Generative Engine Optimization is the engineering discipline of making content cleanly retrievable and citable by generative answer engines. It complements SEO and AEO.

We measure GEO through citation frequency, accuracy of cited claims, and presence in answer sets for category and brand prompts across major engines.

Is GEO different per engine?

There is meaningful variance between engines in how they retrieve and cite. The underlying principles are consistent: clean structure, clear entities, defensible authority, and chunkable answers.

Laboratory · 05

AI Discoverability Laboratory.

The AI Discoverability Laboratory is our research practice for Generative Engine Optimization (GEO) and citation engineering: the structural, semantic, and authority conditions under which large language models retrieve, quote, and attribute a source. It measures how ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude select and cite brands across category and brand-level prompts.

Focus areas

What this laboratory investigates

Generative Engine Optimization (GEO) patterns.

Citation engineering across answer engines.

Machine-readable content design and chunkability.

Source authority and trust signal architecture.

Brand presence across LLM training and retrieval corpora.

Monitoring of AI citations and brand mentions.

Methodology

How the laboratory operates

Prompt design

Construct representative prompt sets that mirror how customers actually ask category and brand questions.

Retrieval testing

Test how content is retrieved, chunked, and cited by generative engines under those prompts.

Iteration

Refine source architecture, structure, and authority signals to increase citation frequency and accuracy.

Active experiments

What we are currently testing

Chunkability vs citation frequency

Studying how content structure and chunkability influence how frequently a source is cited by answer engines.

Source authority signaling

Examining which authority signals most consistently move a source into the cited set.

Cross-engine citation behavior

Comparing how ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude select and cite sources for identical prompts.

Applied to

SaaS CompaniesAI StartupsProfessional ServicesPublishers

FAQ

Frequently asked questions

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Findings from this laboratory are published as the research programme develops.

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