What does GEO stand for?

GEO stands for Generative Engine Optimisation. It is the practice of making an organisation's information retrievable, accurate and citable by generative AI systems such as ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews.

How is GEO different from SEO?

SEO optimises pages to rank in a list of results. GEO optimises an entity and its sources so that an AI system retrieves your information and names you when synthesising an answer. SEO is measured by position and clicks; GEO is measured by share of answer, citation rate and whether the facts returned about you are accurate.

Why does an AI assistant describe our company incorrectly?

Usually because it retrieved an outdated or inaccurate source. Common culprits are stale directory listings, old press coverage, abandoned social profiles and inconsistent descriptions across your own pages. The fix is to identify the likely source and correct it there, then make your canonical description consistent everywhere.

Can GEO work for a company with no existing brand recognition?

Partly. Structural and consistency work will make a small company retrievable for specific, narrow questions where competition is thin. Broad category questions will still favour established names. The realistic strategy for a smaller organisation is to target specific questions it can genuinely answer better than anyone else.

How do you measure GEO performance?

Against a recorded baseline of verbatim AI responses to a defined set of buyer questions. We track whether your brand appears, whether it is cited by name, whether the facts are accurate, and which competitors appear instead. Because retrieval varies between sessions, each prompt is sampled repeatedly rather than checked once.

Generative Engine Optimisation (GEO) Services | OMAV Technology

Generative Engine Optimisation (GEO)

Generative Engine Optimisation is the practice of structuring an organisation's published information so generative AI systems such as ChatGPT, Claude, Gemini and Perplexity retrieve it, represent it accurately, and cite it when answering related questions. OMAV delivers GEO through entity definition, source authority development, factual consistency auditing and ongoing prompt monitoring.

Generative Engine Optimisation

Being the source a generative engine reaches for

Generative Engine Optimisation is the practice of structuring an organisation’s published information so that generative AI systems retrieve it, represent it accurately, and cite it when answering related questions. It operates at the level of the entity and the source rather than the individual page.

The mechanism matters. When someone asks an assistant a commercial question, the system typically runs one or more retrieval queries, pulls a set of candidate sources, and synthesises an answer from the passages it considers most relevant and reliable. Your organisation appears in that answer only if it was retrieved, only if the retrieved passage was clear enough to use, and only if the system considered the source worth naming.

GEO addresses all three conditions. Retrieval depends on crawlability, indexation and topical authority. Usability depends on how unambiguously your content states things. Attribution depends on whether you are recognisable as a distinct, credible entity rather than an anonymous page.

Scope

What generative engine optimisation covers

GEO is a programme rather than a checklist. These are the workstreams that make up a typical engagement.

Entity definition and disambiguation

Establishing one canonical description of your organisation: legal name, alternate names, identifiers, location, services, and what you are notably good at. Then making that description consistent everywhere a model might encounter it.

Source authority development

Earning accurate mentions on sources that are themselves frequently retrieved: industry publications, professional directories, partner sites, standards bodies. A correct description on a trusted third-party source carries more GEO weight than a link on a weak one.

Factual consistency auditing

Finding and correcting places where your own materials contradict each other. Conflicting service names, outdated addresses, three different descriptions of the same offering: each of these lowers a model’s confidence in describing you.

Retrieval-friendly content structure

Ensuring the passages a model would want are complete, self-contained and unambiguous, so extraction does not distort them. Covered in depth by the Answer Engine Optimisation service.

Prompt and share-of-answer monitoring

Tracking a defined set of buyer questions across ChatGPT, Claude, Gemini, Perplexity and AI Overviews. Recording who appears, who is cited, and whether the facts returned about you are correct.

Correction of inaccurate representations

When a model states something wrong about your organisation, identifying the likely source and correcting it there. This is often an outdated directory listing or a stale third-party article rather than anything on your own site.

Method

How a GEO engagement runs

STEP 01

Baseline

Run the priority buyer questions across each AI system and record verbatim responses. This becomes the reference point for everything after.

STEP 02

Entity audit

Map every place your organisation is described, on your site and off it. Identify contradictions, gaps and stale information.

STEP 03

Fix the source of truth

Establish the canonical description, implement it in schema, and align the site’s own copy with it.

STEP 04

Propagate

Correct third-party sources, publish the material that fills genuine gaps, and pursue mentions on retrievable sources.

STEP 05

Re-measure

Re-run the baseline prompts on an agreed cadence and report movement against the recorded starting point.

Comparison

GEO next to the disciplines it is confused with

How GEO differs from SEO and AEO
Dimension	Traditional SEO	AEO	GEO
Unit of work	The page	The passage	The entity and the source
Goal	Rank in a results list	Be the extracted answer	Be retrieved and cited by name
Primary lever	Relevance and links	Structure and clarity	Authority and consistency
Measured by	Position, clicks, impressions	Snippet and answer capture	Share of answer, citation rate, factual accuracy
Typical output	Optimised pages	Structured passages and markup	Consistent entity across all sources
Time to effect	2 to 6 months	Weeks to 2 months	3 to 9 months

Limits

What GEO cannot do

Model providers do not publish their retrieval or citation logic, and they change it. Two identical prompts issued minutes apart can return different sources. Any measurement of AI visibility is therefore a sample rather than a rank, and should be reported as one.

GEO also cannot make an organisation authoritative that has nothing to be authoritative about. If a company has no differentiated capability, no published expertise and no third-party recognition, the honest recommendation is to build some of that first. Structuring an empty claim more clearly does not make a model repeat it.