Generative Engine Optimisation Agency

Generative engine optimisation is the work of making your business visible in AI-generated answers, so that when a customer asks ChatGPT, Google AI, Perplexity or Claude a question in your market, your brand appears in the response as a mention, a citation or an outright recommendation. It is optimisation for the answer itself, not for a list of links.

The name describes the target. Generative engines are the AI systems that compose answers rather than return results, and they assemble those answers from sources they have learned to treat as credible. GEO influences what those sources say about you, how easily your own content can be read and quoted, and how consistently your credibility corroborates when a model checks.

It overlaps heavily with SEO by design rather than accident, because generative engines learned their sense of authority substantially from the same signals search engines reward. Structured content, verified credentials, authoritative mentions and consistent business information serve both. The difference is emphasis: GEO cares about being quotable and corroborated in ways classic rankings never demanded.

The term sits alongside others you may have met, AI SEO, answer engine optimisation, LLM optimisation, and the industry has not finished arguing about the boundaries. What matters commercially is unchanged by the vocabulary: your customers are asking AI systems who to use, the answers contain names, and there is deliberate, measurable work that determines whether one of them is yours.

SEO earns your position in a ranked list; GEO earns your presence inside a composed answer. The distinction sounds small and changes the work meaningfully. A search engine evaluates your page against a query and places it somewhere a user can choose it. A generative engine reads the open web's evidence about your market, decides who is credible and writes a response that names some businesses and omits the rest. There is no position eleven in an answer.

The overlap is real and worth being honest about: perhaps two thirds of the work serves both. Technical health, structured content, authority signals and reviews feed rankings and citations alike, which is why we run GEO as a discipline alongside SEO rather than a replacement for it. Agencies selling GEO as an entirely separate universe are usually selling the same work twice.

The genuinely distinct third is where GEO earns its name. Optimising for quotability: direct answers a model can lift cleanly. Corroboration: making sure independent sources agree about what you do, because models cross-check in ways a ranking algorithm never did. Prompt-level tracking: measuring your presence in actual answers to actual buyer questions, which no rank tracker can see.

The practical difference is the moment of failure. Weak SEO means fewer people find you among the options. Weak GEO means the option list itself excludes you, and the customer who trusted the answer never learns you existed. As more buying journeys start and end inside an AI conversation, the second failure quietly becomes the more expensive one.

GEO pricing follows the same logic as serious SEO pricing: it depends on your market's competitiveness, the state of your existing digital presence and how many prompts you need to win. A regional firm with strong reviews and a sound website needs a lighter programme than a national brand entering AI answers its competitors already dominate. A quote made before measuring either is a number invented to win a contract.

Most clients run GEO as part of a combined search and AI visibility retainer rather than a standalone line, because the work shares foundations with SEO and buying it twice would mean paying twice for the same signals. Where clients want GEO-led engagements, pricing scales with the prompt set tracked, the content volume required and the source coverage their market's answers demand.

The starting point either way is the AI visibility baseline: measuring where you currently stand across the prompts that matter, what competitors hold and how large the gap is. That baseline turns pricing from guesswork into scoping, and it gives you something no proposal can fake: the actual answers your customers are currently being given, with your absence or presence in them documented.

Treat cost against the asymmetry of the moment. Early positions in AI answers are being set now, cheaply, by whoever does the work first in each market. Displacing an incumbent recommendation later will cost multiples of establishing one today, which makes GEO one of the few channels where waiting is the expensive option.

A fair question, and the honest answer has two halves. The measurable half: yes, deliberate optimisation demonstrably changes whether businesses appear in AI answers. We track prompts before and after campaigns, and the pattern is consistent: structured, corroborated, well-cited businesses get named, and the same businesses were not named before the signals existed. The mechanism is not mysterious; models draw on evidence, and the evidence can be built.

The hype half deserves naming too. Nobody can inject your brand into a model's training, buy a guaranteed recommendation or "rank number one on ChatGPT", and anyone selling those words is selling vapour. Model behaviour also shifts with updates, so visibility is a position you hold and defend, not a trophy you win once. An honest GEO practice works with those constraints instead of denying them.

What separates real practitioners from opportunists is measurement. If a provider cannot show you the prompts they track, the current answers, your share of voice against competitors and the movement over time, they are narrating rather than optimising. This is exactly why we baseline before we promise anything: the scoreboard exists before the first optimisation ships.

The strongest evidence is behavioural rather than technical: your own customers have already changed. Ask your sales team how many enquiries this year mentioned asking ChatGPT first. That number only grows, and the businesses treating it as hype are conceding those conversations to whichever competitor took it seriously first.

