Bridging Traditional SEO and AI: Ann Smarty Analyzes What LLMs Cite

In a recent LinkedIn post, Ann Smarty delves into the factors that influence whether a webpage is cited by Large Language Models (LLMs). She bridges the gap between traditional Search Engine Optimization (SEO) and what she terms “Generative Engine Optimization” (GEO), examining whether established SEO practices still hold sway or if a new approach is necessary.

Smarty highlights the challenge of understanding LLM citation criteria due to limited direct information from AI platforms. Instead, she points to the reliance on patent information and independent studies that identify correlations. She notes the work of Cyrus Shepard, who has compiled documents and identified frequently mentioned tactics that appear to impact LLM citations.

“There’s not much information LLM platforms would provide us with, so we have to rely on patents and independent studies looking at correlations.”

Analyzing the Core Drivers of LLM Citations

Ann Smarty’s analysis focuses on understanding these correlations and determining if they align with or diverge from traditional SEO principles. She questions whether current SEO efforts are sufficient or if a distinct set of actions is required for content to be recognized and cited by AI systems.

The Intersection of SEO and GEO

According to Ann Smarty, the key lies in understanding how traditional SEO tactics translate into the realm of AI-driven content consumption. She endeavors to create a clear connection between what has historically worked for search engines and what is now proving effective for LLMs.

As Ann Smarty explains:

“I decided to take one step further here and create a bridge between traditional SEO and SEO for AI (GEO) to see how things have really changed.”

This approach, Smarty suggests, is crucial for content creators and marketers aiming to ensure their work gains visibility and authority within AI-generated content ecosystems. By examining the data compiled by researchers like Shepard, Smarty seeks to provide actionable insights into optimizing content for both human and machine readers.

Is It “Just SEO” or a New Paradigm?

A central theme in Smarty’s post is the investigation into whether the factors influencing LLM citations are merely an extension of existing SEO best practices or if they represent a fundamental shift. She aims to clarify whether content that performs well in traditional search is inherently favored by LLMs, or if specific, AI-centric optimization strategies are becoming paramount.

Ann Smarty argues that this distinction is vital for strategic planning. Understanding whether to refine existing SEO approaches or develop entirely new ones for AI engagement can significantly impact a brand’s digital footprint and information dissemination capabilities.

“So let’s look at those GEO correlations and see if it is “just SEO” or if we need to start doing something differently.”

Her exploration encourages a proactive stance, prompting professionals to evaluate their content strategies in light of evolving AI technologies. By dissecting the correlations, Smarty provides a framework for assessing the effectiveness of current methods and identifying areas for future adaptation in the dynamic landscape of online information.