Answer Engine Optimization (AEO)
Optimizing so answer engines surface and cite your brand as the answer, not just a link.
Answer Engine Optimization is the practice of becoming the answer that an answer engine gives, rather than one of ten links a user has to click through. An answer engine is any system that responds with a direct answer: AI assistants like ChatGPT and Perplexity, voice assistants, and the featured-snippet and AI-overview boxes inside search.
AEO predates large language models. Marketers used the term for featured snippets and voice search well before AI chat, where being the single spoken or boxed answer was already the prize. As AI assistants became the dominant answer surface, AEO extended to cover them.
The line between AEO and GEO is blurry and the terms are often used interchangeably. A useful split: AEO emphasises being the concise, sourced answer to a specific question, while GEO emphasises brand presence across the broader set of generative outputs. Both care about the same underlying signal, which is whether the model trusts you enough to name you.
Frequently asked questions
- What is the difference between AEO and GEO?
- They overlap heavily. AEO focuses on being the sourced answer to a question, including pre-LLM surfaces like featured snippets. GEO focuses on brand presence across generative AI outputs. Many teams use the terms interchangeably.
- Does AEO only apply to AI chatbots?
- No. AEO started with featured snippets and voice search. It now includes AI assistants, but the goal has always been the same: be the direct answer, not one link among many.
Related terms
Whaily turns this from theory into measurement: which brands AI names in your category, and which sources shape those answers, tracked across ChatGPT, Gemini, Claude and Perplexity.