What is Generative Engine Optimization (GEO), and how does it relate to SEO?

Dive into the transformative world of Generative Engine Optimization (GEO) and understand its impact on traditional SEO. Learn how AI advancements in search engines like Google's Gemini and Microsoft's Bing Chat are reshaping content strategies. Discover practical GEO strategies to enhance your content's visibility and stay competitive in an AI-dominated search landscape.

Updated: May 21, 2024

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The era of Artificial Intelligence is transforming everything around us, including how we search for information online.

With the emergence of generative engines, such as Google’s Gemini (formerly Bard) and Microsoft’s Bing Chat, searches have become more dynamic and comprehensive, generating multimodal responses that go beyond text. But hold on: ever heard of Generative Engine Optimization (GEO)?

If you’re feeling lost amidst so many acronyms and technical terms, don’t worry: you’re not alone. Let’s simplify all of this and understand how AI is revolutionizing searches in search engines.

Curious to learn how to adapt your Content Marketing strategy to this new reality? Keep reading!

    What is Generative Engine Optimization (GEO)?

    It’s an innovative approach to search engine optimization that adapts to the era of artificial intelligence-based search engines, also known as generative engines (GE).

    Never heard of the term GEO? Don’t worry: it’s quite recent, having been formalized in a collaborative study conducted in November 2023 by Princeton University, Georgia Tech, the Allen Institute for AI, and IIT Delhi.

    But what is a Generative Engine?

    Before discussing optimization for generative engines, we need to understand what they are, right?

    According to the researchers in the study, “Generative Engines typically satisfy queries by synthesizing information from multiple sources and summarizing them with the help of large language models (LLMs).”

    So, GE not only searches for information but also generates a response to the user’s query from multiple sources, which can include text, video, infographics, e-commerce offerings, and whatever else seems relevant to answer the question.

    Well-known examples include Gemini (formerly Bard), Bing Chat, and Google SGE.

    What is the impact of GEO on SEO?

    The perspective is that this change will have a significant impact on businesses and individuals, especially when considering traffic and search engine optimization (SEO). Giuseppe Caltabiano, VP of Marketing at Rock Content, made the following observation:

    “Generative Engines represent a transformative shift in the search engine paradigm, offering direct, comprehensive answers to user queries and thereby potentially reducing the need for users to visit websites directly. Which can lead to a drop in organic traffic to websites and severely impact their visibility.”

    The decrease in traffic is not new in the world of digital marketing. According to the 2024 Digital Experience Benchmark Explorer research by Contentsquare, in various industries, 55% of websites recorded less traffic in 2023 than the previous year.

    With AI search, many believe there will be an even greater decline in traffic with the intensification of ‘zero-click’ results, especially those with less specific intentions, meaning more at the top of the funnel.

    The logic is simple: the response given by AI to these more general inquiries will likely already satisfy the user, reducing the chances of them clicking and going to your site.

    Considering that many businesses rely on traffic and online visibility to generate conversion and sales, there is a discussion of how GEs have a very high potential to affect the economy of those working with Content Marketing in general.

    That’s precisely why GEO emerged: to help this group better deal with this change we are going through and without much certainty about what the next steps will be. Quoting the same study:

    “To address this, we introduce GENERATIVE ENGINE OPTIMIZATION (GEO), a novel paradigm to aid content creators in improving the visibility of their content in GE responses through a black-box optimization framework for optimizing and defining visibility metrics.”

    The idea is that by understanding and implementing GEO methods, content creators can significantly increase visibility in AI-driven search environments.

    GEO and SEO, what’s the difference?

    After understanding the definition of each term, you might be wondering: but what about SEO? Does it no longer exist? Isn’t it the same thing? What’s the difference? Let’s delve deeper below.

    Focus on AI Algorithms

    GEO focuses on optimizing content for the AI algorithms of generative engines. Meanwhile, traditional SEO aims to improve rankings on search engine results pages (SERPs) based on various criteria like keywords, backlinks, content quality, user experience, and page loading speed.

