How generative search chooses sources and what a site can do to be understood and cited.
GEO (Generative Engine Optimization) is the work of making sure AI systems — ChatGPT Search, Perplexity, Google AI Overviews, Gemini, Yandex Neuro — can find a site, understand the facts about the company correctly and use its pages as a source for answers. The foundation is the same as SEO: accessibility and indexing. On top come clear wording, verifiable facts, structured data and consistent brand information in external sources.
SEO competes for a place in a list of links; GEO competes for inclusion in a synthesised answer. A generative system extracts fragments from pages, so self-contained paragraphs whose meaning is clear without context, unambiguous facts and no contradictions between pages all matter. Many AI search engines rely on search indexes, so GEO without an SEO foundation rarely works.
No. The answer depends on how the question is phrased, the sources the system finds, region, language and model version. There is no way to buy or guarantee a recommendation, and attempts to manipulate answers — such as hidden text for bots — can backfire. What you can influence is the quality and accessibility of the sources a model draws on.
Precise service names instead of slogans, a definition in the first sentence of a section, concrete facts (prices, geography, timelines, contacts) that are identical on every page and in every language, named authors and dates, HTML accessible without JavaScript, and Schema.org markup. Contradictions — for example, different prices on two pages — make a system doubt the source.
An FAQ helps if the questions come from real customer enquiries and each answer is self-contained: a direct answer in the first sentence, then conditions and details. This matches how people ask AI assistants. FAQs made of generic definitions the model already knows, or repeated keyword-stuffed questions, are useless.
Schema.org markup (Organization, Service, FAQPage, Article) describes entities unambiguously: who the company is, which services, prices and contacts it has. Google uses it for rich results and the Knowledge Graph. There is no direct confirmation that generative systems rank by markup, so it complements clear on-page text but does not replace it.
Search where the user gets a generated answer instead of, or alongside, a list of links. The pattern (RAG): the system finds relevant pages, extracts fragments and composes an answer from them, often citing sources. Examples are ChatGPT Search, Perplexity, Google AI Overviews and AI Mode, and Yandex Neuro. For a site it is both a new channel and a risk of losing clicks.
Build a fixed set of control queries — 30–100 questions customers ask, by market and language. Run them on a schedule under the same conditions and record the system and version, date, region, whether the brand is mentioned, whether the facts are correct and which sources are cited. Only like-for-like samples are comparable — a single answer proves nothing.
Cases where an AI system names a page of your site as the source of an answer — as a link or footnote. A citation brings visits and trust, but it differs from a mention: a model can name your brand while citing someone else's review. Citation depends on the product (Perplexity almost always links, a chat without search does not) and on whether the page directly answers the question.
Yes. AI systems cite what they can read: open HTML without login, without bots blocked in robots.txt or a WAF, without content locked in PDFs or images. Check that OAI-SearchBot, PerplexityBot, Googlebot and YandexBot get a 200 response, not a CAPTCHA. Openness is a necessary condition, not a guarantee of inclusion.
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