What is Generative Engine Optimization?
Generative Engine Optimization (GEO) is the practice of improving how often and how favorably your brand appears in answers written by AI models such as ChatGPT, Gemini, Perplexity and Google AI Overviews. The goal is not a ranking position but a place inside the answer itself: as a mention, a citation or a recommendation.
The name comes from a 2023 research paper by researchers from Princeton University, Georgia Tech, the Allen Institute for AI and IIT Delhi, which tested how changes to a web page affect its visibility in generated answers. GEO has since become the common label for all work aimed at earning AI visibility.
GEO overlaps with two related disciplines. Answer Engine Optimization (AEO) focuses on becoming the direct answer to a specific question, while LLM optimization looks at what language models know about your brand. GEO is usually the umbrella term: it covers the complete answer a generative engine assembles from many sources, including which brands it recommends and how it describes them.
Why Generative Engine Optimization matters for your brand
A search engine shows a list of links; a generative engine writes one answer. That answer compares options, summarizes reviews and names a handful of brands, often without the user visiting a single website. Brands left out of the answer do not rank lower. They are simply absent.
Strong SEO does not guarantee a place in these answers. AI models combine search results, what they learned during training and third-party sources such as reviews and comparison articles. A page can rank first on Google while AI answers recommend your competitors.
How to get started with GEO
GEO works best as a loop of measuring, improving and measuring again:
Map your prompts. List the questions buyers ask in your category, such as "best payroll software for small businesses", and check which brands AI models name.
Measure your baseline. Track mentions, citations, sentiment and share of voice per model, because ChatGPT, Gemini and Perplexity often give different answers.
Make your content easy to quote. Answer questions directly, use specific facts and keep product pages accurate and crawlable.
Build presence on third-party sources. Reviews, comparison articles, industry media and community discussions help decide which brands a model recommends.
Measure again and adjust. AI answers change often, so judge progress on weekly trends instead of a single screenshot.
The seven GEO metrics that matter make a compact scorecard. Trackbase runs your prompts daily across 11 AI models and turns the results into prioritized actions for GEO optimization.
Examples of Generative Engine Optimization
A Dutch bicycle webshop sees that ChatGPT recommends two competitors for "best e-bike for commuting". It publishes a comparison guide with clear specifications and prices and works to get included in independent e-bike reviews.
A B2B payroll software vendor finds that Perplexity quotes outdated prices and updates its pricing page and help center so the facts are consistent everywhere.
A marketing agency adds GEO reporting to its SEO retainer and tracks a client's share of voice against five competitors in ChatGPT, Gemini and Google AI Overviews.
A hotel group rewrites its FAQ pages so each answer starts with one direct, self-contained sentence that AI assistants can quote.
Frequently asked questions
Is GEO replacing SEO?
No. GEO builds on SEO instead of replacing it. Many AI assistants look up pages in a search index before answering, so the SEO basics of crawlability, structure and authority still count. GEO adds new goals on top: being mentioned, cited and described accurately inside AI answers, and measuring that across several AI models.
Which AI platforms does GEO cover?
GEO applies to every system that writes answers from multiple sources. That includes chat assistants such as ChatGPT, Claude and Gemini. It also includes answer engines such as Perplexity and search features such as Google AI Overviews and AI Mode. Each platform draws on different sources, so a brand can be visible in one and missing in another, which is why results should be measured per platform.
How long does GEO take to show results?
It depends on the platform. Assistants that search the web can pick up a new or updated page once it has been crawled and indexed, while knowledge built into a model only changes when the model is retrained. That is why teams track AI answers daily and judge progress on weekly trends rather than single answers.