What is answer engine optimization?
AEO is making content usable by systems that answer directly instead of returning links. The mechanics differ: structure and attributability matter more than keywords.
By Sapun Lamichhane · Arcetis
Answer engine optimisation is structuring your content so systems that answer a question directly - AI Overviews, ChatGPT, Perplexity, Claude - can find a passage on your page, lift it, and attribute it to you. The overlap with SEO is large. The difference is what counts as success: a cited passage rather than a ranked link.
What actually changes?
Four things, and none of them is a keyword tactic:
- **Self-contained passages.** A model lifts a paragraph, not a page. A paragraph that depends on the two above it cannot be quoted, so the answer goes to whoever wrote a standalone one.
- **The answer first.** Not 'in this article we will explore'. If a model reads one paragraph and it does not contain the answer, the citation goes elsewhere.
- **Question-shaped headings.** People ask questions; models match passages to questions. An H2 reading 'Why does my certificate expire early?' matches a query that 'Certificate lifecycle' does not.
- **Declared attribution.** Author, publication date, organisation. A model deciding whom to name needs something to name, and prose does not supply it unambiguously.
Does structured data still matter if rich results are shrinking?
Yes, and arguably more. Google restricted FAQ and HowTo rich results in 2023, so the search carousel is gone for most sites - but answer engines read the same markup, and that audience is growing while the carousel shrinks.
FAQPage markup remains the clearest machine-readable way to state a question and its answer together. It is worth having for the reader it now has rather than the one it used to have.
How do you measure any of this?
Honestly: badly, so far. There is no Search Console for answer engines, referral traffic from AI surfaces is under-reported, and nobody publishes ranking factors. Anyone presenting AEO rules as established fact is overstating what is known.
Which is a reason to weight these checks lower than specification-backed ones rather than to skip them. A rule encoding observed behaviour from one product generation deserves less confidence than a rule restating the HTML standard, and an honest tool says so in the score rather than in a footnote.
How do I check my own content?
The answer engine checker on this site runs 100 rules covering the structure above - FAQ and HowTo markup, question-formatted headings, semantic landmarks, declared authorship and publication dates, cited sources and passage structure.