Generative Engine Optimisation (GEO): The B2B Guide to AI Search Visibility

Why GEO has become a commercial problem, not a marketing trend

B2B discovery is moving upstream. A buyer can now ask an assistant to compare providers, explain a category, shortlist vendors and challenge a recommendation before a sales form is ever opened. That changes the moment at which a brand enters the buying process. If the assistant does not know enough about you to name you, your conventional funnel may never get a chance to work.

The term Generative Engine Optimisation was formalised in research published at KDD 2024. The researchers described a new optimisation problem: instead of competing only for a position in a ranked list, publishers also compete for visibility inside a generated answer assembled from multiple sources. Their experiments showed that content changes could materially alter visibility, but also that the effect varied by domain. That last point matters. There is no universal GEO trick.

For a B2B firm, the commercial question is simpler: when a buyer asks an AI system the questions that precede a purchase, are you part of the answer set?

GEO and SEO share a foundation

The strongest GEO programme still begins with ordinary search discipline. Google states that its existing SEO best practices remain relevant to AI Overviews and AI Mode, and that there are no special technical requirements or secret AI markup required to appear. Pages still need to be crawlable, indexable, useful and internally connected.

The difference is what you optimise the content to do once it is found. Traditional SEO asks whether a page deserves to rank for a query. GEO also asks whether a specific passage can be extracted cleanly, whether the brand and claim can be verified elsewhere, and whether the source adds something distinctive enough to cite.

That is why generic content becomes even less useful in an answer engine. A paragraph that merely repeats the consensus gives a model no reason to attribute the idea to you.

The five layers of a practical B2B GEO programme

1. Prompt and demand mapping. Start with the questions a real buying committee asks, not a list of short keywords. Include category questions, comparison prompts, implementation questions, risk questions and vendor-shortlist prompts.
2. Technical accessibility. Make sure search crawlers can access the pages. For ChatGPT search specifically, OpenAI advises publishers not to block OAI-SearchBot if they want their content discoverable and citable in search results. For Google AI features, the normal Search technical requirements apply.
3. Extractable content. Put direct answers near the top of relevant sections. Use descriptive headings, explicit entities, short definitions, comparison tables where useful, and language that makes the subject of each claim unambiguous.
4. Evidence and corroboration. A company saying it is excellent is marketing. Independent mentions, case studies, named proof, original data and credible third-party citations give an answer engine something it can verify.
5. Measurement. Track both visibility and commercial outcomes. A mention that never creates qualified traffic or assists pipeline is not the same thing as a recommendation that sends an in-market buyer to the site.

What not to confuse with GEO

GEO is not a licence to produce hundreds of thin pages for every conversational variation of a query. Google explicitly warns against scaled content that adds little value. Nor is it a matter of adding an llms.txt file and declaring the site AI-ready. That file may be useful in some ecosystems, but Google says no special AI text file or schema is required for its generative Search features.

It is also not reputation management disguised as SEO. Third-party evidence matters, but only when the evidence is real. Manufactured forum posts, fake reviews and synthetic consensus create brand risk and are a weak foundation for a channel built around trust.

A simple GEO operating model

Choose twenty to forty commercially relevant prompts. Baseline which brands and sources appear across the AI systems that matter to your market. Group the gaps into three buckets: technical access, on-site answer quality and off-site evidence. Fix the narrowest, highest-intent set first, then repeat the same inspection monthly.

The objective is not to be mentioned for everything. It is to become a reliable source and credible option for the questions that occur immediately before a buyer creates a shortlist.

Why B2B generative engine optimisation is a different problem

Most published GEO advice is written for high-volume consumer categories, where one prompt is asked thousands of times a day and small shifts in phrasing are worth testing. B2B does not work that way. The prompts that precede a six-figure engagement are asked rarely, by a handful of people, in language specific to one situation. Volume is a poor guide to value here.

Three consequences follow. Coverage matters more than frequency: being named in the twenty prompts that precede a shortlist is worth more than appearing in a thousand informational answers. The buying committee also asks different questions at different moments — the technical evaluator asks how it is implemented, the finance sponsor asks what it costs and what breaks, the executive asks who comparable has already done it. And the evidence bar is higher. An assistant recommending a consumer product can lean on aggregate ratings; recommending a supplier for a regulated environment needs something specific to point at.

Four GEO strategies that earn B2B citations

1. Answer the comparison and shortlist prompts directly. Buyers ask assistants to compare approaches, categories and providers long before they ask anyone for a proposal. Most B2B sites have no page that makes an honest comparison, so the model assembles one from whoever did. Write the comparison you would give a prospect on a call, including the cases where your approach is the wrong fit.
2. Publish what only you can know. Aggregate patterns from your own engagements, the failure modes you see repeatedly, the sequence you actually run — none of it can be reconstructed from the consensus, and it is the durable reason to cite you by name.
3. Make the entity unambiguous. State in plain prose who you are, what you sell, who you sell it to and where you operate, and keep that description consistent across your site, your profiles and any third-party listing. A brand an engine cannot resolve confidently is dropped rather than risked.
4. Write for the whole committee, not the champion. A page that answers only the practitioner's question leaves the cost and risk prompts to someone else's content. Give each role a headed section it can be extracted from, in the language that role actually uses.

A ninety-day GEO plan

Starting from nothing, sequence matters more than volume.

1. Weeks one and two — baseline. Choose twenty to forty prompts a real buyer would ask before shortlisting. Run them across the assistants your market uses and record which brands, sources and pages each one names. Without this you cannot tell later whether anything you did worked.
2. Weeks three and four — clear the access blockers. Confirm the crawlers you want can reach the pages, that the pages render without scripts a crawler will not run, and that nothing commercially important is missing from the sitemap.
3. Weeks five to eight — rebuild the answer surface. Take the ten prompts with the highest commercial intent and make sure a specific page answers each one in its opening lines, under a heading that names the question.
4. Weeks nine to twelve — build evidence and re-baseline. Publish the proof you can stand behind, pursue the independent mentions that are realistic in your market, then re-run the same prompt set and compare it with week one.

At ninety days the honest measure is not traffic. It is the share of your target prompts where you are named.

What to measure when the click may never happen

An answer engine exists to resolve the question inside the answer. When it succeeds, the buyer has what they asked for and no reason to visit anyone's site. The signal most marketing teams reach for — sessions from a named source — therefore arrives thinned, delayed or not at all. Read as a scoreboard, it makes a working GEO programme look like a failing one.

Use three tiers instead. Prompt coverage is the leading indicator: the share of your chosen prompt set where you are named, and by which assistant. You own the prompt list, so it is the one measure you can take honestly from day one. The citation itself is the middle tier — which page was lifted, and whether that passage still describes you accurately, because a mention attached to a stale claim is a liability rather than a win. Self-reported attribution is the lagging tier: a free-text question on the enquiry form about how the buyer came across you is often the only honest record of where a B2B first impression was made.

Cadence decides whether any of it means anything. Assistant answers vary between runs, so a single check tells you almost nothing. Run the same prompts, in the same wording, on a fixed schedule, and compare against your week-one baseline rather than against last month's impression.