Generative Engine Optimization
AI search is already deciding who gets cited.
AI search is rewriting who gets cited and who disappears. Most GEO advice is recycled SEO intuition. Here's what the actual research shows, and where it goes completely silent.
The short version
The one controlled experiment on the question is Aggarwal et al. (Princeton and IIT Delhi, KDD 2024), which found content changes can lift visibility in generative answers by up to 40%, with quotations from authoritative sources and statistics carrying explicit citations as the strongest levers. Everything else is platform documentation and industry measurement: Google says no special markup or AI-specific file is required, Pew found users click a traditional link 8% of the time when an AI summary appears against 15% when it does not, and Ahrefs found schema produces no citation lift. Follow-up papers extend the question to structure and to e-commerce rather than re-testing the original levers. The practical answer is unglamorous: cite your sources inline, give the figures, and write the answer where a reader will find it.
Chapter 01
What GEO is, and where the term came from
"Generative Engine Optimization" entered the academic literature in November 2023, when researchers from Princeton University and IIT Delhi published a paper by that exact title. It was presented at ACM KDD 2024, one of the top data mining conferences in the world. It's still the only peer-reviewed paper that systematically tested optimization strategies for AI search visibility.
The paper's authors, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, and Ameet Deshpande, defined the problem precisely: search is shifting from returning a list of links to generating a synthesized answer. When that happens, visibility stops being about ranking position and starts being about whether the AI's response includes your content at all.
They built GEO-bench: 10,000 real queries paired with the top-5 Google results, tested 9 content optimization strategies, and measured which changes made the AI include more of a given page in its answer.
Two strategies stood out clearly: adding quotations from authoritative sources and adding statistics with explicit citations. Across 25 topic domains the framework's content methods lifted visibility by up to 40%, validated on real Perplexity.ai responses, not just simulations. (The paper reports several per-method figures depending on the metric; the headline ceiling is what holds up — treat the individual percentages as directional.)
| Strategy | Visibility improvement |
|---|---|
| Add quotations from sources— Top lever in the study | Strongest method |
| Add statistics with citations— Consistent across 25 domains | Effective |
| Cite sources explicitly | Effective |
| Easy-to-understand language | Moderate positive |
| Technical terminology | Moderate positive |
| Keyword stuffing— No benefit | Zero / negative |
Chapter 02
What the platforms officially say (and what they won't)
- Standard indexability required
- Snippet eligibility required
- Ranking mechanism not disclosed
- No special markup documented
- llms.txt not supported (explicitly)
- H1/H2/H3 headings reflecting specific questions
- Short, focused sections (one idea each)
- FAQ / HowTo / Product schema
- Factual language with measurable facts
- Clean, accessible HTML
- Content consistent with authoritative sources
- Source selection mechanism not disclosed
- Citations required in API responses
- Query rewritten into targeted sub-queries
- No publisher guidance published
Chapter 03
What an AI Overview does to your click rate
Pew Research Center published the most methodologically rigorous study on AI Overview CTR impact. Through March 2025 it tracked actual browsing behavior from over 900 U.S. adults who consented to a browser tracker (real clicks, not SERP scraping), and published the results that July. 68,879 unique Google searches analyzed.
Seer Interactive tracked 3,119 informational queries across 42 client organizations over 15 months (June 2024 – September 2025). Being cited in an AIO was associated with 35% higher organic CTR and 91% higher paid CTR. The authors explicitly note they can't prove causation. The figures below are that cut of the study; Seer has since published a third revision covering January 2024 to February 2026 over roughly 10,000 keywords, which reports a 55% organic CTR decline (1.41% to 0.64%) on a differently drawn sample. If you compare our table against Seer's live page and the headline numbers differ, that is why.
SparkToro's 2024 clickstream study, run on Datos panel data, found only 360 clicks per 1,000 US Google searches reach non-Google properties. 58.5% of US searches end with no click to the open web. Later readings put the figure higher still.
| Scenario | Organic CTR | YoY change |
|---|---|---|
| AIO present, not cited | 0.52% | −65% |
| AIO present, cited | 0.70% | −49% |
| No AIO | 1.45% | −46% |
Chapter 04
What doesn't work
Chapter 05
What the evidence actually supports
Chapter 06
The honest uncertainty
A few things are genuinely unknown, and anyone claiming certainty about them is selling something.
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