Definition: what is AEO?
Answer Engine Optimization aims to make your brand part of a directly delivered answer — as a cited source, as snippet content or as a named recommendation. The term predates the generative wave, coming from featured snippets, People-Also-Ask and voice search; generative answer systems gave it today's breadth: every surface that conclusively answers questions is an answer engine.
The AEO taxonomy
The field sorts itself sensibly like this: AEO is the meta-discipline for all answer systems. GEO is the specialisation in generative search systems (AI Overviews, ChatGPT Search, Perplexity) with a focus on selection and citation. LLM SEO adds the training layer — how content reaches future model generations. The classic AEO formats (featured snippets, PAA, voice) remain distinct surfaces with their own rules.
Cross-cutting and channel-specific levers
Cross-cutting: precise question-answer structures (H2 questions with immediately following answers), passages that are citable standalone, clear entity and author signals, machine-readable publication data and unrestricted crawler access.
Channel-specific: snippet formatting for the classic SERP, retrieval and citation logic per generative system, voice-assistant requirements (short, speakable answers) and the respective measurement systems — position-zero tracking here, citation rate and share of model there.
Practical framing
The terminology debate is secondary; the choice of levers is not. Using “AEO” as a label for the same old snippet optimisation misses the generative systems; optimising exclusively for LLMs wastes the classic answer formats that still carry reach. An integrated answer strategy serves both layers from the same content base — with separate KPIs.
Related terms
The specialisations of AEO are GEO and LLM SEO; the dominant answer format in Google Search is AI Overviews. The full distinction with KPI mapping is in Answer Engine Optimization and GEO vs. AEO.
AEO is the umbrella, GEO the generative specialisation
Every surface that conclusively answers questions is an answer engine. AEO bundles the optimisation for them; GEO and LLM SEO are the specialisations for generative systems and training data.
FAQ on Answer Engine Optimization
What is the difference between AEO and GEO? ▾
AEO is the umbrella term for optimising for all answer systems — including featured snippets, People-Also-Ask and voice. GEO is the specialisation in generative search systems such as AI Overviews, ChatGPT and Perplexity, focused on source selection and citation.
Is AEO new? ▾
No. The term comes from the era of featured snippets and voice assistants. What is new is its breadth: with generative systems, the direct answer has moved from special format to the default of informational search — turning AEO from a niche topic into a structural one.
Which levers work across all answer systems? ▾
Question-answer structures with directly answering passages, standalone citability (QUEST criteria), clear entity and author signals, machine-readable data and open crawler access. Formatting, retrieval logic and measurement remain channel-specific.
Which KPIs belong to AEO? ▾
Different ones per layer: snippet/PAA presence and position-zero shares for the classic formats; citation rate, share of model and PVI for the generative systems. A single blended KPI hides where the effect comes from.