    Multimodal Responses

    As we’ve seen, generative engines produce multimodal responses, combining information from various sources and formats, contrasting with traditional SEO’s focus on link-based results most relevant to answering the query.

    Complex Queries

    When conducting searches with long and detailed queries, search engine results pages (SERPs) often couldn’t address the entire specific demand. Thus, they opted to provide content they deemed more generally relevant to the query.

    However, with the evolution of Generative Engines (GEs), these platforms now generate responses considering more specific long-tail keywords, offering more precise solutions tailored to user needs.

    This implies a shift in content creation approach, requiring greater attention to detailed and specific audience queries.

    SERP Positioning Relevance

    In the traditional search engine model, visibility is often measured by a site’s average ranking on search results pages.

    However, this metric is less relevant for generative engines, which prioritize structured, rich responses over a simple list of links.

    Table comparing the results of a more traditional search and the results of GEs. Image source: article “GEO: Generative Engine Optimization” (November/2023)

    What Are the Main Examples of Generative Engines?

    Feeling overwhelmed by all the theories? It’s much simpler than it seems and has become quite familiar in our daily lives lately. As mentioned in the introduction, we have some very popular examples of GEs nowadays.

    Gemini (Formerly Bard)

    Gemini is an artificial intelligence tool developed by Google, initially named Bard. It functions as a generative language assistant, capable of understanding and responding to complex questions, as well as generating relevant and informative content.

    Using advanced natural language processing and machine learning techniques, Gemini aims to provide more precise and human-like responses. It can even be used in place of Google Assistant.

    Below, you can see how a search and response work on Gemini.

    Gemini research video

    Bing Chat

    Bing Chat is a search engine developed by Microsoft that is designed to provide users with relevant and accurate search results.

    Bing Chat utilizes a modified version of ChatGPT, developed by OpenAI, to provide its conversational functionalities, allowing the chatbot to respond to questions and engage in conversations more naturally and informatively.

    Thus, Bing incorporates artificial intelligence features to enhance the search experience, offering direct and personalized responses to user queries.

    Below, you can see how a search and response work on Bing.

    Bing Chat research video

    Google SGE

    SGE, or Search Generative Experience, is a Google initiative to integrate AI-based natural language generation capabilities into its search results.

    It aims to improve the search engine’s ability to provide direct answers, summaries, and intelligently generated explanations to user queries.

    Using advanced language models, SGE seeks to understand the user’s intent and generate responses that are informative, concise, and contextually relevant.

    Below, you can see how a search and response work with Google SGE.

    Google SGE search gif

    As you may have noticed, the sources used to generate the response are indicated in the form of a linked title and a summary. So, if desired, users can click and read the complete source.

    Now that you understand what GEs are and what the main ones are, as well as the importance of this new way of searching, we can move on to the next step.

    How do Optimization Strategies for GEO Work?

    GEO strategies are designed to enhance content visibility on generative engines, which synthesize responses from various sources.

    These strategies differ at times from traditional SEO practices as they focus on making content more relevant and appealing to the AI algorithms of these advanced search engines.

    The research we mentioned at the beginning emphasizes the importance of adapting to this emerging paradigm, as traditional search engine optimization strategies may not directly translate into success in the context of AI-driven search.

    In fact, the study’s findings suggest that the dominance and relevance of a brand on Google’s search engine results pages do not guarantee similar visibility in AI-driven search environments.

    Regarding this, Giuseppe Caltabiano states: “This shift also prompts a redefinition of competition in the SEO space, as the landscape now includes not only established players but also new startups that are adept at leveraging AI algorithms to their advantage.”

    As AI algorithms become more sophisticated, understanding and optimizing content for these systems requires a more dynamic approach focused on natural language and contextual relevance.

    What Are the Main Optimization Strategies for GEO?

