Where the term comes from
The research paper “GEO: Generative Engine Optimization” was first submitted in November 2023 and accepted to KDD 2024. It introduced a framework and benchmark for studying content visibility in generative answers. Results from that setting are not a forecast for every assistant, website or topic.
What the work looks like
Start with an audience question and an observed problem. Check whether the relevant page can be accessed, whether it answers the question clearly, and whether a reader can verify its claims. Correct inaccurate facts and connect useful pages through descriptive internal links.
Then revisit comparable saved answers. Count names, source links and recommendations separately. A publisher’s citation goal may differ from a brand’s recommendation goal or a creator’s need for an accurate biography. The starting guide turns those checks into a practical sequence.
How GEO relates to SEO
GEO and search engine optimization overlap. For Google AI Overviews and AI Mode, Google says existing SEO practices remain relevant and there are no extra technical requirements beyond Search eligibility. See Google’s guidance.
The additional editorial task is to examine what the answer actually says: whom it names, what it recommends and which pages it cites. Read GEO versus SEO for the measurement differences.
What GEO cannot promise
A citation is not proof that a page caused a recommendation. A before-and-after change is not automatically evidence that your edit caused the difference. Keep the collection method, dates and competing explanations visible.
There is no universal checklist that guarantees a brand will appear. A small organization can start with a narrow question set and useful evidence; its size alone does not establish that it will be easier to improve. The CRM study shows why outcomes need to be separated.