Generative Engine Optimization is not a set of radically new rules but a strategic shift in focus. The core difference lies in the objective: moving from optimizing for clicks and rankings to optimizing for brand visibility and inclusion within an AI-generated answer. 

Traditional SEO principles are the fundamental building blocks for successful Generative Engine Optimization (GEO) in the era of Large Language Models (LLMs).

At Chris McElroy SEO Agency we believe that rather than viewing GEO as a replacement for traditional SEO, SEO professionals should recognize it as an evolution built upon the same core concepts.

These things still matter...

Crawlability and mobile optimization

Structured data: While schema markup was previously used for rich snippets, it is now crucial for helping AI models understand the context of your content, such as entities, relationships, and facts.

There's been some people posting about gow chat GPT and other AIs strip that out and pull the text to give responses to users. The schema is important long before the prompt was ever made because it helped train the AIs on what your data was about.

Content and authority

Quality and accuracy: Generative engines like Google's AI Overviews prioritize high-quality, authoritative content that provides in-depth and accurate information.

This is directly aligned with the Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) principles of traditional SEO. And before somebody pops in and says EEAT isn't a direct ranking factor, It's indirect effect is crucial when you're talking about entity SEO & GEO. 

Authority signals: LLMs are trained on vast datasets and are more likely to reference widely cited and trusted sources. Building a strong brand, securing mentions across high-authority publications, and citing credible external sources are traditional SEO tactics that increase your chances of being included in an AI's response.

Internal linking: An effective internal linking strategy helps AI models understand topical clusters and deep content, which is valuable for surfacing authoritative answers. 

A strong traditional SEO foundation improves the technical accessibility, authority, and content structure that generative AIs need to interpret and cite content accurately.

Things to do...

Strengthen the fundamentals: Conduct a technical SEO audit to fix underlying issues with site speed, crawlability, and schema markup.

Double down on authority: Use a people-first content strategy that focuses on Expertise, Experience, Authoritativeness, and Trustworthiness (E-E-A-T).

Invest in digital PR and unique data to reinforce your authority with both traditional search engines and LLMs.

Optimize for structure and clarity: Write content that is highly scannable for both users and AI models by using clear headings, tables, bullet points, and an FAQ section.

Adopt a conversational tone: Shift away from keyword-stuffed language toward conversational, natural language that mirrors how users interact with chatbots.

Expand your measurement toolkit: Go beyond traditional metrics to track brand mentions, citations, and overall sentiment within AI-generated responses. 

We're here to help. If you have any questions about optimizing for AI search, post your questions and we'll do our best to answer them.



GEO: Just Another Evolution of SEO