AEO optimization

AEO optimization is the working process behind Answer Engine Optimization. Where AEO names the goal — being cited in AI answers — AEO optimization names the loop that gets you there: audit, measure, generate, publish, re-measure.

The audit covers five things assistants depend on. Crawler access: GPTBot, OAI-SearchBot, Google-Extended, PerplexityBot, and ClaudeBot each have to be explicitly permitted and each has to receive real HTML. Answer readiness: every page needs a self-contained passage of roughly 40 to 80 words that stays correct when quoted alone. Entity clarity: Organization, WebSite, Product, Article, and FAQPage JSON-LD so the model knows who the passage belongs to. An llms.txt index so retrieval systems get a curated map of the site. And consistency of name, description, and claims across third-party sources the model may corroborate against.

Measurement replaces rank tracking with prompt tracking. You fix a prompt set, run it on a schedule, and record which brands and domains each answer names. Every miss becomes a specific work item — a metadata change, a schema block, an FAQ passage, or a new page — rather than a general instruction to write more content.

AEO optimization is a loop rather than a project because assistants re-retrieve continuously and competitors keep publishing. Teams that treat it as a one-off audit see gains decay; teams that run it on a cadence and verify each change against the same prompt set compound them.