    The collaborative study mentioned in the introduction examined nine distinct strategies aimed at optimizing website content specifically for generative engines.

    As emphasized by our VP of Marketing, “These strategies appear to be a combination of traditional SEO techniques – including keyword optimization, adherence to E-E-A-T principles (Expertise, Authoritativeness, Trustworthiness, and Experience), semantic richness, and the use of external links—tailored to the unique demands of generative search platforms.”

    These strategies include:


    Modifies the writing style of the content to be more persuasive and authoritative, making confident assertions.

    Keyword Stuffing

    Modifies content to include more user query keywords, similar to traditional SEO optimization strategies.

    Statistics Addition

    Modifies content to include quantitative statistics instead of qualitative discussion whenever possible, adding data-based evidence.

    Cite Source

    Explicitly mentions sources used to support statements throughout the website content.

    Quotation Addition

    Incorporates quotations from relevant sources to enhance the authenticity and depth of website content.


    Simplifies the language and structure of website content, making it more accessible and appealing to the generative engine and users.

    Fluency Optimization

    Improves the fluency and readability of website text, ensuring a smooth and coherent reading experience.

    Unique Words

    Adds unique and intriguing vocabulary to website content, making it stand out and increasing its appeal.

    Technical Terms

    Incorporates relevant technical terms and jargon for the domain or industry, demonstrating expertise and catering to specific audiences.

    What Are the Most Effective Strategies for GEO Optimization?

    In this study, the three strategies that stood out in terms of effectiveness were Cite Sources, Quotation Addition, and Statistics Addition, which, with minimal changes to the original content, improved site visibility by 30-40% on generative engines compared to other strategies.

    The study also showed that the effectiveness of optimization strategies varied depending on the domain of knowledge.

    For example, Authoritative optimization worked best for content related to historical domains, while Source Citation was more effective for factual search queries, and Statistics Addition proved beneficial for questions related to laws and government.

    According to the study, adding more search query keywords to the content (Keyword Stuffing) was not effective and performed worse than the baseline by 10%.

    Giuseppe also shares a list of more practical tips that are being suggested by various experts, such as Malte Landwehr, to guide and positively influence AI search. These include the strategies mentioned in the above study but go further with other suggestions such as:

    • Have real user reviews.
    • Have an expert analysis.
    • Have a pros and cons list.
    • Provide a summary for any long content that is relevant but too extensive to be quoted.
    • Add more content – not just increase the number of words, but the number of unique related words.
    • Have UGC (user-generated content). Summarize it in a quotable manner.
    • Write about new topics and events that are not part of LLMs’ training data (large language models).
    • Ensure there are no crawling or indexing issues.
    • Mention and explain relevant technical terms for your topic.
    • Keep content updated.
    • Use lists, especially for key aspects of the topic you are covering.
    • All common advice on E-E-A-T (Experience, Expertise, Authority, and Trust) also applies.

    These findings and the emergence of early strategies underline the importance of adapting content to meet the demands of generative engines, using specific GEO strategies to maintain and improve online visibility in an increasingly AI-dominated search environment.

    What to Expect From the Future of SEO with GEO

    As with any innovation, a lot can (and is) changing rapidly. Giuseppe Caltabiano brings an important discussion to the table: how many people are currently conducting searches via AI? And how will this further impact the already declining traffic, as we’ve seen?

    “First of all, the rate at which users are shifting from traditional search engines to AI-driven generative search engines remains ambiguous, with a Gartner report forecasting a significant 50% decline in organic search traffic by 2028 due to the proliferation of AI search.”

    Another interesting analysis is about how GEs choose their sources, especially regarding SERP and positioning. We’ve seen that having a good position in SERP isn’t necessarily tied to being chosen by generative engines.

    During the SEO Square event by Semji in October 2023, speakers Sélim Dahmani and Amiel Adamony from HubSpot France, in their conference “Aligning Content with User Experience: The Key to Converting with Your Website in 2023,” already emphasized the need to focus content marketing efforts to become one of the sources used by AI in generating responses.

