LLM SEO (or GEO) is optimizing content to be cited or recommended by AI models like ChatGPT, Perplexity or Google AI Overviews.
LLM SEO (Large Language Model SEO), also known as GEO (Generative Engine Optimization), is an emerging discipline that optimizes content to be selected as a citable source by generative AI models. Unlike classic Google (which follows links), LLMs read the text and decide whether it is worth citing based on the clarity, specificity and credibility of the information. Key principles: clear definitions at the start of sections ("X is Y that does Z"), specific numeric data, cited sources, FAQ-style structure, tabular format and a robots.txt that allows AI crawlers (GPTBot, ClaudeBot, PerplexityBot).
By 2026, an estimated 30-40% of searches with a direct answer will come from AI Overviews (Google) or chatbots (ChatGPT, Perplexity). Sites not optimized for LLMs lose a third of their potential organic visibility.
Source: Perplexity — AI Searchof Google searches already show an AI Overview.
BrightEdge, 2025
higher chance of being cited by AI engines when you add sourced statistics.
visibility lift in AI answers for lower-ranked pages that cite sources.
E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is the framework Google uses to assess the credibility and quality of a site's content.
A featured snippet is the box above Google's organic results — "Position 0" — showing a direct answer to a question, extracted from an indexed page.
Schema markup is structured data in JSON-LD format added to a page's HTML that helps Google and LLMs understand the context and type of the content.
Robots.txt is a text file placed at the root of a site that tells crawlers (Google, Bing, GPTBot) which pages they may or may not access and index.
Explore how to apply this concept to your industry and city.
