Generative engine optimization (GEO) examines how brands, products and content are found and described in AI search, then improves the accuracy and accessibility of the information behind those answers.
Answer engine optimization (AEO) structures content to answer customer questions clearly and with evidence, and examines how that information is used in search and AI answers.
Large Language Model Optimization (LLMO) is an industry expression that refers to efforts to improve how language model-based services describe brands or content.
AI search optimization refers to the work of improving the accessibility, accuracy, and explanatory power of web content in searches and generated answers, and examining actual usage.
AI search visibility describes how often a brand is mentioned or a page is cited in a defined AI search or answer environment. It is not one standardized metric covering every service.
Generative search uses retrieved information to produce a natural-language answer, sometimes with links to supporting sources. Google AI Overviews is one example.
An answer engine is an expression that refers to a system that finds information related to a user's question and provides it in the form of an answer.
SGE, or Search Generative Experience, was the name of Google's generative AI search experiment in Search Labs. It is a historical term used to discuss the development of AI in Google Search.
Multi-turn search is a method of searching that does not end with a single question but asks several questions following the context of the previous conversation.
Answerability is an editorial perspective that looks at whether the content sufficiently provides the answers and conditions needed to answer readers' questions.
Snippetability refers to the possibility that specific content on a web page will be excerpted and displayed directly in search results, such as Google featured snippets, People Also Ask, and AI Overviews.
Citable content refers to content where the argument, context, and source are clearly presented so that it can serve as evidence in other documents or responses.
The question-and-answer structure is an editing method that organizes information by matching the questions readers are curious about with their answers.