Generative engine optimization is not an agency buzzword. Researchers at Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi coined the term in a 2023 paper, later presented at the KDD 2024 conference (Aggarwal et al., arXiv:2311.09735).
They built a benchmark of ten thousand real queries, tested nine different content techniques against live generative engines, and measured which ones actually changed whether a page got cited.
One example from the paper makes the idea concrete. A small pizza restaurant's website had almost no visibility in generative engine answers, even for questions it should have owned, like which restaurant delivers fastest in its own neighborhood.
After applying the techniques the researchers tested, that same page started showing up in the generated answer. Nothing about the restaurant changed. Only the way its content was written did.
What the research measured, and what it found
The strongest single technique was adding statistics. A vague claim like "we deliver quickly" barely moves a citation decision. The same claim rewritten as "average delivery time under 22 minutes" does.
Citing outside sources came second. Adding a short, attributable quote came third. Keyword stuffing, the oldest trick in classic SEO, produced flat or negative results in the same tests.
Generative engine optimization (GEO) rewards specificity over position. Pages already ranked first on Google saw almost no additional lift from these techniques.
Pages ranked closer to fifth position saw the visibility of their content in AI answers increase by 115% after the same rewrite. A page does not need to dominate Google to win at GEO. It needs a claim a model can defend without hedging.
Why this breaks from how SEO has worked for two
decades
Generative AI changes a fundamental assumption behind traditional SEO. Instead of browsing a ranked list of pages like a search crawler, an AI model pulls information from a much broader collection of sources, evaluates which statements are reliable, and selects only the fragments that deserve to appear in its response.
That shift changes what actually earns visibility.
- Backlinks still matter because they help pages rank in traditional search engines.
- They matter far less when an AI model decides whether a page is worth citing or quoting.
- The quality and clarity of the information itself become far more important than the page's position in search results.
The same principle applies to keywords.
Traditional SEO rewarded pages that repeated a target phrase often enough to signal relevance. AI models don't measure keyword density. Instead, they look for information that is specific, verifiable, and easy to attribute.
A single sentence containing a clear, defensible insight is often more valuable than an entire page optimized around repeating the same keyword.
That is the core difference between SEO and AI SEO. A page can rank exceptionally well in traditional search while contributing nothing to an AI-generated answer if it fails to provide information the model considers worth citing.
Applying the three techniques to a real page
Most pages already contain the raw material for this work, buried inside paragraphs that never isolate the claim.
The fix rarely means writing more. It means finding the sentence that already says something true and useful, and giving it room to stand on its own with a number attached.
Adding a real, verifiable source inside a page sounds like it would weaken the page's own authority. In practice it does the opposite.
A page that cites a credible outside source, and explains what that source shows, reads as more thorough to a model deciding what to trust. That thoroughness is part of what earns the citation in return.
Getting one short, attributable quote is the technique most teams skip, usually because it means asking a real person for a real sentence instead of paraphrasing a general idea.
A single quote from a founder, a client, or a subject expert on the exact question a page is trying to answer is often enough to shift how a model treats the whole section.
Where this sits next to a normal content calendar
None of this replaces the editorial calendar a content team already runs. It adds a second pass, applied to a handful of priority pages first rather than the entire site at once.
The pages worth starting with are the ones sitting in the middle of the pack today, since the research shows that is exactly where the biggest gains are still available.
Build your GEO framework with Ande Media
Ande Media applies the techniques the original research validated, directly, instead of treating generative engine optimization as a new name for an old SEO retainer.
- Find the claims already buried in your content that just need a number attached
- Add verifiable sources and short attributable quotes to priority pages
- Prioritize mid-ranked pages first, where the research shows the largest gains
- Track citation share across ChatGPT, Perplexity, and Gemini separately from rank
- Report on which specific rewrites actually changed citation behavior
Build your GEO framework with Ande Media. Apply the same techniques the original research validated, on your own highest opportunity pages.
Frequently asked questions
Generative engine optimization. The term comes from a 2023 research paper by Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi.
No. SEO targets rank on a results page. GEO targets a mention inside a generated AI answer, and the two use different signals.
The original research found adding specific statistics to a claim produced the strongest visibility gains, ahead of citing sources and adding quotes.
No. The research shows the biggest gains happen on mid-ranked pages. Starting with a handful of priority pages is enough to see results.
