The GEOrgina GEO methodology

Generative Engine Optimisation, often shortened to GEO, is the practice of making a brand and its content easy for AI answer engines to retrieve, understand, trust and cite. Where classic search optimisation targets a ranked list of blue links, Generative Engine Optimisation targets the generated answer itself in systems such as Google AI Overviews, Google AI Mode, ChatGPT Search, Perplexity and Claude. The work covers entity clarity, machine readable page structure, structured data, verifiable trust signals, self-contained answer content and crawlability for AI engine user agents.

The GEOrgina roadmap is organised into Groups. Each Group is a sequence of related tasks rather than a fixed calendar, so every partner progresses at its own pace. Alongside the Groups, recurring weekly and monthly activities run in parallel, because website work, partnerships and community posting do not happen one after the other. Every task carries a method, best practices and an explicit definition of done.

Entity Pillars are the dimensions GEOrgina uses to classify GEO work: how clearly the brand is defined as an entity, how machine readable its pages are, how trustworthy its signals look and how answerable its content is for a language model. Every roadmap task belongs to an Entity Pillar, so a partner can see which dimension of its GEO profile a piece of work improves.

GEOrgina reads the live URL a partner pastes and runs deterministic checks grouped into four categories: machine readability, entity and trust signals, answerability and AI-engine crawlability. Each check is weighted into a score out of 100, every failed check is explained in plain language, and each finding links to the roadmap task that fixes it. Full detail is on page auditing.

GEOrgina measures AI visibility through recurring sweeps. For a fixed set of questions that matter to the partner, the partner records, per AI engine, whether the brand was mentioned, whether it was cited as a source and which competitors appeared instead. Those figures build a trend over time rather than a single snapshot. Full detail is on AI visibility measurement.

An AI citation is a link or source reference that an AI answer engine shows next to, or inside, a generated answer. A mention is weaker: the brand name appears in the answer text without a link back. A citation is the stronger signal because it means the engine retrieved that specific page, judged it reliable enough to attribute, and sent the reader a path back to the site. GEOrgina tracks mentions and citations separately for this reason.

Each sweep is recorded engine by engine, because the same question produces different answers in different systems. A brand can be cited in Perplexity and invisible in Google AI Mode at the same time. GEOrgina keeps the results separate so a partner can see which engine is improving, which competitor holds an engine, and which roadmap work moved the number.

Classic SEO optimises for position in a ranked list. Generative Engine Optimisation optimises for being retrieved, understood and cited inside a generated answer. The two overlap, because an unindexable page is invisible to both, but the success metric differs: positions and clicks for SEO, mentions and citations for GEO.

The methodology is maintained by Gotoclient. See also about GEOrgina, how GEOrgina works and the FAQ.