Generative Engine Optimization

In the past, if you wanted to know something, you typed it into a search engine and got a list of links. Today, many people instead ask their question to a chat program like ChatGPT and receive a fully formulated answer text. This text often includes a few sources or products — and quite many others simply don’t appear. This is exactly what Generative Engine Optimization is about: companies try to get their own website, brand, or product into such AI answers. The English term literally means “optimization for generating machines,” because these programs generate answers anew themselves instead of just showing links. The discipline is abbreviated as GEO.

From the blue link to the single answer

With a classic results list, there are ten spots on the first page. Someone ranking seventh gets little traffic, but at least something. An AI answer, on the other hand, might name three sources, sometimes none at all. This makes competition harsher: either you get mentioned, or you’re invisible.

For companies, a lot of money is at stake here. Online shops, travel portals, and comparison sites depend on people landing on them through search queries. If the AI answers the question directly, nobody clicks through anymore. Experts call this “zero-click,” meaning search without a click. Some media companies already report significantly fewer visitors from search.

For this reason, an entire market has developed around GEO within just a few years. Agencies sell consulting, software providers sell measurement tools. And because stock markets closely watch how search engines' advertising revenues develop, the term also shows up in financial news.

What chatbots prefer as a source

AI answer services usually work in two stages. First, they search the web for suitable pages, then the language model summarizes the texts found. A language model is a program that has learned to predict sentences word by word. Anyone who wants to be visible must therefore clear two hurdles: being found, and then also being cited.

For the second hurdle, how a text is structured matters most. Clear subheadings, short paragraphs, and direct answer sentences are easier to extract than convoluted promotional prose. Concrete numbers, dates, and named experts also help, because they appear citable. A sentence like “Admission costs 12 euros” is more useful for a model than “fair prices for every budget.”

It also matters what is stated outside one’s own website. Models often rely on forums, review platforms, news sites, and encyclopedias. A brand that is mentioned frequently and consistently there also appears more often in answers. GEO can therefore be understood less as a bag of tricks and more as work on one’s own reputation across the entire web.

GEO in everyday life and in job ads

You notice GEO indirectly on your own phone. If you ask an AI about good running shoes, it usually names a handful of brands and reviews. This selection is no coincidence, but the result of visibility on the web — and some providers actively work on it. A disclosure that a recommendation was paid for is typically missing.

The term has already arrived in the world of work. Job ads seek “SEO/GEO managers,” and tools measure how often a brand appears in ChatGPT, Perplexity, or Google AI answers. Such figures are called “share of voice,” meaning the proportion of mentions.

A common misconception is that GEO is something entirely new and replaces old-school search engine optimization. In fact, many AI services still use normal search results as their basis. Anyone invisible there is also barely cited by the AI. GEO is therefore more of an extension than a replacement — with the difference that, in the end, what often results is not a click, but merely a mention.