basic SEO measure, correlates with AI visibility at just 0.27.
Citation engineering is the strategic work of building presence in the sources AI systems learn from: articles in industry media, expert posts on platforms such as LinkedIn, presence in directories and comparison sites, and reviews on platforms such as Clutch and G2.
2. Structured content optimisation
Content on your site has to be constructed so AI can process and cite it easily. That means clear definitions of key concepts, an FAQ structure, comparison tables, and lists and headings that answer specific questions. Generic content full of buzzwords and short on substance is useless to AI as a citation source.
3. Schema.org and technical GEO
Structured data helps search engines classify entities and content types, provided it matches what the user sees on the page. It is not independent proof of credibility, nor a guarantee of citation. An llms.txt file can organise your most important URLs for selected crawlers, but Google does not require it for results or AI features.
4. Brand Gravity
Brand Gravity measures a brand's pull within the semantic space of an AI system - how often and how centrally it appears in answers to category questions. Building it requires consistent work on communication coherence: the brand should be associated with a specific niche, a defined expertise and a concrete value to the customer, not merely with a broad product category.
5. E-E-A-T for AI
Google's E-E-A-T framework - experience, expertise, authoritativeness and trustworthiness - originated in SEO, but matters even more in GEO. AI systems learn to trust sources repeatedly cited by authorities. A named expert's personal brand, contributions to industry media, awards and certifications are all signals that build E-E-A-T in an AI context.
How to measure GEO
GEO is harder to measure than SEO, because AI systems publish no rankings. The key metrics are:
- Share of Voice in AI - how often the brand appears in answers relative to competitors (brand mentions divided by total company mentions in the category)
- Citation frequency - how many times the brand appears across the tested question set
- Position in the narrative - whether the brand is named first or somewhere in the middle of a list
- Sentiment - how favourably, neutrally or unfavourably the brand is described in AI answers
- Model coverage - how many AI systems (ChatGPT, Perplexity, Gemini, Claude) know the brand
GEO measurement can use manual tests, model APIs and monitoring tools. Whichever you choose, you need a defined question set, complete answers, documented run conditions and stable coding rules.
How to implement GEO, step by step
- 1Baseline diagnosis: measure your current Share of Voice in AI for your category. Check ChatGPT, Perplexity, Gemini and Claude. Benchmark against three main competitors. Identify the gaps.
- 2Content audit for citability: does the site have clear definitions? Is there an FAQ section? Are there case studies with data? Is the tone expert and specific?
- 3Technical foundations: implement or verify schema.org Organization, Article and FAQ markup. Add an llms.txt file. Check that AI crawlers are permitted in robots.txt.
- 4Citation engineering - a media plan: identify ten industry publications you want to be cited in. Prepare a pitch with a distinctive insight or dataset. Start with the ones AI systems cite most often.
- 5Create definitive content: write articles that become the reference on their topic in your niche. For every key concept in your category, your company should have an article that defines and explains it better than any other source.
- 6Monitor and iterate: measure Share of Voice monthly. Analyse which actions produced growth. Scale what works.
Want to establish your company's GEO baseline? We assess category fit first. A Snapshot or audit then documents the agreed questions, the complete answers, the citations and the benchmark.
The state of the market
Most markets are at an early stage of GEO adoption. Large search agencies now have landing pages about GEO, but deep expertise in optimising for AI systems remains rare. That means companies investing now hold a first-mover advantage in their niches.
Google AI Overviews are widely available. Perplexity and ChatGPT Search are in daily use. The market is ready, and most B2B companies have not started.
The window will not stay open indefinitely. As with SEO in the early 2010s, whoever starts now builds a position that is hard to catch. The first companies to optimise for GEO in their niches become the default AI recommendation for their category.
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Frequently asked questions
What is GEO (Generative Engine Optimization)?
GEO is a set of strategies and practices aimed at increasing a brand's presence in answers generated by AI systems such as ChatGPT, Perplexity, Google AI Overviews, Claude and Gemini. In short: GEO is SEO for generative AI engines.
How does GEO differ from SEO?
SEO optimises content for the ranking algorithms of Google and Bing, measures positions in results lists and rests largely on links. GEO optimises a brand for AI language models, measures Share of Voice within an AI narrative and rests on mentions, citations and content structure. The two are complementary - strong SEO helps GEO, but does not replace it.
Does GEO matter for small and mid-sized B2B companies?
Yes, and for smaller firms it can be an opportunity. Large corporations hold an advantage in conventional SEO through budget, links and domain authority. In GEO everyone starts closer to zero, so a new discipline means more even odds. A smaller company with genuine niche expertise, an active presence in industry media and well-structured content can out-perform much larger competitors in AI visibility.
How long does GEO take to show results?
GEO works on several horizons. Technical changes such as structured data and llms.txt can show effects within four to eight weeks. Citation engineering, meaning presence in media, takes two to four months. Building Brand Gravity in AI systems is a six- to twelve-month effort. Starting early is worth it.
Which AI systems matter most for GEO?
For B2B the priorities are usually ChatGPT (the largest user base), Perplexity (used for research with cited sources), Google AI Overviews (integrated into Google Search) and Claude (growing use in professional contexts). Gemini is worth monitoring given its integration with Google Workspace.
Does my blog content help with GEO?
Yes, but not all content equally. Expert content with specific data, definitions and a distinctive point of view is cited by AI far more often than general content. Articles that become the definition of a topic in their niche, FAQs with precise answers and case studies with numbers are the formats that convert best into AI citations.
Where can I commission a GEO audit?
AiVisible offers a Snapshot and a strategic AI visibility audit for B2B companies. We match the range of models, questions and benchmarking to the category, and pair the result with complete answer records and prioritised actions. See the [current pricing](/en/pricing).