GEO

Generative Engine Optimisation (GEO) is the practice of improving the chance that a generative engine — ChatGPT, Gemini, Perplexity, Copilot, Claude or Google's AI surfaces — retrieves your content, uses it to support an answer, and cites you as the source. It extends SEO rather than replacing it: a page that cannot be found and parsed never enters the pool of candidate sources in the first place.

The term comes from academic work: 'GEO: Generative Engine Optimization' (Aggarwal et al., ACM SIGKDD 2024) formalised it as a measurable optimisation problem and found that citing sources, adding statistics and adding quotations increased how prominently a page was used in a synthesised answer, while keyword stuffing did not.

For product brands, GEO is mostly a data problem. The questions people ask an assistant are specific — which variant fits, what it costs, whether it is still available, what refill or spare it takes, whether it can be repaired. Those answers live in product data, not prose. Google's guidance is explicit that there is no special AI-only markup; the implication is that the ordinary plumbing must be complete: canonical product pages, full schema.org Product and Offer data, standard identifiers such as GTIN and GS1 Digital Link, machine-readable manuals, and a retrieval surface (RAG, MCP) an agent can query.