Generative engine optimisation, done honestly.
Generative engines no longer hand your buyers a list of links. They write an answer, and name a few sources. Generative engine optimisation is the work of making yours one of them.
Generative engine optimisation (GEO) is the practice of making your business the source that generative engines, such as ChatGPT, Google AI Overviews, Perplexity and Gemini, synthesise and cite when they answer a question in your category. It shares SEO's entity and structured-data foundation but targets the passage a model quotes rather than the link a person clicks. We measure it in citation share and assisted pipeline, never in guaranteed placements.
Generative engine optimisation, in full.
The term generative engine optimisation comes from 2023 research that studied how large language models choose which sources to weave into a generated answer. The finding that matters commercially is simple: generative engines do not rank ten links and step back. They read the strongest sources, write a single synthesised response, and credit a handful of them. If your business is not in that handful, you are invisible at the exact moment a buyer is forming a shortlist.
GEO is the discipline of influencing that outcome. It sits under answer engine optimisation as the broad, cross-engine layer: where our per-assistant pages tune for how one surface behaves, GEO is the shared method that makes you eligible to be synthesised and cited wherever the answer is generated. The foundation is the same entity and structured-data work that underpins good SEO, but the target moves from the ranked link to the quoted passage, which changes how content has to be written and structured.
Two honest constraints shape everything we do here. First, nobody controls what a model outputs, so no agency can guarantee a citation, and any that promises one is guessing. What we can do is move the inputs the engines demonstrably use, and measure the result against your own set of buying questions. Second, GEO is premature without something worth citing. If you have no structured data, no authority and no reference content, there is nothing for a model to synthesise, and we will tell you to start with SEO rather than sell you GEO you are not ready for.
The pay-off, when the foundation is there, is being the named source in the answer your market trusts by default. That is durable in a way a paid slot is not, and it compounds: every corroborating reference and every clean entity signal makes the next citation more likely.
Generative engine optimisation, broken down.
Entity and citation baseline
We establish where generative engines currently source your category and who they credit today. That honest starting line is what every later gain is measured against, and it usually reveals which competitors have quietly become the default answer.
Explore →Technical legibility
Clean, semantic HTML, fast pages, valid schema and content that renders without heavy JavaScript, so a model reads your facts rather than skipping a page it cannot parse. This is the least glamorous and most decisive layer.
Explore →Answer-surface mapping
The 40 to 120 questions your buyers actually put to machines, scored by commercial value, so the work targets the queries that move pipeline rather than vanity phrasings nobody asks.
Source-worthy content
Reference pages, definitions and original data written to be extracted and quoted, with the answer stated plainly near the top. Content built to be synthesised, not only to rank on its own.
Corroboration and authority
Digital PR and citations in the publications generative engines already trust in your sector, because a claim repeated by credible sources is one a model will repeat too.
Explore →AI Overviews and the assistants
The same foundation aimed at each surface your buyers use, from Google's AI Overviews to ChatGPT, Perplexity and Gemini, tuned to how each one sources and cites.
Explore →The way we run Generative engine optimisation.
Baseline the answers
We run your priority questions across the major generative engines and record what they say, who they cite and where you sit today. No projections, just the current state of the answer.
Fix what blocks legibility
We clear the technical and structural issues that stop a model reading you cleanly: rendering, schema, entity consistency and page speed. This is the foundation the rest depends on.
Map and prioritise the surface
We build the scored map of buying questions, then decide which answers are worth competing for first based on commercial value and how winnable each one looks.
Build the source material
We write and structure the reference content and primary data the engines can quote, with the extractable answer up front and the entity signals a model needs to attribute it to you.
Earn corroboration
We pursue the coverage, mentions and citations in trusted sources that make an engine confident enough to name you, without buying links or pitching stories we cannot stand behind.
Track share of answer
We report citation share question by question, month by month, so you see movement honestly, whether it is up or down, and we adjust where a surface is not responding.
How we approach Generative engine optimisation.
Make you machine-legible
Generative engines can only synthesise what they can parse. We fix the rendering, structure and schema that keep a model from reading your pages cleanly, so your facts survive the summarisation.
Give the model something to quote
Answers written up front, primary data, clear definitions and reference pages built to be lifted verbatim. If the passage is easy to extract and hard to argue with, it gets used.
Consolidate the entity
One consistent identity across your site, Companies House, Wikidata-grade references and the directories, so engines know who you are, what you do and do not confuse you with a competitor.
Earn the corroboration
Models trust claims that credible third parties repeat. We build the coverage and citations in sources the engines already lean on, so they are confident enough to name you.
What Generative engine optimisation puts on your desk.
Who does the work, and how
Rogue Logic is the trading name of Bryley Ltd. GEO is run by four senior practitioners with around forty years of combined experience between them, and there are no juniors on your account. The work is deliberately unglamorous and evidence-led: we move the inputs generative engines actually use and we report the outcome against your own questions, up or down, rather than pointing at a dashboard of impressions.
Senior practitioners only
The person who audits your entity and writes your source material is the person you speak to. No account-management layer, no learning on your budget.
Inputs we can influence, measured honestly
We optimise the structured data, content and corroboration the models rely on, and track citation share question by question. We never guarantee a placement, because no one can.
Foundation-first standards
If there is nothing worth citing yet, we say so and start with SEO. GEO only earns its place once the entity, content and authority are there to build on.
Generative engine optimisation: common questions.
What is generative engine optimisation?
Generative engine optimisation, or GEO, is the work of becoming a source that generative engines like ChatGPT, Google AI Overviews, Perplexity and Gemini synthesise and cite when they answer a question in your category. It builds on the same entity and structured-data foundation as good SEO, but targets the quoted passage rather than the ranked link.
Is GEO the same as AEO or SEO?
They overlap and share a foundation. SEO optimises for ranked links. AEO is becoming the cited source in an answer. GEO is the broad, cross-engine layer of AEO that focuses specifically on engines which generate a written answer. In practice we run them together, because the underlying entity and structured-data work serves all three.
Can you guarantee we appear in ChatGPT or AI Overviews?
No, and anyone who guarantees it is not being straight with you. No one controls what a model outputs. What we can do is move the inputs the engines actually use, make you the most citable option, and measure the movement against your real buying questions over time.
How do you measure GEO if there are no rankings?
We track a defined set of your buying questions across the major generative engines and record, question by question, whether you are cited, a competitor is, or nobody is. That share of answer, tied to assisted pipeline, is the measure, reported monthly whether it moves up or down.
How long before it works?
Technical and structural gains can surface within a few weeks once a model re-reads your pages. Citation gains that depend on authority and corroboration typically build over a quarter or two. We baseline first so any movement is measured against a real starting point, not a guess.
Do our Google rankings help with generative engines?
Usually, yes, indirectly. Strong SEO tends to mean the crawlable, structured, authoritative content generative engines favour. But the target differs, so content has to be written to be extracted and quoted, and some engines lean on indexes and sources that classic rankings do not fully cover.
How much does GEO cost?
It runs as part of a combined SEO and AEO retainer, which starts from £1,500 per month. We rarely sell GEO on its own, because without an SEO and authority foundation there is little for a model to cite and it would be premature.
Which generative engines do you cover?
ChatGPT, Google AI Overviews, Perplexity and Gemini as standard, with others such as Google's AI Mode or Copilot added where your buyers actually use them. We tune the shared foundation to how each surface sources and cites.