Last week I wrote about AI and Search. I didn’t know a term had emerged in the meanwhile: Generative Engine Optimization (GEO).
In a recent collaborative study by Princeton University, Georgia Tech, the Allen Institute for AI, and IIT Delhi, the concept of Generative Engine Optimization (GEO) was introduced, marking a significant shift in the search marketing landscape. GEO is a novel approach aimed at enhancing the visibility of content within generative search engines, which include platforms like Perplexity, Bard/Gemini, ChatGPT, and Bing.
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is a novel approach to search engine optimization that is specifically designed for AI-driven search engines, also known as generative engines.
The goal of GEO is to create high-quality content that resonates with both the AI algorithms of generative engines and the users who interact with these responses. By understanding and implementing GEO methods, content creators can significantly enhance their visibility in AI-driven search environments
Researchers denominate these new systems Generative Engines (GE) because they not only search for information, but also generate multi-modal responses by synthesising multiple sources.
Unlike traditional SEO methods that primarily focus on keyword optimization and backlinks, GEO aims to enhance the visibility of web content in the responses generated by these AI-driven engines.
The research underscores the importance of adapting to this emerging paradigm, as traditional search engine optimization (SEO) strategies may not directly translate to success in the realm of AI-driven search.
- GEO: Generative Engine Optimization, the study (pdf)
- Generative Engine Optimization framework introduced in new research, Dany Goodwin, Search Engine Land
- Generative Engine Optimization (GEO) and How to Optimize for AI Search Results, Daniel Højris Bæk, Co-founder, SEO.ai
- Generative Engine Optimization: Revolutionizing Content Creation, Stanfel Media
The study’s findings suggest that the dominance of a brand on Google’s search engine results pages (SERPs) does not guarantee similar visibility in AI search environments.
To assess a brand’s presence in AI search, marketers must employ new metrics and methodologies that align with the unique nature of generative search engines. The research indicates that adding relevant statistics, quotations, and citations can increase content visibility by up to 40% in generative engines.
Adding relevant statistics, quotations, and citations can increase content visibility by up to 40% in generative engines.
The evolution of search from a keyword-centric to a chat-driven model necessitates a reevaluation of success metrics and return on investment (ROI) justification.
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. With several millions of small businesses and individuals relying on online traffic and visibility for their livelihood, generative engines might significantly disrupt the creator economy.
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.
In the traditional search engine model, visibility is often gauged by a website’s average ranking on search results pages (SERP). However, this metric is less relevant for Generative Engines, which prioritize rich, structured responses over a simple list of links. These engines integrate website content as inline citations within their responses, varying in length, position, and style, which necessitates a rethinking of conventional SEO strategies.
The implications for SEO professionals are significant. As Generative Engines like Google’s Search Generative Experience (SGE) become more integrated into search practices, particularly with Google’s increasing AI integration expected in 2024 and beyond, SEO experts must review their strategies to remain effective. Traditional methods may not be as effective with Generative Engines, which could lead to decreased organic traffic to websites.
Therefore, it is imperative for SEO professionals to understand and adapt to this new landscape, developing new metrics and methodologies to maintain and enhance online visibility in an AI-dominated search environment.
How to increase visibility – strategies for optimization in GEO
By incorporating citations, relevant quotations, and statistical data, SEO practitioners can significantly improve a website’s prominence in these novel search environments.
Traditionally, a website’s visibility in search engines has been measured by its average ranking across a spectrum of actual queries. However, the unique outputs of generative engines, which combine information from various sources into a singular response, necessitate the development of new impression metrics. Factors such as the length, distinctiveness, uniqueness, and the presentation of the cited website play a crucial role in determining the visibility of a citation within these engines.
The study in question examined nine distinct GEO strategies aimed at optimizing website content specifically for generative engines. 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.
The strategies evaluated are as follows:
- Authoritative: Modifies the text style of the source content to be more persuasive and authoritative, making claims with confidence.
- Keyword Stuffing: Modifies content to include more keywords from the user query, similar to traditional SEO optimization strategies.
- Statistics Addition: Modifies content to include quantitative statistics instead of qualitative discussion wherever possible, adding data-driven evidence.
- Cite Sources: Adds relevant citations from credible sources to support claims and provide attribution throughout the website content.
- Quotation Addition: Incorporates quotations from relevant sources to enhance the authenticity and depth of the website content.
- Easy-to-Understand: Simplifies the language and structure of the website content, making it more accessible and appealing to the generative engine and users.
- Fluency Optimization: Improves the fluency and readability of the website text, ensuring a smooth and coherent reading experience.
- Unique Words: Adds unique and intriguing vocabulary to the website content, making it stand out and increasing its appeal.
- Technical Terms: Incorporates technical terms and jargon relevant to the domain or industry, demonstrating expertise and catering to specific audiences
More effective methods
The researchers found that some methods were more effective in certain domains, while three strategies proved successful across all types of sites.
These top three strategies were Cite Sources, Quotation Addition, and Statistics Addition. These methods, requiring minimal changes to the actual content, improved the website’s visibility by 30-40% compared to the baselines.
Interestingly, the researchers found also that the effectiveness of optimization strategies varied depending on the knowledge domain. For instance, the Authoritative optimization, which uses more persuasive language, worked best for content related to the Historical domain.
Meanwhile, the Citation optimization was most effective for factual search queries, and adding statistics proved beneficial for Law and government-related questions.
Instead, adding more keywords from the search query into the content (what we in classic SEO know as keyword stuffing if overdone), was not effective and performed worse than the baseline by 10%.
Conclusions – How much should we trust the study?
The reliability of the study in question is subject to further scrutiny.
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.
The study confirms that Generative Engine Optimization (GEO) could potentially equalize opportunities for smaller content creators and independent businesses by boosting their visibility in AI search results.
However, there exists an opposing perspective suggesting that AI search engines may inherently favour larger, more established websites, potentially exacerbating the disparity between these entities and smaller businesses in the digital ecosystem.