So that ChatGPT, Gemini and AI Overviews cite your brand.

AI optimization for search systems, more precisely AI visibility optimization, builds content, technology and entity data so that AI search systems like ChatGPT, Gemini and the Google AI Overviews mention and cite the brand. The method is called GEO (Generative Engine Optimization) and targets the generated answer, not the classic list of results.

Four names, one goal: appear in the generated AI answer instead of only in the list of results. GEO stands for Generative Engine Optimization, GAIO for Generative AI Optimization, LLMO for Large Language Model Optimization, AEO for Answer Engine Optimization. I work consistently under the term GEO, because it has become established in the DACH region.

Text tools like ChatGPT, Jasper or Copy.ai produce text, but no citation. Two other things are decisive: measurement, for which I use Peec.ai, and structure that a model can extract. To get started there is the Excel workbook from the prompt library and the open GEO Share of Voice Monitor from my lab.

No. Without crawler access and clean indexing, no AI system reaches your page, and what it cannot reach it cannot cite. Technical SEO is the foundation on which GEO works at all. If the foundation is not in place, the first step is an SEO project, not a GEO project.

First movement often builds up within weeks to a few months; my own fintech project went from zero to around 33 percent in 90 days. But it only becomes reliable with ongoing work. GEO is monthly work, sensible from six months on, because the engines change constantly and a single hit is not yet a stable signal.

The entry point is the GEO audit: a fixed package, a fixed time frame, terms on request. The ongoing implementation runs through the GEO program on a monthly cadence. I deliberately do not state a price, because scope and number of markets determine it. The business case calculates three scenarios in two minutes.

AI visibility is the share of AI answers in which your brand is mentioned or cited as soon as a buyer asks a purchase question. It is the result, GEO the path there. It is measured per engine and per prompt, not as a single overall number, because ChatGPT, Perplexity and the AI Overviews answer differently.

Classic marketing fights for a spot in the list of results or an ad that the user still goes through themselves. AI visibility is decided one level earlier, in the text the model outputs finished. The buyer often sees only this one answer and the two or three brands in it. Rank and ad help only to a limited extent at this point.

Content is the substance a model cites from. Without content that answers a purchase question clearly and with evidence, there is nothing to mention. The form is decisive: the answer in the first sentence, a clean structure, verifiable facts. Pure text output without this substance produces not a single citation.

Across three levels. The citation rate and the visibility index per engine show how often your brand appears in a fixed prompt set, measured against the competition. Referral traffic from AI domains shows the direct crossovers to your page. And the trend of branded and direct search shows the indirect effect that the mentions push along.

Strongest in the middle and at the bottom, with comparison and decision questions. Prompts like "best alternative to X" or "which provider for Y" lead directly to the shortlist, and there a mention decides the inquiry. At the top of the funnel, with broad awareness, GEO also works, but is harder to attribute to a specific inquiry.

On two levers, never on the third. I work on your website, on structure, schema and crawler access, and on your signals outside the page, on third-party sources, Wikidata and reputation. Closed models like ChatGPT cannot be retrained from the outside by anyone. Whoever promises that is selling an illusion. I shift the probability of a mention with evidence, at the places the model reads.

That depends on where the answer comes from. What an engine pulls live from the web, for example Perplexity, the Google AI Overviews or ChatGPT with search, updates with the next crawl, often within days to a few weeks. What is fixed in the model changes only with a new training state, so over months. That is why I start with the retrievable sources first.

Not necessarily. GEO stands on the same technical foundation as SEO; part of the work pays into both channels at once. Ads buy attention for the moment, GEO builds a position that stays. In practice it is its own line item that supports the existing channels instead of taking something away from them.

The brands that are cited today become the default answer, and this position reinforces itself: every mention is a signal that makes the next one more likely. Whoever only starts once the competition is established there works against a head start. How big it turns out depends on your industry. The direction is certain, not the number.

GEO does not buy clicks. It gets your brand onto the shortlist when the buyer decides in the AI interface. I make the value visible through three approaches: the direct referral traffic from AI domains like perplexity.ai or chatgpt.com; the indirect effect, that is the parallel rise of branded and direct search during the GEO work; and the visibility index across a fixed set of 50+ purchase prompts (sometimes called Share of Model), which shows in what percentage of scenarios you appear. Together they give a solid picture, even without perfect one-click attribution.