seo-geo

GEO — Generative Engine Optimization 2026

Target Engines

• Google AI Overviews (formerly SGE)
• ChatGPT with web search
• Perplexity
• Claude with web search
• Gemini
• Bing Copilot

LLM-Readiness Score (0-100)

scripts/geo-score.ts checks:

Signal	Points
Quick answer in first 100 words	15
Direct H2 questions ("What is X?")	10
Tables/lists for comparable data	10
Citations with dates + sources	15
Statistics with attribution	10
Author bio with credentials	10
Schema.org markup	10
Updated date < 12 months	10
llms.txt present	5
No JS-only content (SSR)	5

Quantified Impact (Princeton / 2026 studies)

GEO techniques boost AI visibility by up to +40%. Ranked by impact:

Technique	Visibility
Adding statistics	+40%
Citing authoritative sources	+40%
Quoting experts	+28%
Improving text fluency	+15–30%
Keyword stuffing	-10% (worse than baseline)

AI Overviews cite ~13 sources on average per answer (2026); 59.6% of citations come from URLs outside the top-20 organic results.

Content Structure for LLMs

# <Topic>

**Quick answer** (40-60 words, factual, no fluff)

## What is <topic>?
Definition paragraph...

## Why does it matter?
Stats with sources...

## How to <task>?
Numbered steps...

## Comparison
| X | Y |
|---|---|

## FAQ
- Q: ...
- A: ...

llms.txt

Not required by Google (its crawlers ignore it) — useful for other LLMs, where early adopters report improved citation accuracy. Place at site root: https://example.com/llms.txt

# Site Name
> One-line description

## Pages
- [Homepage](https://example.com/): description
- [Docs](https://example.com/docs/): description

References

• seo-entity — entity signals + schema that drive AI citations
• skills/seo/04-geo-2026/ (ai-platforms, citation-strategies, content-structure, llm-crawlability, zero-click-optimization)
• skills/seo/08-measurement/share-of-model.md