5 GEO Tactics That Get Your Content Cited by AI
Researchers at Princeton and Georgia Tech ran an experiment: take real pages, change one thing at a time, and measure whether AI engines cite them more. They tested nine changes and published the results at KDD 2024 (Aggarwal et al.). Five changes worked. Here is what they were, and how to copy each one.
What makes AI cite a page?
AI cites the claims it can trust and lift on their own. The five tactics below each make one sentence more trustworthy: a number, a quote, a source, cleaner prose, or a plain statement. They apply at the claim level, so you use them line by line rather than page by page.
1. Put a number on the claim
A statistic is a fact the model can quote without borrowing the rest of your sentence. Give every number its evidence with a simple shape: the figure, who reported it, and the year.
Before: "Our platform helps teams onboard faster."
After: "Our platform cuts onboarding 40%, saving 120 hours a month
(Creative Nexus customer audit, 2025)."2. Bring in a named quote
When you attribute a line to a real, named person, the model treats it as checked. That is why a single expert quote often outweighs a paragraph of your own claims. Use real people and real quotes only; a fabricated one falls apart the moment an engine tries to corroborate it.
3. Cite the original source
Point to the study, not to a blog that mentions the study. Linking credible sources tells the engine your page is careful with facts. In the experiment, this was the change that lifted lower-ranked pages the most.
4. Clean up the writing
This one is about clarity, not vocabulary. The re-ranking stage drops text it can't parse smoothly, so a tangled sentence loses even when the fact inside it is good. Read each paragraph out loud and rewrite whatever trips your tongue.
5. Drop the hedging
"Could," "may" and "arguably" tell the model your own page isn't sure of itself. When your evidence backs the claim, say it flat.
Before: "Our tool could potentially be faster than some options."
After: "Our tool renders reports 3× faster than the legacy exporter
(internal benchmark, 2025)."What the study says to stop doing
| Change | Effect on citations |
|---|---|
| Keyword stuffing | No benefit, and a drop on Perplexity |
| Adding word count | More noise, higher chance of rejection |
| Simplifying everything | Removes the depth engines reward |
| Persuasion with no evidence | Discounted during synthesis |
Key takeaways
- Numbers, quotes and citations are the heavy signals. Build every important claim on one.
- Clean prose and a plain voice decide whether a good claim survives re-ranking.
- Stuffing and padding do nothing for AI, and sometimes cost you.
- The tactics helped small pages most, so a precise site can beat a vague giant.
The Creative Nexus Content Engine writes to this standard, and Autopilot ships the schema for you.
Frequently asked questions
What are the GEO tactics that increase AI citations?
Adding statistics, quoting named experts, citing sources, cleaning up the prose, and dropping hedged language. Each makes a single claim easier for an AI to trust and lift into its answer.
Where do these tactics come from?
From a Princeton and Georgia Tech study by Aggarwal et al., published at KDD 2024, that tested nine optimization changes across thousands of queries and measured which ones raised AI citation rates.
Which tactic works best?
Statistics, quotes and citations were the strongest, because each gives the model a self-contained, checkable unit. Citing sources especially helped pages that ranked lower in normal search break into AI answers.
Does keyword stuffing help?
No. The study found it produced no benefit, and Perplexity showed reduced visibility for over-optimized pages. AI pulls out factual claims, so specific evidence beats keyword density every time.
What is the number-plus-source-plus-year format?
A pattern where each statistic carries its own proof: the figure, who reported it, and when. For example, 'cuts onboarding 40% (2025 audit).' It lets an AI quote the number on its own.
Do the quotes need to be real?
Yes, real and attributed to a named person. The credibility comes from the model being able to corroborate the quote elsewhere. Inventing one removes the very signal you were trying to add.
What does cleaning up the writing mean here?
Clear, readable sentences a model can parse without stumbling, not fancier words. Tangled or inconsistent text tends to get dropped at re-ranking, even when the fact inside it is sound.
Why avoid hedged language?
Words like may or arguably signal that your own page is unsure, so the engine seeks a firmer source. State claims your evidence supports directly, and keep hedges only where the facts are genuinely mixed.
How many statistics should a page have?
Enough that every major claim rests on one, without padding. Three well-sourced numbers beat ten vague ones. Attach a source and a year to each so the model can trust and lift it.
How do I apply these at scale?
Rewrite your top commercial pages first, one claim at a time, then systematise it. A content engine built on the same standard can draft new pages this way while you approve each one.
Want this done for your site?
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