    Now, we are witnessing the emergence of GEO focused on this issue.

    In another lecture from the same event, “The Future of SEO is Called Google SGE,” by Charley Bouzerau and Jérémie Conde, they showed that most of the sites present in Google SGE as sources of the generated responses (appearing alongside or below the response itself) didn’t exactly follow the top 10 order of SERP, and many weren’t even in the top 10.

    Presentation of “The Future of SEO is Called Google SGE,” by Charley Bouzerau and Jérémie Conde, from October/2023 (available here)


    The majority of the sites present in the SGE are not in the top 10.

    | Search: trail running shoes

    | In blue: all sites were in the top 10.

    | In red: some were in the top 10.

    | In yellow: none were in the top 10

    | Image: Presentation of “The Future of SEO is Called Google SGE,” by Charley Bouzerau and Jérémie Conde, from October/2023

    On one hand, some argue that this opens up new opportunities for smaller brands and websites to gain visibility. On the other hand, as our VP of Marketing highlights, this may further emphasize the importance of highly authoritative brands:

    “There exists an opposing perspective suggesting that AI search engines may inherently favor larger, more established websites, potentially exacerbating the disparity between these entities and smaller businesses in the digital ecosystem.”

    None of the statements or data we’ve presented are intended to be absolute truths. They are guidelines and suggestions to keep in mind during this time of many changes and emerging trends.

    In fact, in the conclusion of the GEO study, the researchers themselves defined it as “Our work serves as a first step toward understanding the impact of generative engines on the digital space and the role of generative engine optimization in this new age of search engines.” Therefore, the discipline itself is still in its early stages, and much is bound to change.

    However, based on everything we observe, in addition to traditional SEO techniques, we understand that a deep investment in the principles of E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) becomes even more relevant in the AI-driven era. After all, as demonstrated, many criteria used by GEs seem to be linked to them, aiming to ensure that users receive high-quality, reliable, and relevant content in their online searches.

    E-E-A-T and GEO: How These Two Pieces Relate?

    In a nutshell, E-E-A-T is an acronym for Expertise, Experience, Authoritativeness, and Trustworthiness, used to assess the quality and reliability of a website’s content. They refer to:

    • Expertise: Referring to the knowledge and skill of the content author in a particular subject or area;
    • Experience: Relating to the depth and relevance of the author’s experience on the topic, ensuring that the content is informative and useful for the user;
    • Authoritativeness: Measuring the recognition and credibility of the author and the website in the field in question; and
    • Trustworthiness: Evaluating the reliability and security of the site, including aspects such as content accuracy and user information protection.

    The relationship between E-E-A-T and GEO is intrinsic, as the first one serves as an excellent guideline in changes related to search engines. These changes always keep in mind what Google has emphasized since the beginning, and even more so since the advent of Google Helpful Content: Providing users with the most relevant, useful, and high-quality content.

    Therefore, maintaining a focus on content excellence and adhering to what E-E-A-T dictates is a solid strategy not only for traditional SEO but also for successfully navigating the changes brought by the rise of AI-driven search. This is what we believe, even amidst the rise of AI Search and many uncertainties in this regard.

    Hire Specialized Talent at WriterAccess

    We know it’s a lot of new things to digest, and it feels like we’re navigating through rough waters with a boat that isn’t working very well.

    However, don’t think about giving up everything and changing your entire content strategy overnight, betting all your chips on these optimizations to maintain relevance and visibility in AI-driven search environments.

    Remember that everything is in the early stages. Watch the movements, stay updated with the news, conduct tests, measure results, and try again.

    Not sure where to start? Try WriterAccess. With over 15,000 specialized talents in various segments and advanced AI features, WriterAccess is the ideal content platform to optimize your creation process and ensure your content stands out even in the era of Generative Engine Optimization.

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