By weighing evidence, not by consulting a ranking. When a generative engine answers a "who should I use" question, it draws on what it learned in training and, increasingly, what it retrieves live from the web at the moment of the question. Both routes reward the same underlying things: sources that mention you, content that describes you clearly and credibility that survives cross-checking.

The retrieval route matters most for GEO because it is the route you can influence fastest. Platforms like Perplexity and Google AI fetch current pages before composing answers, and ChatGPT increasingly does the same. The pages they fetch skew heavily towards sources search engines already rank, which is why strong SEO is GEO's foundation: the model's reading list is substantially Google's first page.

From what it reads, the model favours what it can use. Clean, direct statements get quoted; hedged marketing prose gets skipped. Specific evidence, numbers, credentials, named clients, reviews, outweighs adjectives. And corroboration is decisive: a claim your site makes that independent sources repeat is treated as fact, while a claim only you make is treated as marketing. Models are sceptical readers in exactly the way buyers are.

Start with where your customers actually ask, which for most UK businesses currently means four: ChatGPT for its sheer usage, Google AI because it now sits inside the search results your customers already see, Perplexity for research-heavy buyers and Claude in professional and technical markets. Each composes answers differently, but they lean on overlapping evidence, which is what makes one programme of work viable.

Google AI deserves particular weight because it changed the economics of ordinary searching. AI Overviews appear above traditional results for a growing share of queries, which means even customers who never open a chatbot are reading generated answers. Visibility there draws directly on your search authority, making it the platform where SEO and GEO are most obviously the same fight.

The honest guidance is not to over-optimise for any single platform's quirks. Platform-specific tricks age badly as models update, while the underlying signals, quotable content, corroborated credibility, presence on cited sources, transfer across all of them and to platforms that do not exist yet. We track per platform but optimise for the common core, deliberately.

Weighting also varies by market, and your baseline reveals yours. Consumer services see heavy ChatGPT and Google AI influence; B2B and technical purchases show more Perplexity and Claude; local trades feel Google AI most because it intercepts the searches they always lived on. The prompt research at the start of a campaign tells us where your buyers are, rather than assuming.

You need less of it than a business starting cold, which is genuinely good news, and you are more exposed than you think, which is the caveat. Strong rankings mean the sources AI systems read already include you, and campaigns for well-ranked clients typically show faster citation gains for exactly that reason. Your authority is real currency in this new market.

The exposure is that rankings and citations are correlated, not identical. We routinely baseline businesses who own page one for their core terms yet barely appear in AI answers for the same intent, because their content ranks without being quotable: comprehensive pages that never state a liftable answer, credibility implied rather than corroborated, entity signals scattered across inconsistent listings. The model read them and found nothing it could safely repeat.

There is also a defensive calculation. AI Overviews now sit above the rankings you worked for, answering a growing share of your queries before a single blue link gets clicked. When that answer names competitors, your position one earns the click of whoever scrolls past the answer, a shrinking audience. Ranking well makes that outcome more painful, not less likely.

For well-ranked businesses, GEO is mostly refinement rather than reconstruction: restructuring what already ranks so it quotes cleanly, tightening corroboration and measuring prompt-level visibility you currently cannot see. It is the cheapest GEO there is, which is precisely why doing it before a weaker competitor does it first is the rational move.

Against real answers to real prompts, tracked over time. The campaign runs on a defined prompt set, the questions your buyers actually ask, and we measure three things across it: mentions, where your brand is named in an answer; citations, where your pages are linked as a source; and share of voice, how often you appear versus named competitors across the whole set. Baseline first, movement monthly.

The tooling combines Ahrefs Brand Radar, which tracks brand mentions, citations and share of voice across AI platforms at scale, with structured manual testing for the platforms and localised prompts automation covers less well. Manual testing follows a fixed protocol, same prompts, logged dates, recorded answers, because ad-hoc chatbot screenshots prove nothing and we do not report on them.

Two honest caveats belong in any measurement conversation. AI answers vary between sessions and users, so we measure frequency across repeated sampling rather than pretending any single answer is the answer. And platforms update models without notice, so trend lines matter more than any individual month. We report the variance rather than hiding it, because a suspiciously smooth graph in this field is a fabricated one.

Alongside visibility, we track the commercial layer: referral traffic that AI platforms now send, enquiry attributions your team logs and the pipeline influenced. The industry has not settled on a standard AI attribution model yet, and we say so plainly rather than inventing a proprietary score. What we report, you can verify, which is the only kind of reporting worth paying for.

