What is GEO (Generative Engine Optimization)

GEO encompasses all the technical, content and authority actions that maximise a brand's presence in generative engines. It includes how content is structured for easy synthesis, the creation of verifiable facts and data that the model can quote, presence in sources LLMs already consider trustworthy (Wikipedia, Wikidata, reference media) and the continuous monitoring of how engines respond to relevant prompts.

Unlike AI advertising (which some engines are starting to test through sponsored slots), GEO is organic: it works to have the model pick you on merit. That makes it a defensible asset, not a recurring pay-per-click cost.

To understand GEO you need to understand how a generative engine builds an answer. When a user asks something, the system combines two layers: the information already baked into the model's weights (pre-training) and, increasingly, a real-time retrieval layer (RAG, Retrieval-Augmented Generation) that pulls fresh web sources before drafting the response.

The model's output typically includes a natural-language synthesis and, in many cases, explicit citations to the sources consulted. Those citations are the goal of GEO: being among the pages the engine selects as its basis, and being mentioned by name inside the generated text.

An effective GEO strategy works in parallel on several fronts. Content must be clear, easy to synthesise and focused on answering concrete questions. Brand authority is built through mentions in sources the models trust. And technical presence (structured data, accessible sitemap, content renderable without JavaScript) makes it easier for LLM crawlers to read you.

Beyond technical levers there is a strategic component: identifying the prompts that truly matter in your industry and understanding which sources dominate those answers today. Without that baseline, every action runs blind.

SEO optimises pages to rank well in Google and capture traffic. GEO doesn't chase direct traffic: it chases presence. Its success is measured in mentions, AI share of voice and citation accuracy, not in clicks. That changes priorities: deep, technical URLs may never rank in SEO but can still be cited if they contain well-structured, verifiable data.

The levers also shift. In classic SEO, domain authority and backlinks are decisive; in GEO, what matters is how often your brand appears as a trustworthy source and the consistency between sources that talk about you. That forces SEO, digital PR and branding to merge into a single strategy.

Measuring GEO is more complex than measuring SEO because there is no official Search Console for LLMs. The usual practice is to define a set of prompts representative of your industry and run them periodically across engines, logging whether your brand appears, in what position within the answer and whether the statements are accurate.

Dedicated tools (Otterly, Profound, AthenaHQ, Peec AI) automate that tracking and let you compare your share of voice against competitors. The most useful metric is usually the "inclusion rate": the percentage of prompts in which the model mentions you as a source or example.

GEO is not an alternative to SEO: it's a strategic complement. If your brand relies heavily on informational, comparative or recommendation queries ("best X for Y", "alternatives to Z", "how to choose A"), investment becomes mandatory. If your organic traffic comes mostly from brand or navigational queries, urgency is lower but it's wise to start.

The first step is usually a light GEO audit: identify the 20-30 most relevant prompts in your sector, see where you are cited today and design a six-month improvement plan. From there, GEO becomes one more layer of the digital visibility strategy.