A paradigm shift in search and SEO
The digital marketing industry has been undergoing a transformation as generative AI redefines how people search for information. Traditional Search Engine Optimisation has long been the foundation for success and online visibility, but with the rise of Large Language Models (LLMs) and chatbot front ends like ChatGPT, Claude, and Gemini, we are potentially witnessing a new era in digital marketing: Generative Engine Optimisation (GEO) – also sometimes cited as Answer Engine Optimisation (AEO), AI Search Engine Optimisation (AISEO), Conversational Search Optimisation (CSO) and various other synonyms which are currently breaching the traditional “SEO” landscape.
Previously, search engines simply indexed and retrieved information from the web for users to choose from. Now, they can generate information, synthesising data to provide direct answers, making it less necessary for users to scroll and look through options to find what they need. As a result, ‘search engines’ are evolving beyond their original purpose.
Additionally, people are no longer relying solely on traditional search engines like Google and Bing for knowledge and recommendations. Instead, some are turning to AI-driven models, which act as both search engines and information generators. This shift means businesses must rethink their approach to online visibility and content creation.
Google’s Response: AI Overviews and the rise of GEO
Google has acknowledged this shift by integrating AI overviews into its search engine. These AI-generated summaries pull information from various sources to provide users with instant answers. They are able to answer more complex search queries compared to a traditional “keyword” search, and are powered by Gemini, Google’s LLM. Google is also currently testing ‘AI Mode‘ internally, signalling its importance and Google’s commitment to challenging the likes of OpenAI. This raises a critical question: Is GEO the next evolution of SEO?
The answer is sort of. Whilst GEO is important to recognise, we still need to keep SEO front and centre of our online strategies. This is partly because so much of GEO relies on practices we should already be doing for SEO.
Just as websites have been optimised for traditional search engines, they now need to be optimised for LLMs. Like Search Engine Results Pages, Generative AI models can recommend businesses, products, and services in their responses, making it essential for companies to ensure their content is well-positioned to be featured.
How to optimise for Generative Search
While GEO introduces new considerations, as we’ve already noted, many SEO best practices still apply.
Here are a few ways that businesses can optimise for generative search:
1. Make sure your content is accessible to LLMs
Ensuring the content on your website is accessible to LLMs (via their corresponding web crawlers) is vital if you want them to cite your website in their answers. Ensure your robots.txt file allows AI bots to crawl your site. Avoid disallowing major search engine crawlers like Googlebot and AI-focused crawlers GPTBot. Similarly, many technical SEO practices to ensure crawlers can access web content are also applicable to AI crawlers, such as limiting reliance on JavaScript Rendering. Recent research from Vercel shows a clear divide in JavaScript rendering capabilities, with ChatGPT unable to render JavaScript – meaning any content rendered via JavaScript (including internal linking) is unavailable to GPTBot – while Gemini leverages Googlebot’s infrastructure to harness full JavaScript rendering. Subsequently, ensure logical internal linking between related pages to help AI understand relationships between topics, like you would do for search engines.
2. Understand the nature of people’s AI queries
As with any good content strategy, before you write anything, start by understanding user queries being typed into LLMs. These tend to be much more conversational than traditional, short or long tail, keyword search engine queries. Adapt your strategy by crafting content that directly answers these queries using natural, engaging headings. In B2B, where the purchase journey is longer, focus on educational content alongside product-related topics to nurture awareness and engagement.
3. High-quality content is key
Provide well-researched, informative content, and try to incorporate quantitative data and cite reputable sources. Ensure that your content is clear, engaging, and valuable to users. You should already be doing this for SEO and user experience!
Traditional SEO principles still apply – build authority with comprehensive content like guides, case studies, and core webpages linking to in-depth blogs. Context is key, so ensure each piece covers multiple elements of a topic for nuanced, relevant responses.
4. Digital PR and link building matter more than ever
Research by Neil Patel and Eric Siu suggests that brand mentions, reviews, content relevancy, and online authority are crucial for AI-driven recommendations. Relevancy and brand mentions appear to be the most influential factors in determining whether an LLM recommends a product or service. Digital PR campaigns, authoritative backlinks, and media features can help establish credibility, helping with both SEO and GEO.
5. Be everywhere: Expanding your online presence
LLMs are trained on vast amounts of online data. If your brand is mentioned frequently across authoritative sources, AI models may be more likely to cite your brand or website. Extensive content marketing and PR campaigns can help ensure that AI systems recognise your brand’s relevance.
6. SEO foundations still apply
It’s clear that strong organic search rankings correlate with visibility in AI-generated responses. Traditional SEO practices like crawler accessibility (in this sense AI crawlers), keyword optimisation, structured data, and internal linking remain valuable tools for any marketer.
7. Adapting for Google’s AI Overviews
Optimising content specifically for Google’s AI-generated summaries is important if you want to feature in them. This includes crafting concise, authoritative responses and structuring content for easy AI interpretation.
The winner-takes-all effect of GEO
A major difference between traditional SEO and GEO is the competition for visibility. With SEO, ranking in positions 2, 3, or 4 still provides significant traffic. However, in generative search, there is often only one answer for any given query—the AI-generated recommendation. Whilst this may change every time you ask the question, users are still seeing a more limited range of answers than they would by using a traditional search engine. This is similar to voice search, where only the top result is read aloud. The challenge for businesses is to ensure they are the single recommendation that AI models provide.
Final thoughts: The future of Generative Search Optimisation
GEO isn’t just a passing trend—it’s the next step in search evolution. Businesses that adapt quickly by investing in high-quality content, digital PR, and a strong online presence will gain a competitive advantage. While traditional SEO techniques remain essential, optimising for AI-driven search experiences will become just as critical as more and more people turn to AI for their answers.
The key takeaway? Make sure your brand is talked about everywhere! The more an AI model sees and understands your business, the more likely it is to recommend you. If you’d like to learn more about how your online presence can be optimised for generative search, get in touch with our team at Footprint Digital.