Mostly, making your content answer the way models quote. Generative engines favour pages that state things directly: what you do, for whom, where, at what cost and on what evidence. So the work restructures key pages around liftable statements, the question answered in the opening sentence, specifics beside every claim, comparisons laid out plainly, rather than the warm-up paragraphs most business websites open with.

Structure carries as much weight as wording. Clear headings that match how questions are asked, FAQ sections in crawlable HTML, schema markup that tells machines what each page is and tables where comparison is genuinely the content. A model assembling an answer under time pressure quotes the page it can parse without guessing, and parseability is a design decision.

New content targets the prompts you currently lose. If your baseline shows competitors owning "best X for Y" style answers, you need a page that is honestly the strongest available response to that question, not a keyword-stuffed imitation of one. Models are better at detecting hollow content than ranking algorithms ever were, because they read for usable substance rather than relevance signals.

What GEO never requires is writing for robots at readers' expense, and be wary of providers who suggest otherwise. The clean, direct, evidence-forward style models prefer is the same style human buyers prefer; the decades of padded SEO copy were serving neither. Every page we touch remains a page a customer converts on, because a citation that delivers visitors to unreadable content wins you nothing.

Yes, and local is quietly where some of the strongest early GEO returns are, because the question shape suits it perfectly. "Best plumber near me", "recommend a dentist in Cardiff", "who should I use for X in Y" are exactly the prompts AI assistants now answer with named businesses, and most local markets have no competitor doing deliberate work to win them. The bar is low and the answers are being set now.

Local GEO leans on assets most good local businesses already hold: a Google Business Profile, reviews, local directory presence and coverage in local press. The work makes those assets legible to models, consistent details everywhere, review responses that reinforce services and locations, content that states plainly which areas you serve, and fills the gaps, typically the absence of any page that answers the recommendation question directly.

Corroboration matters even more locally because models cross-check smaller claims more visibly. A clinic whose website, Google profile, professional register entry and local coverage all agree about its services and location reads as a safe recommendation. One whose details contradict across listings reads as a risk, and models default to omitting risks rather than flagging them.

The measurement works identically at local scale: your baseline shows which local prompts already produce recommendations, who currently gets named and which sources those answers draw on. For most local businesses that baseline is the cheapest strategic document they will commission this year, because it usually reveals a market where nobody has claimed the answers yet.

Faster than classic SEO in some respects, and the honest reason is retrieval. Where a platform fetches live pages before answering, Perplexity and Google AI most visibly, changes to your content and source coverage can surface in answers within weeks of models re-reading them. Early mentions on prompts close to your existing authority commonly appear inside the first two to three months.

The deeper positions take longer because they rest on accumulated evidence. Becoming a brand models name by default for your category, rather than one they sometimes cite when retrieval favours you, is built from corroboration across many sources over time, and no update cycle shortcuts it. Campaigns typically show meaningful share-of-voice movement by months four to six, compounding from there.

Your starting point moves both timelines substantially. A business with strong rankings, reviews and press is mostly being made quotable and corroborated, which is quick work. A business starting without authority is building the underlying evidence first, and the citations follow the foundations, exactly as rankings do. The baseline tells you which business you are before any promises get made.

Treat timing claims as a vetting test for any provider, including us. Model updates land without notice, answers vary between sessions and nobody controls the platforms, so precise delivery dates for AI visibility are fiction by definition. What can honestly be committed to is the direction and the measurement: tracked prompts, monthly movement and work redirected at whatever the data shows. That commitment we make in writing.

Nobody honestly knows, and your strategy should not require an answer. What is observable now: AI answers are absorbing a growing share of question-shaped searches, Google has put generated answers above its own results and a meaningful slice of buying research has moved inside assistants. What is equally observable: billions of searches still happen daily, and transactional and local intent still runs heavily through classic results.

The strategic point is that the question matters less than it seems, because the two futures reward the same preparation. The signals that win AI citations, authority, structure, corroboration, credibility, are the signals that win rankings, and vice versa. A business building both through one programme of work is positioned for whichever equilibrium arrives, and for the long messy middle that is actually most likely.

What has already changed, permanently, is the funnel's shape. Even customers who finish on your website increasingly started with an AI answer that framed their options, set price expectations and shortlisted names. Being absent from that framing while ranking well for the click is winning the last step of a race whose first steps eliminated you for some share of buyers.

Our position, and the way we build campaigns: treat search and AI answers as one visibility problem with two surfaces. Measure both, build the shared foundations once and let the budget follow the data on where your buyers actually are. Businesses that picked a side in previous platform shifts generally picked wrong; businesses that built durable assets generally did not.

