Where does the term GEO come from?
GEO stands for Generative Engine Optimization. Pranjal Aggarwal and colleagues introduced the framework in a paper first submitted in November 2023 and accepted at KDD 2024. It examines ways to measure and improve visibility in generated answers. Its experimental results are not a promise of the same effect for a particular business or current AI product.
How is GEO different from SEO?
SEO helps people find your pages in search results. GEO also asks what an AI answer says about your organisation, whether it mentions competitors, and which sources it links to. The two overlap: useful content and sound technical SEO support both.
The distinction is in the questions you ask and the outcomes you measure. A brand can be mentioned without a link; a page can be cited without attracting a visit. Neither event, on its own, proves that the business gained a qualified enquiry.
| Question | What to examine |
|---|---|
| Are we represented? | Brand mentions, factual accuracy and positioning in the answer. |
| Are our pages used as sources? | Linked citations and the pages or domains cited. |
| Does that help the business? | Identifiable referral traffic, useful visits and qualified enquiries. |
How do AI systems choose what to cite?
In a search-enabled experience, a system can look up sources to help answer a question. It may reformulate the question, retrieve pages and draw on passages from several sources. The details depend on the product, configuration, language and query; there is no universal public formula for earning a citation.
That makes the actual answers your starting point. Inspect which organisations appear, what the answer says, and whether the cited pages support it. Recurring patterns can suggest work worth testing; one favourable answer is not a stable position.
Google AI Overviews and AI Mode are AI features within Google Search, distinct from the Gemini app. AI Overviews can add an AI-generated summary to a results page; AI Mode supports exploratory questions and follow-up searches. Their responses and citations can differ, so observations should identify the exact search experience. A result in one is not evidence of visibility in the others.
What makes a page useful for AI search?
Make the page useful to a buyer first. Answer a specific question clearly, support factual claims, and give readers enough context to understand who is speaking and why the information matters.
- Put the direct answer near the start, with useful detail below it.
- Use descriptive headings, semantic HTML, and lists or tables when they clarify the subject.
- Give important facts a source and label examples so they cannot be mistaken for client results.
- Keep names, services, locations and author information consistent across relevant pages and profiles.
- Keep important content accessible without requiring an interaction to reveal it. Check how the relevant crawlers receive rendered content.
- Use accurate structured data that matches the visible page, and update dates when the content actually changes.
These are practical content and accessibility principles, not a promise of citations. Google says its AI Search features require no special schema or additional technical optimisations beyond the relevant Search requirements.
How do crawler controls affect AI search?
Check both robots.txt and the response the crawler receives from your server or CDN. An allowed URL can still be blocked by a challenge, return an error, or hide its useful content behind a rendering step.
Search retrieval and model training are different uses. Googlebot is relevant to Google Search, including its AI features. Google-Extended controls certain Gemini training and grounding uses; it does not govern inclusion in Google Search. Other providers also distinguish search, training and user-requested access. Check the current documentation for each product before changing access rules.
How do you measure GEO?
Start with the questions your buyers actually ask. Agree a panel that covers the relevant decisions, then keep enough of the method stable to make repeated observations meaningful. A prompt panel is a sample of questions, not a census of all AI searches.
- Record the audience, language and market separately.
- Identify the engine, product or API configuration, date and relevant settings.
- Repeat observations because answers can change between runs.
- Count mentions and linked citations separately, showing the denominator and recording failed runs.
- Retain responses and source links so someone else can inspect the findings.
- Compare identifiable referral traffic and enquiries separately; do not treat every mention as a visit or a sale.
For example, a panel could cover 30 buyer questions, three agreed AI configurations and three observations per question and configuration. That gives 270 planned responses per language/market combination. Report the usable responses and failed collections explicitly. An API test should be labelled as such rather than presented as a measurement of the consumer app.
Coverage is agreed for the market and question: typically ChatGPT, Gemini and Perplexity. The exact product, mode and collection method are recorded; consumer apps and APIs are assessed separately.
What does a useful diagnostic lead to?
Consider an illustrative situation: competitors appear repeatedly when buyers ask about a specialist service, while your brand appears mainly in questions that already name it. That is a visibility gap to investigate, not proof that a single page change will fix it.
The next step is to inspect the cited sources and your own pages. Is the service explained clearly? Does the local-language page answer the buyer’s question? Are relevant pages reachable? Do external sources describe the business accurately? The action plan follows those checks, with each recommendation tied to evidence and a way to reassess it.
Does GEO work across languages and markets?
AI visibility can be investigated in every language relevant to your buyers. The useful comparison is between equivalent commercial intents, not simply the same sentence passed through a translation tool. Competitors, vocabulary and cited sources may differ between markets.
Language is not a substitute for geography. French in France, Belgium and Switzerland can involve different services, regulations and buying expectations. Define the market explicitly and review the prompts with that context in mind.
I work in English, French, Italian and Spanish. A multilingual diagnostic compares the agreed combinations and prioritises local work where the evidence supports it. Whether authority carries across languages is something to measure; a smaller language market is not automatically easier.
Where should an organisation start?
Choose one business question, one priority market and a team able to act on the findings. Capture a baseline before making changes, then address the clearest accessibility, factual or content gaps.
Keep a record of interventions and repeat the observations. Changes in answers can also reflect product updates, competitor activity or sampling variation, so improvement after an edit is not automatically proof that the edit caused it. A useful report makes those limits clear while still giving you decisions to take.