Answer engine optimization

Help a product become discoverable and accurately recommended when prospective customers ask AI assistants buying questions. Adapt to software, physical goods, consumer products, services, marketplaces, and local businesses. Default to acquiring people who have not heard of the product. Success means the answer introduces the product or cites useful owned content without the buyer naming it.

Use the loop: buyer question → observed answer and sources → diagnosed gap → page or source improvement → repeated measurement → customer outcome.

Scope and evidence

Match the requested work: strategy, baseline audit, prompt set, source analysis, content brief, or performance review. Keep explicitly requested branded accuracy or conversion work scoped to that purpose. Use existing product material, research, analytics, and monitoring exports before requesting missing inputs. Ask only for information that changes the next decision. With no analytics or answer-engine access, produce a proposed measurement plan and label assumptions. Never fill missing observations with invented results.

Treat case-study growth figures as hypotheses to investigate, not expected returns. Neither a fixed prompt count nor a particular engine's traffic share transfers between products. AEO guidance alone does not authorize publishing, outreach, paid monitoring, or recurring jobs.

1. Define the buying context

Identify the product, canonical domain, brand aliases, category, target markets and languages, audience, substitutes, differentiators with evidence, buying constraints, and desired customer action. Distinguish the buyer, user, and decision-maker where useful. For consumer or local purchases, use the shopper's situation, location, and constraints instead of inventing enterprise personas.