For a year, "how do I show up in AI answers?" had only folk-wisdom answers. Then a group of researchers from Princeton, Georgia Tech and IIT Delhi did the obvious-in-hindsight thing: they built a benchmark of 10,000 real queries across nine domains, systematically edited the source content, and measured what moved an engine to cite it. They called the discipline Generative Engine Optimization, GEO.
Show the data
| Expert quotations | 41% |
|---|---|
| Statistics | 32% |
| Cited sources | 30% |
Source: Aggarwal et al., “GEO: Generative Engine Optimization”, Princeton / Georgia Tech / IIT Delhi (KDD 2024), measured on GEO-bench.
Source: Aggarwal et al., "GEO: Generative Engine Optimization," Princeton / Georgia Tech / IIT Delhi (KDD 2024), measured on GEO-bench.
The headline result: the right edits lifted a page's visibility in AI answers by up to 40%. Not by chasing keywords, by making the content more citable.
Show the data
| Unoptimized page | 100 |
|---|---|
| After the right edits | 140 |
Source: Aggarwal et al., KDD 2024: the right edits combined lifted visibility in AI answers by up to 40%, shown here against an unoptimized page set to 100.
The best combinations of tactics moved an unremarkable page near the top of what engines surface.
The moves that worked
The benchmark tested editorial changes one at a time. Three stood out, and they rhyme: they all make a claim more verifiable.
- Add expert quotations, the single biggest lever, around +41% visibility. A named human saying it reads as authority.
- Add statistics, +32%. Specific numbers get lifted into answers far more than vague claims.
- Cite your sources, +30%. Pages that themselves cite authorities are treated as more trustworthy.
The GEO research, key figures at a glance:
| Finding from the research | Figure |
|---|---|
| Adding expert quotations, the single biggest lever | +41% visibility |
| Adding statistics | +32% visibility |
| Citing your own sources | +30% visibility |
| Visibility lift from the right edits combined | up to +40% |
| AI citations that came from the first third of the text | 44% |
| Cited pages using a clean H1 → H2 → H3 hierarchy | 68.7% |
| Cited pages using structured data markup | 61% |
The mirror image is just as useful: classic SEO keyword stuffing did nothing for AI visibility, and in several runs it hurt. The engines aren't counting keywords; they're judging credibility.
Write like a source, not like a landing page. Quotes, numbers, and citations are the currency of being cited.
Position is leverage
Where a fact sits on the page matters almost as much as whether it's there. In analyses of cited pages, 44% of all AI citations came from the first third of the text. The model rewards getting to the point. Bury your best, checkable claim under 800 words of preamble and it may never be read.
Show the data
| Short pages | 1× |
|---|---|
| 20,000+ characters | 4.3× |
Source: Citations relative to the shortest pages. ~44% of citations come from the opening third of a page, so depth only pays when the evidence is front-loaded.
Comprehensive pages (20k+ characters) earned ~4.3× the citations of thin ones. Position matters too: ~44% of citations come from the opening third of a page, front-load the evidence.
Structure the machine can read
AI engines parse structure, not vibes. Among cited pages, 68.7% followed a clean H1 → H2 → H3 hierarchy and 61% used structured data markup. Headings, lists, tables, and schema turn prose into something a model can lift a precise answer from. A beautiful wall of text is, to a crawler, an unstructured blob.
Show the data
| Clean H1 → H2 → H3 hierarchy | 68.7% |
|---|---|
| Structured data markup | 61% |
Source: Share of cited pages exhibiting each trait.
Hierarchy and schema aren't nice-to-haves; they're how the answer gets extracted.
The playbook
Translate the research into a checklist you can run on any page you want cited:
- Lead with the answer. Put your most quotable, checkable claim in the first third.
- Back every claim with a number. Replace adjectives with statistics and dates.
- Quote a named expert. One real attributed sentence beats a paragraph of marketing.
- Cite your sources, and link them. Borrow authority by referencing it.
- Use real structure. H1→H2→H3, short paragraphs, lists, comparison tables, FAQ schema.
- Go deep on one thing. Comprehensive beats thin; cover the topic, not the keyword.
- Make it crawlable. No content trapped behind JS, logins, or PDFs.
- Earn third-party mentions. The page is half the battle; the consensus around it is the other half.
GEO is just good faith at scale: say something true, prove it, structure it, and make it easy to find.
Don't game it, measure it
One caution the research makes clear: the engines are actively tuned against manipulation, and the source list churns without warning. A tactic that wins this month can flatten the next. That's the case for treating GEO as a measured loop, not a one-time checklist, publish, watch what each engine does with it, and adjust.
That loop is the whole product. Mentionova runs your category's questions through all six engines on a schedule, shows which of these moves is actually moving your citations, and flags the day the answer changes. Start with the macro picture in The State of AI Search, the wider framework in answer engine optimization, or see your own answer below.
Sources
- Aggarwal, Murahari, et al., "GEO: Generative Engine Optimization" (arXiv 2311.09735, KDD 2024)
- Princeton University, GEO publication record & GEO-bench
- Search Engine Land, GEO framework introduced in research
- ConvertMate, GEO benchmark 2026: position, length & structure of cited pages
- AI Thinker Lab, Princeton-backed GEO playbook, 2026