The short answer
Which structured data fields move the needle — and which don't. The pattern repeats across ChatGPT, Perplexity and Gemini: the model isn't choosing the highest-ranked page — it's choosing the page that makes its answer easiest to write.
What the data shows
For two decades, search ranking was a list. Generative search broke that format. There is no list anymore — there is a paragraph, written by a model, that mentions some brands and ignores the rest.
The model isn't choosing the best page. It's choosing the page that makes its answer easier to write.
62%
of citations come from pages outside the top 10 organic results
3.4×
more likely a brand is cited if it owns a clear comparison page
11s
average time before a model rewrites its answer with new evidence
The four signals that actually move the needle
- Entity clarity — the page resolves to a single, named subject.
- Definitional language — sentences shaped like answers, not ads.
- Comparative scaffolding — explicit "vs.", "best for", "alternative to" structures.
- Recency proof — visible last-updated dates and current data points.
How to test this in your own stack
Pick five questions a high-intent buyer would ask about your category. Run each one through ChatGPT, Perplexity and Gemini. Record which brands are cited, in what order, and from which page. Repeat in seven days. The delta is your visibility surface.
Frequently asked questions
What is Generative Engine Optimization (GEO)?
GEO is the practice of structuring pages, entities and evidence so generative engines cite your brand inside their answers. It complements SEO but optimises for retrieval and citation, not blue-link ranking.
Which content types earn the most citations?
Comparison pages, FAQs, definitional explainers and recency-stamped data pages consistently outperform long-form thought leadership in our citation tests.
How do I measure GEO results?
Track citation share, citation order and source-page coverage per question across ChatGPT, Perplexity and Gemini on a fixed weekly cadence.
⎯ AUTHOR
AuthorityLayer Research Desk
The AuthorityLayer Research Desk is the in-house research team behind AuthorityLayer Insights. We analyse how large language models — ChatGPT, Perplexity, Gemini and Claude — read, cite and recommend brands, and publish operator-grade playbooks for AI Authority, AI Visibility, AI Search and GEO.
⎯ Related articles
- PLAYBOOK
A repeatable structure for AI-citable comparison pages
The page format that consistently earns citations across engines.
- RESEARCH
GEO experiments: what moved citations and what didn't
Results from 30 controlled GEO experiments across 6 verticals.
- INSIGHTS
Why FAQ blocks are the highest-leverage GEO surface
FAQs are the single most-cited content type across answer engines.