Just a couple of years ago, the question was «what position do you rank in on Google?». Today, more and more users do not even open a traditional search engine: they ask ChatGPT, Perplexity, or Google’s AI assistant directly which product to buy, which agency to hire, or which solution to use. And the answer they receive is not a list of ten blue links, but a written recommendation, with (or without) brands cited within it.
That recommendation is the new «number one result.» And the discipline focused on getting your brand to appear there is called GEO: Generative Engine Optimization, or optimization for generative engines.
What Is GEO (Generative Engine Optimization)
GEO is the set of practices designed to get generative search engines — ChatGPT, Gemini, Perplexity, Copilot, Claude, Google AI Overviews — to mention, cite, or recommend your brand when a user asks them a question related to your industry, products, or services.
Unlike traditional SEO, where the goal is to occupy a position on a search results page, the goal of GEO is to be the source that the language model decides to use (and cite) to build its response. The user does not click through ten links and compare them: they read a synthesized answer and, at best, click on one or two cited sources. If your brand is not among those sources, it is as if you do not exist for that user.
The term GEO began gaining popularity in 2024, following academic research (such as the «GEO: Generative Engine Optimization» paper from Princeton, Georgia Tech, and other universities) demonstrating that there are measurable tactics for increasing the likelihood that a model will cite a specific source. Since then, agencies and marketing teams around the world have started treating it as a discipline of its own, with specific methodologies, metrics, and tools.
Why GEO Is No Longer Optional
Three data points explain why GEO has become a priority:
- Search traffic is shifting toward conversational AI. More and more informational and commercial queries — especially comparison («best X for Y»), recommendation («which agency…»), and problem-solving queries — are being resolved within a chat, without going through a traditional results page.
- Google is already integrating generative AI into its own results. AI Overviews appear above traditional organic results for a growing share of searches, which means that even if you do «perfect» SEO, you can remain invisible if you are not also optimized for the generative layer.
- Trust in AI recommendations is growing. Users increasingly treat these responses as a neutral advisor, giving them greater decision-making weight than a simple search result.
For a brand, this means that the digital «first impression» no longer happens only on a SERP: increasingly, it happens within a conversation with an AI model. If that model does not know you, does not understand you correctly, or does not trust your sources, it simply will not mention you.
GEO, SEO, and AEO: Are They the Same?
It is common to confuse these three terms, so it is worth clarifying them here (and we go deeper into this in the dedicated SEO vs GEO vs AEO article):
- SEO (Search Engine Optimization): optimizing to appear in traditional organic search results on search engines such as Google or Bing.
- AEO (Answer Engine Optimization): optimizing content so that it is selected as a «direct answer» in featured snippets, voice assistants, or answer panels.
- GEO (Generative Engine Optimization): optimizing so that generative AI language models cite, mention, or recommend you within a synthesized, conversational response.
In practice, GEO and AEO share many fundamentals (clarity, structure, authority), and both rely on a solid technical SEO foundation. They are not mutually exclusive disciplines, but rather layers built on top of one another. That is why at Merissel we talk about a «total visibility» strategy: SEO as the foundation, AEO as the bridge, and GEO as the newest and fastest-growing layer.
How AI Models «Read» Your Brand
To optimize for GEO, you need to understand, at least broadly, how a model decides which sources to cite. There are two main mechanisms:
- Trained knowledge (parametric knowledge): what the model «learned» during training about your brand, based on everything that has been written about you on the internet. The consistency and volume of mentions of your brand over time carry significant weight here.
- Real-time retrieval (retrieval): models such as Perplexity, Copilot, or Google’s AI Overviews perform live searches and cite specific pages. Here, factors very similar to technical SEO matter: crawlability, structured data, semantic clarity, and page authority.
This means that a complete GEO strategy works on two fronts at once: building a coherent brand entity that the model recognizes as an authority in its training, and producing technically citable content that the model can retrieve and reference in real time. We explore the first front in our article on entity optimization, and the second in our article on schema markup and structured data.
The Pillars of a GEO Strategy
A solid GEO strategy is built on six pillars that we explore in depth throughout the rest of this content cluster:
- Entity optimization. AI does not read isolated pages; it reads brands as entities within a knowledge graph. The more consistent your website, profiles, press mentions, and reviews are, the easier it is for the model to understand and cite you with confidence.
- E-E-A-T signals. Experience, Expertise, Authoritativeness, and Trustworthiness remain the framework that both Google and generative models use to decide whom to trust.
- Structured data and technical accessibility. Schema markup and a properly configured robots.txt can make the difference between being invisible to an AI crawler and becoming a recurring source.
- Platform-specific presence. ChatGPT, Perplexity, and Google AI Overviews work differently and reward different signals.
- Measurement and monitoring. Without data on how often and how AI mentions you, there is no way to know whether your strategy is working.
- Avoiding common mistakes. Some tactics seem logical but can actually hurt your visibility in AI.
In addition, GEO does not apply equally to every type of business: if you have a physical business, our guide to GEO for local businesses is especially relevant, and if you sell to other businesses, check out GEO for B2B and SaaS.
Where to Start
If you are getting started with GEO, the recommended order is:
- Audit your current situation. Ask ChatGPT, Perplexity, and Gemini yourself about your industry and check whether they mention you, how they describe you, and whom they cite instead of you.
- Review technical access. Make sure your robots.txt is not unintentionally blocking GPTBot, PerplexityBot, or other AI crawlers.
- Strengthen your brand entity. Make sure your name, description, and key information are consistent across your website, social media, directories, and press coverage.
- Add structured data. Implement schema markup on your most important pages.
- Create citable content. Clear content with specific data, well structured around questions and answers, and supported by verifiable sources.
- Measure and adjust. Establish a recurring process for monitoring mentions in AI.
GEO Does Not Replace SEO: It Complements It
One important idea to close this guide: GEO is not a trend that replaces SEO. It is an additional layer of visibility built on the same foundations — quality content, authority, and technical expertise — but with its own nuances. The brands that win the next decade of digital search will be those that understand they are no longer competing solely for a click in a list of links, but for a mention within a conversation.
At Merissel, we help brands build exactly that visibility: from the initial audit to technical implementation and ongoing monitoring of mentions in AI. If you want to know where your brand stands today across ChatGPT, Perplexity, and Google AI Overviews, learn about our GEO service or contact us for an initial, no-obligation assessment.
