What Is GEO (Generative Engine Optimization)? A Plain-English Guide

Generative Engine Optimization is the practice of shaping a website's content and structure so that generative AI systems — Google's AI Overviews and AI Mode, ChatGPT, Perplexity, Claude — can retrieve it, understand it correctly, and choose to cite it in a generated answer.

The name mirrors "SEO" deliberately: same underlying goal (be found and trusted for a topic), but the output the system optimizes for is a synthesized answer instead of a ranked list of links.

Classic SEO optimizes for a ranking position: the page that best matches a query's intent, backed by links and relevance signals, gets the click. GEO optimizes for something further downstream — whether a language model's retrieval step surfaces your passage at all, and whether the passage is clear enough for the model to lift and attribute correctly.

In practice this means GEO cares more about passage-level clarity (a direct, self-contained answer near the heading it answers), verifiable specifics (numbers, dates, named entities the model can trust), and structured data that confirms who is saying what — on top of, not instead of, the technical fundamentals SEO already requires (crawlable HTML, fast pages, real authority).

Answer Engine Optimization (AEO) is the most concrete, actionable slice of GEO: writing and structuring individual pages so they read as a direct, quotable answer to a specific question, the same shape an AI system is trying to extract.

Treat GEO as the strategy — know which AI engines matter for your audience and why — and AEO as the execution: the actual page-level rewrites (direct answers, schema, clear sourcing) that make each individual page more likely to be the one an AI system decides to cite.