Published (1.9.25 - updated 26.10.25)
Generative Engine Optimisation (GEO) is a new approach to optimising online content that focuses on how AI-powered search engines, (also known as generative engines) understand and use information. It is an emerging field, and I can assist . My work is focused on Chatgpt (see my attempt to reverse engineer the response to the prompt "best smartphones" in Chatgpt 5.0) & Google Gemini, whose answers are frequently integrated as AI Overviews (AIOs) in 'normal' search results on GOOG and is used as a search engines as well in it's own right. See https://www.seolondonsurrey.co.uk/blog/quality-webspam-issues-in-some-google-ai-overviews . I also focus my work on Bing Copilot (based on Chat GPT) which is integrated into some Bing search results.
Unlike traditional SEO, which primarily targets keyword rankings in search engine results, GEO aims to make your business / product more strongly associated in conceptual / semantic space in the LLM models for relevant prompts e.g. "best smartphones". This is the core task (according to my research) which involves an integrated digital marketing strategy and is possibly something which is a long-term strategy e.g. according to my research, for the prompt "best smartphones" Apple iPhone & Samsung Galaxy may be considered "Global Prototypical Smartphone Exemplars" of smartphones in CGPT's semantic space.
This is because according to my research these products are consistently recognised across most cultural and linguistic contexts, and show up as central exemplars in Chatgpt's knowledge base:
Apple's iPhone → universally salient, culturally iconic = often “the” smartphone prototype.
Samsung's Galaxy S Series → widely available, dominant Android flagship with global recognition.
Thus for example, trying to replace Samsung Galaxy's strong associations as a "Global Prototypical Smartphone Exemplar" might be considered a very difficult / long-term task.
GEO can also involve making content more accessible and useful to AI models that generate direct answers and summaries for user queries (like a Chatbot).
My 20 years experience of SEO informs my research of LLMs. https://lnkd.in/eMTMiqiB argues that bias is a structural and inevitable feature of current large language models (LLMs). Because LLMs are trained to approximate the distribution of human-generated text, they can & will reproduce the patterns (including harmful biases) embedded in those texts. There is good evidence for the broad alignment of LLM bias with human bias. But LLMs don’t simply reflect biases present in human language use. They are also at risk of amplifying them.
https://lnkd.in/eQ8GZbNq explores how the fields of machine learning (ML) bias mitigation and philosophical “conceptual engineering” (the project of revision of our concepts) can inform each other. They argue that LLMs reveal biases in our human conceptual prototypes (how we think of categories socially) and that de-biasing LLMs can serve as a tool for conceptual engineering and possibly working against "LLM bias engineering" (aka GEO).
Key aspects of GEO:
Technical: Chatbots (a.k.a answer engines) like ChatGPT or Perplexity do not render pages like Googlebot or Bingbot (at time of writing) because it's relatively costly. To be able to turn up in the responses generated from their web crawls / browsing tools, information needs to be available in the initial HTML when the bot visits the site – test this with https://punits.dev/check-server-side-rendered/ .
Content Contextualisation: Ensuring your content is clear, well-structured, and provides sufficient context for AI to understand the topic and generate accurate responses.
Information Synthesis: Focusing on how AI can integrate and synthesize information from your content with other sources to provide comprehensive answers.
User Intent Understanding: Going beyond keyword matching to anticipate and address the deeper intent behind user queries.
Fluency Optimisation: Making sure your website's text flows smoothly, is free from errors, and is easy for both humans and AI to read.
In essence, GEO is about creating content that is:
Comprehensive: Covering all relevant aspects of a topic.
Contextual: Providing clear explanations and background information.
Accurate: Ensuring factual correctness and reliability.
Structured: Using headings, subheadings, and lists to organize information logically.
Accessible: Easy to read and understand for both humans and AI.
Authoritative: Google is likely looking at which other (authoritative) websites link to a website to deem how authoritative a site is.
Why is GEO important?
With the rise of AI-powered search features that provide direct answers and summaries, GEO is becoming increasingly important for online visibility especially due to the prominence of AI overviews on Google for many searches : a late 2024 study by SE Ranking stated that almost 10% keywords (8,718 out of 100K in their sample) have AI Overviews (AIOs). By optimising your content for generative engines, you can:
Increase the chances of your content being used as a source for AI-generated answers.
Enhance your brand's authority and credibility.
Reach a wider audience through AI-powered search experiences.
While traditional SEO remains relevant, GEO represents a significant shift in how we think about content optimisation. It's about creating valuable, informative content that not only ranks well in search results but also serves as a reliable source of information for AI-driven search engines.