What is generative engine optimisation (GEO)?

Why it emerged

When a question is answered directly in a chat interface, the traditional funnel changes shape. Fewer people click through, and the ones who do arrive with the answer already in hand. Sites that depended on ranking for informational queries have watched referral traffic decline while their content continues to be used.

That shift is the entire reason GEO exists as a distinct practice.

What actually influences citation

Extractability. Models quote passages that stand alone. A definition in the first paragraph, phrased so it makes sense with no surrounding context, is far more likely to be lifted than the same information distributed across four paragraphs of build-up.

Structure. Clear headings, question-shaped H2s, tables and lists all make content easier to parse and section.

Verifiability. Specific numbers, named sources and dates are quoted more readily than general claims, because they're checkable.

Presence in the retrieval path. Being crawlable, being in the index, and — for assistants that fetch live — being fast and not blocked at the edge.

The practical starting list

Answer the literal question in the heading, then answer it immediately in the text. Add structured data where it fits, particularly FAQ and QA schema. Keep a machine-readable summary of your corpus. Make sure AI crawlers and live fetchers aren't being rate-limited or geo-blocked by infrastructure that was configured for a different threat model.

The honest caveat

None of this is a ranking algorithm you can reverse-engineer. There's no equivalent of a link graph to manipulate, and the systems change without notice. What holds is the underlying property: being the clearest, most quotable, most verifiable answer to a specific question is useful regardless of which system is doing the reading.