GEO – Definition & Guide

What is GEO?
Generative Engine Optimization

GEO (Generative Engine Optimization) is an optimisation method that ensures AI chatbots – ChatGPT, Claude, Gemini, Perplexity – cite a website as a source in their answers.

GEO is the AI-era complement to traditional SEO: while SEO optimises for Google rankings, GEO ensures content also appears as a source in AI chatbot answers. In 2025, 45%+ of searches happen via AI chatbots, growing 20–25% per year.

The 4 main GEO targets

ChatGPT Search

OpenAI, Microsoft Bing index

Largest user base

Perplexity

Real-time search, source listing

Most transparent GEO measurement

Gemini with Search

Google index, fast growing

Google ecosystem

Claude

Anthropic, training data + search

Longer training cycle

GEO implementation – 6 steps

1

Snippet-ready content audit

Every key content first sentence must be a max 20-word definition, citable on its own.

2

FAQPage + DefinedTerm JSON-LD

Structured data for every Q&A – signals AI crawlers the content is citable.

3

Create ai-facts.json

Machine-readable facts file with expertise, definitions and key metrics.

4

Create llms.txt

AI crawler guide in root directory – URL list of most important content.

5

External links and entity building

Backlinks from trusted sources + sameAs fields pointing to Wikidata entities.

6

Measure AI citations

Manual testing in ChatGPT/Perplexity + brand mention monitoring. First result: 4–12 weeks.

GEO vs SEO – comparison

Goal Google top 10 AI chatbot citation
Channel Google, Bing ChatGPT, Claude, Gemini, Perplexity
Main tool Keywords, backlinks Snippet-ready content, JSON-LD
Measurement Google Search Console Manual AI testing
Time to result 2–6 months 4–12 weeks (Perplexity: 4–6 weeks)
FAQ

Questions about GEO

10 concise answers about AI chatbot citation and GEO.

← Home
GEO ensures AI chatbots cite a website as a source. In 2025, 45%+ of searches happen via AI chatbots.
SEO optimises for Google rankings. GEO ensures AI chatbots cite the website as a source. In 2025 both are needed together.
5 conditions: (1) snippet-ready content; (2) FAQPage and DefinedTerm JSON-LD; (3) ai-facts.json and llms.txt; (4) links from trusted sites; (5) fact-based content with numbers.
Perplexity uses real-time web search: (1) fresh content; (2) snippet-ready first sentences; (3) concrete data; (4) FAQPage schema; (5) domain authority building.
llms.txt is a guide for AI crawlers in the website root: main topics, key URLs and AI-friendly summaries. The AI-era equivalent of robots.txt.
Measurable within 4–12 weeks. Perplexity: 4–6 weeks. ChatGPT Search: 6–10 weeks. Claude and Gemini: 8–12 weeks.
Machine-readable JSON file with key facts and definitions for AI crawlers: organisation name, expertise definitions, key facts with numbers.
GEO long-term ROI is 3–10x better as citations bring free, lasting traffic. Disadvantage: 4–12 week setup time.
4 methods: (1) manual testing in AI chatbots; (2) Perplexity Pages monitoring; (3) brand mention tracking; (4) referral traffic in GA4.
Text AI systems can extract and cite without context: first sentence max 20 words, fact-based with numbers, self-contained.