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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.

PublishedApril 11, 202620 min read
Opening finding
43.5%
of AI Overview citations come from pages outside the organic top 100
SE Ranking · 100,013 queries · July 2024
+41%
visibility gain from adding inline source citations to content
Princeton / IIT Delhi · KDD 2024
−65%
organic CTR when an AI Overview is present and you're not cited
Seer Interactive · 42 organizations · 2025
8%
click rate on organic links when an AI Overview appears (vs 15% without)
Pew Research · real browsing data · April 2025

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, 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 (+41% visibility) and adding statistics with explicit citations (+40% visibility). These were consistent across 25 topic domains and validated on real Perplexity.ai responses, not just simulations.

StrategyVisibility improvement
Add quotations from sourcesHighest performing+41%
Add statistics with citationsConsistent across 25 domains+40%
Cite sources explicitly+30–40%
Easy-to-understand languageModerate positive
Technical terminologyModerate positive
Keyword stuffingNo benefitZero / negative
+41%
visibility gain from adding inline source citations — the single most effective strategy in the Princeton paper
arXiv:2311.09735 / ACM KDD 2024
Follow-up research in 2025–2026 (GEO-SFE, E-GEO, and others) consistently found the same pattern across verticals, languages, and generative engines.

Chapter 02

What the platforms officially say (and what they won't)

Google
  • Standard indexability required
  • Snippet eligibility required
  • Ranking mechanism not disclosed
  • No special markup documented
  • llms.txt not supported (explicitly)
"No additional requirements to appear in AI Overviews... You don't need to create new machine readable files, AI text files, or markup." — Google Search Central, Dec 2025
Microsoft Bing — Most specific guidance
  • 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
AI referrals +357% YoY to 1.13B visits (June 2025). Krishna Madhavan, Principal PM Bing, Oct 2025.
OpenAI ChatGPT Search
  • Source selection mechanism not disclosed
  • Citations required in API responses
  • Query rewritten into targeted sub-queries
  • No publisher guidance published
Launched October 31, 2024 for all users. Uses "third-party search providers and content provided directly by partners."

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. In April 2025, they tracked actual browsing behavior from 900 U.S. adults using app-based panel tracking (real clicks, not SERP scraping). 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.

SparkToro's clickstream panel found only 360 clicks per 1,000 Google searches reach non-Google properties. 58.5% of searches end with no click to the open web.

ScenarioOrganic CTRYoY change
AIO present, not cited0.52%−65%
AIO present, cited0.70%−49%
No AIO1.45%−46%
−65%
organic CTR drop when AIO present and you're not cited vs. the same queries before AIOs
Seer Interactive · Q3 2025
8% vs 15%
CTR on organic links: with AI Overview vs. without
Pew Research · real navigation data
31.5%
The zero-click paradox:
Semrush found that keywords where AI Overviews appeared actually showed a slight decrease in zero-click rate, from 33.75% to 31.53%. AI Overviews tend to trigger on complex, research-type queries where users click more regardless of whether an AI summary appears. The Pew data controls for this better.
Semrush · 200,000+ keywords · Jan–Oct 2025

Chapter 04

What doesn't work

Schema markup as GEO driver
Microsoft mentions it. Google says you don't need it. Search/Atlas found no correlation between schema coverage and citation rates (December 2024). No controlled experiment shows FAQ schema causes AI citation.
llms.txt
Proposed by Jeremy Howard (Answer.AI, September 2024). None of the major platforms — Google, OpenAI, Anthropic, Perplexity — have confirmed they read it. Adoption stats vary from 0.3% to 10% depending on measurement method.
Keyword stuffing
Princeton paper tested it directly. Zero improvement. AI search uses semantic retrieval, not keyword matching. A page with your target phrase 15 times is less likely to be cited than one with 2 uses and actual context.

Chapter 05

What the evidence actually supports

01
Cite your sources inline
Inline citations in body text, not a bibliography at the bottom. "According to a 2024 Pew study of 68,879 searches..." gives the AI something to anchor.
+41% visibility (Princeton)
02
Include verifiable statistics
"Most users prefer..." is ignored. "72% of users reported preferring X in a 2025 survey of 4,000 respondents" gets included. A number with a source gives the AI something to anchor.
+40% visibility (Princeton)
03
One section, one question
AI retrieval looks for the chunk of content that answers a specific sub-question. Focused sections get cited for more queries than blended pages.
04
No JavaScript gates
Bing's crawler doesn't click, expand accordions, or scroll carousels. Content behind any JavaScript interaction is invisible to crawler-based AI systems.
05
Write like a reference, not a product page
AI systems favor third-party authoritative sources over brand-owned content. A comparative page explaining how multiple solutions approach a problem gets cited more than a page that only describes your solution.
06
Keep content current
AIO trigger rates swung between 6% and 25% in 2025. Pages with stale data get deprioritized in systems that actively compare claims against current web information.

Chapter 06

The honest uncertainty

A few things are genuinely unknown, and anyone claiming certainty about them is selling something.

Google's selection mechanism
Never published. The query fan-out description tells us how they search, not how they rank what they find. No controlled experiment on what changes cause Google AI to start citing a page.
GEO vs SEO causality
93.67% of AIOs cite from the top-10, but 43.5% of citations come from outside the top-100. Both are true simultaneously. Strong SEO correlates with AI citation but doesn't predict it fully.
AI slop contamination
A WWW '26 paper found 67% AI content contamination leads to 80%+ retrieval exposure, while answer accuracy stays stable. The system looks fine while the web underneath it isn't.
Sources — primary only
Academic papers
Aggarwal et al. — GEO: Generative Engine Optimization (Princeton / IIT Delhi, KDD 2024)arxiv.org/abs/2311.09735
Yu et al. — GEO-SFE: Structural Feature Engineering (March 2026)arxiv.org/html/2603.29979
Chen et al. — GEO empirical study (September 2025)arxiv.org/abs/2509.08919
Yu, Kim, Kim — Retrieval Collapses When AI Pollutes the Web (WWW '26)arxiv.org/abs/2602.16136
Qian et al. — Citation Generation in LLMs (CCIR 2024)arxiv.org/abs/2410.11217
Venkit et al. — Answer Engine Evaluation (October 2024)arxiv.org/abs/2410.22349
Platform documentation
Google Search Central — AI features guidance (December 10, 2025)developers.google.com
Microsoft — Optimizing for AI search answers (October 8, 2025)ads.microsoft.com
Bing Webmaster — AI Performance tools (February 10, 2026)blogs.bing.com
OpenAI — Web search tool documentationplatform.openai.com
Jeremy Howard / Answer.AI — llms.txt proposal (September 3, 2024)answer.ai
Industry research
Pew Research Center — AI Overview CTR study (July 22, 2025)pewresearch.org
Seer Interactive — AIO CTR impact (September 2025)seerinteractive.com
Semrush — AI Overviews 10M+ keywords (2025)semrush.com
Semrush — Most-cited domains in AI (November 2025)semrush.com
SE Ranking — AI Overviews sources (July 2024)seranking.com
BrightEdge — One year of AI Overviews (May 14, 2025)brightedge.com
SparkToro — Zero-click search study (2024)sparktoro.com

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