Generative engine optimization has to account for how AI search actually works: not one lookup, but a keyword decomposed into 8 to 12 sub-queries spanning definitional, comparative, how-to, pricing and alternatives intent. Content that covers only the head term loses the rest to competitors. This simulator shows which sub-queries your page already answers and where the gaps sit.
How it works
Get started in 3 simple steps
Enter a target keyword and your domain URL.
The simulator fetches your sitemap, decomposes the keyword into 8-12 AI sub-queries, and matches each against your pages.
Review per-query coverage results with matched URLs and identify content gaps to fill.
Best use cases
Built for teams that take AI visibility seriously
Content strategists identifying which sub-topics to cover for a target keyword.
SEO teams auditing topical coverage against AI search decomposition patterns.
AEO strategists prioritising new content creation based on AI query coverage gaps.
One check is a snapshot. Want to see the trend?
Start free trialFAQ
Frequently asked questions
What is query fan-out?
How does this tool work?
Why does content coverage matter for AI visibility?
What's a good coverage score?
Does this need a sitemap?
Further reading
Learn the concepts behind this tool
- Query Fan-Out: How AI Expands a Single Question Into Hundreds of Discovery PathsQuery fan-out is how AI systems expand one user query into many related sub-queries before answering. Learn why it matters for AEO and how PingAura helps brands optimise across the full query network.
- How to Rank Inside ChatGPT? The Complete AEO Playbook for BrandsA practical AEO playbook to earn top ChatGPT recommendations, fix your brand narrative, and monitor AI visibility with PingAura.