A citation is when an AI answer links your page as a source, distinct from a mention, where your brand is named without a link. Perplexity cites in nearly every answer, Google AI links its supporting sources and ChatGPT cites when browsing. Citations matter doubly: they send measurable referral traffic, and they are the clearest public evidence that models treat your content as trustworthy enough to build answers on.

Citations are earned at the page level, which changes how you think about content. Models cite the specific page that supplied the answer, not your homepage, so a site with strong, focused pages on each question it can credibly answer collects more citations than a site with one comprehensive page trying to answer everything. Depth of coverage, page by page, is the citation strategy.

There is also a second-order effect worth understanding: citations beget citations. Pages that models cite gain traffic and visibility, which tends to earn them links and further authority, which makes them more likely to be retrieved and cited again. The compounding loop that built dominant pages in classic search is rebuilding itself around AI answers, with early positions again the cheap ones.

We track citations as a first-class metric, per platform and per page, because they are also diagnostic. Watching which of your pages models choose to cite, and for which prompts, shows you what the systems consider your credible territory, and where they still reach for a competitor instead. That map directs content work more precisely than any keyword tool.

GEO as we practice it carries no penalty risk, because everything in it is work search engines and AI platforms openly reward: clearer content, accurate structured data, consistent business information, genuine reviews and earned coverage. There is no dark pattern in making your business easier to read and verify. The same campaign that wins citations strengthens your search standing, not endangers it.

The risks live at the manipulative end of the market, and they are worth recognising before someone sells them to you. Fabricated reviews, fake listicles built to be retrieved, networks of sites corroborating invented claims and attempts to inject instructions into content for models to follow. Platforms are actively hardening against all of these, and businesses caught in the cleanup inherit the damage long after the vendor is gone.

The reputational risk runs deeper with AI than it did with search, because models remember differently. A search penalty suppresses pages; corroborated negative information about a brand can surface in answers for a long time, and contradictory or false claims a business seeded about itself can resurface as scepticism in how models describe it. Building on true, verifiable claims is not just ethics; it is the only durable strategy.

Our rule is simple and we apply it to every tactic: if the work would embarrass you when a platform documents it publicly, it does not belong in a campaign. Everything we build for GEO clients is signals they genuinely earned, made legible. That standard costs some speed at the margins and it is why the results survive model updates instead of vanishing in them.

No, and the reason is structural, not cautious: nobody controls what a generative model says, including the platforms themselves entirely. Answers vary between sessions, shift with model updates and weigh evidence in ways that are influenced rather than commanded. Any provider guaranteeing specific AI answers is guaranteeing something they cannot see, let alone control, and that tells you what their reporting will be worth.

What can be honestly committed to is the influence and its measurement. We commit to building the signals that demonstrably move AI visibility, tracking your defined prompt set continuously and reporting mentions, citations and share of voice against competitors monthly, with the movement explained. If a prompt cluster resists, you hear it from us with a revised plan, not from a competitor's citation.

The evidence pattern across campaigns is what makes the work rational despite the absence of guarantees: businesses that build quotable content, corroborated credibility and presence on cited sources appear in more answers, more consistently, over time. The variance is real between sessions; the trend under it is durable. We show clients both, because hiding the variance is how this industry will discredit itself.

Treat the guarantee question as your best vetting tool in a young market. Ask any GEO provider three things: which prompts will you track, show me a baseline you have produced for someone else and what happened to your clients' visibility after the last major model update. The confident ones answer with data. The dangerous ones answer with a guarantee.

Start with the AI visibility baseline, because everything else depends on it. We research the prompts your buyers ask, test them across ChatGPT, Google AI, Perplexity and Claude, configure Brand Radar tracking for you and your named competitors and deliver the report: where you appear, where you are absent, who owns the answers you need and which sources their visibility rests on.

That baseline is valuable whether or not you proceed, which is deliberate. It shows you, with recorded answers rather than assertions, what your customers are currently being told about your market. Some businesses discover they already hold positions worth defending; most discover specific, addressable gaps; a few discover a competitor got there first, which is its own urgency.

From the baseline, the campaign is scoped against the gaps worth most: which prompts to target, what content and credibility work they require and what the realistic timeline looks like given your starting authority. You get the plan priced against measurable objectives, not a generic retainer with AI in the title, and the scoreboard is running before the first optimisation ships.

If you already run SEO with us, GEO extends the same programme and inherits everything your campaign has built; the baseline simply adds the AI surface to your existing reporting. If you are new to us, the baseline doubles as the fastest honest way to judge whether we know this field: you will see real answers, real data and real gaps before you commit a pound to closing them.