What is GEO (Generative Engine Optimization)?
TL;DR
Optimization for getting cited inside ChatGPT, Claude, Perplexity, Gemini, and AI Overviews answers. The 2026 successor to SEO, often called 'SEO 2.0'.
GEO (Generative Engine Optimization): Definition & Explanation
GEO (Generative Engine Optimization) is the 2024-2026 discipline of making your content cite-worthy to generative AI engines — ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Where classical SEO targets Google rank, GEO targets the answer the LLM produces: you want your domain in its source list, your phrasing in its summary, and your brand in its narrative. Practical levers: (1) lead-with-the-answer structure (LLMs lift discrete chunks well), (2) hard E-E-A-T (named authors, editorial policy, first-party data), (3) llms.txt at site root (Anthropic-proposed standard), (4) full structured data (JSON-LD: Article, FAQ, Product, HowTo, plus DefinedTerm and ClaimReview), (5) brand mentions in the wild (LLMs weight in-text mentions over backlinks), (6) comparison and 'X vs Y' content (the most-cited format inside LLM answers), (7) freshness signals ('2026' in titles, datePublished/dateModified bumps). KPIs: citation rate when users prompt about your category, AI Overviews exposure, branded search lift. Tooling: Otterly.AI ($29/mo), Profound ($499/mo), Peec AI, SEMrush AI Toolkit. With 30-40% of search volume migrating to AI engines, allocating 30-50% of SEO budget to GEO is now the table-stakes 2026 move. Without it, AI-search referrals drift to zero by 2027.