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The new term on the block: Generative Engine Optimisation (GEO)

The way users search is changing quickly and drastically with the introduction of generative AI engines and conversational search. Gone are the days of solely focusing on Search Engine Optimisation (SEO), and now, Generative Engine Optimisation (GEO) is rising in notoriety. 

So exactly what is GEO and how is GEO different from SEO?

SEO vs. GEO

SEO is a well-established strategy aimed at enhancing a website's visibility in traditional Search Engine Results Pages (SERPs). It involves techniques like keyword optimisation, high-quality content creation, and building backlinks. 

GEO is a newer concept

GEO is a relatively new strategy designed to propel your content to the forefront of AI search rankings. 

GEO emerged in response to the rise of generative AI engines, such as ChatGPT. These engines, unlike traditional search engines like Google, generate direct responses to user queries rather than simply ranking websites. 

AI search optimisation strategies focus on optimising content to ensure it’s included in responses. It focuses on creating content that resonates not only with human readers but also with the algorithms of AI-powered search engines. This approach goes beyond traditional SEO, considering the unique needs of these evolving search systems.

Long story short: SEO focuses on improving a website's ranking in SERPs. GEO focuses on ensuring a website's content is included in the AI-generated responses of these new search engines.

Princeton University and IIT Delhi GEO study

A closer look at GEO

A recent study by researchers at Princeton University and IIT Delhi highlighted the importance of GEO1, a term they coined themselves (one we aren’t particularly keen on, it’s giving secondary school Geography vibes.) They found that by implementing AI search optimisation strategies, they could significantly increase the visibility of their content in AI-generated responses. 

Researchers investigated nine factors to determine how content influences generative AI responses. These factors included:

  • Unique words 
  • Keyword stuffing 
  • Easy to understand 
  • Authoritative 
  • Technical terms 
  • Fluency optimisation 
  • Cite sources 
  • Quotation additions 
  • Statistics additions 

The analysis assessed which factors most significantly affected the results. Techniques like keyword stuffing proved unsurprisingly ineffective, reducing visibility by as much as 10%.1

The top-performing AI search optimisation strategies included: 

  • Citing sources: Include links to reputable sources to enhance content credibility.
  • Adding quotations: Incorporate quotes from relevant experts to increase depth and authority.
  • Statistical support: Back up claims with statistics to improve data-driven decision making.
  • Fluency optimisation and easy to understand: Takes into account readability and how a website’s text flows. These two factors can boost visibility by 15–30%.1 Obviously, the presentation does matter.

Combining factors is key, according to the study:1 

Relative Improvement Graph
Relative Improvement on using combination of GEO strategies. Using Fluency Optimization and Statistics Addition in conjunction results in maximum performance. The rightmost column shows using Fluency Optimisation with other strategies is most beneficial.

The study concluded, “. . .these methods can boost source visibility by up to 40% in generative engine responses. Among other findings, we show that including citations, quotations from relevant sources, and statistics can significantly boost source visibility.”1

How reliable is the study?

As of this writing, the paper has not yet been peer-reviewed, and that’s important to remember. It’s currently available as a preprint on platforms Arxiv and OpenReview. Preprints are preliminary versions of scholarly research shared publicly. It’s not uncommon for researchers to distribute or publish preprints to gather feedback, refine their work, and ultimately submit a more robust final draft to academic journals. 

In other words, fans of GEO may be getting ahead of themselves. Sandbox SEO’s Tyler Hermanson cites flaws in the methodology, among other problems.2 If the study’s authors take his and other comments on board, we should see revised results. Until then no one can properly judge GEO. 

Google EEAT

GEO & EEAT best practices

As it stands now, the key practices highlighted in the GEO paper align closely with best practices recommended for establishing Experience, Expertise, Authoritativeness, and Trustworthiness (EEAT) in content creation. 

Both emphasise strategies such as optimising content for clarity, including authoritative sources, and presenting information in a way that resonates with the target audience. These actions improve both visibility in generative engine results and content credibility, which is vital for EEAT.

AI search optimisation strategies

Even though we’re waiting for the final verdict on the GEO paper, it still contains what we’d call great advice. 

1. Understand intent

  • Research user queries: Use keyword research platforms to identify common questions and topics your target audience is searching for. Are these queries informational, navigational, or transactional? Then match content with intent. 
    • Informational queries: Use citations, quotes, and statistics to improve visibility by providing trustworthy, in-depth answers for users looking for reliable information.
    • Navigational queries: Optimise content fluency and directly address the user's destination to enhance visibility in generative AI engines when users are searching for specific websites or pages.
    • Transactional queries: Include clear calls to action and ensure content is persuasive and easy to follow to boost visibility for queries related to purchases or service subscriptions.

2. Create optimised content

  • Tailor content to specific domains: For science and technology, use technical language and reliable sources. In arts and humanities, reference respected sources. For business and finance, use data-driven insights and statistics.
  • Focus on authority and trust: Write content that demonstrates expertise, using quotes from credible sources and relevant industry terminology.

3. Use structured data 

  • Incorporate schema markup: Structured data helps AI models understand your content better. By using schema markup, you can organise your content in a way that generative AI engines can easily interpret and display in responses.

4. Leverage multimedia and social media

  • Engage with multimedia: AI-driven engines favour videos, infographics, and interactive content. Add diverse types of content to your pages.
  • Distribute content across platforms: Generative models gather data from different sources, not just traditional websites. Share your content on social media platforms and forums like Reddit and Quora.

5. Continuous optimisation

  • Test and analyse performance: Monitor how your content performs in generative engine responses, and adjust your strategies based on visibility and engagement data.
  • Adapt to algorithm changes: Keep up with evolving AI models and algorithms, refining your GEO strategy as needed.

What’s next?

If you want to talk about optimising your website and AI search rankings, then let’s have a chat! In the meantime, we’ve written a few blogs on SEO which you can explore here.

This is one of our areas of expertise, and we’re continuing to delve into GEO and what this means for future marketing and content strategies. Here are a few of our case studies or our page on SEO services. 

Sources:
1GEO: Generative Engine Optimization, Aggarwal, Murahari, Rajpurohit,  Kalyan, Narasimhan, and Deshpande, 28 June, 2024
2GEO Targeted: Critiquing the Generative Engine Optimization Research, Sandbox SEO, Tyler Hermanson