Answer Engine Optimization Basics
A short framework for understanding how AI answer engines choose which brands and sources to cite.
Answer engine optimization starts with a simple question: when an AI system answers a buyer's question, which sources does it trust enough to mention?
Most teams already publish content for search. The difference is that AI answers compress discovery into a short generated response, so your source coverage, clarity, and crawlability have to work together.
Three signals to track
- Whether the brand is mentioned for the prompts that matter.
- Which domains are cited when the brand is mentioned.
- Which competitor sources repeatedly appear instead.
The useful habit is to measure these signals over time rather than treating a single prompt run as the full truth.
type AnswerSignal = {
prompt: string;
brandMentioned: boolean;
citedDomains: string[];
};
export function hasOwnedCitation(signal: AnswerSignal, domain: string) {
return signal.citedDomains.some((candidate) => candidate === domain);
}What to improve first
Start with pages that already explain your category, pricing, integrations, and use cases. Those pages tend to answer the same questions buyers ask AI systems, which makes them strong candidates for source coverage work.