LLM SEO (or GEO — Generative Engine Optimization) is the practice of 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 SearchE-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 that appears above Google's organic results — "Position 0" — showing a direct answer to a question, extracted from one of the indexed pages.
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.
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