Build your own AEO + GEO ontology.
Most companies try to win AI search by writing more content. That's backwards. The companies actually showing up inside ChatGPT, Perplexity, and Google AI Overviews built something different first — a structural map of how their business's concepts connect. This guide walks you through the 7-step process we use with RAMMP clients to do that work.
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What's inside.
The 7 steps, in order. Plus an honest read on what you can do yourself and where the work gets genuinely hard.
Identify your category-defining terms
The 8–20 concepts your buyers ask about, that you've coined, or that you're constantly explaining.
Classify each term by ownership tier
Owned, reframed, adjacent, distracting. Not every term deserves a page.
Map the relationships
Part of, produces, constrains, resolves into, operationalises. This is what turns a glossary into a graph.
Choose your register
Encyclopaedic, technical specification, or reference manual. Pick one. Use it everywhere.
Structure each page identically
A 9-section skeleton that gives AI engines a predictable place to find each fact.
Map the ontology to JSON-LD
Stable URIs, bidirectional links, one canonical set. The schema patterns that turn pages into a knowledge graph.
Set the governance layer
Without governance, your ontology drifts. The monthly maintenance commitment most companies underestimate.
DIY vs. consultation
Honest read on what you can do in-house, and where the work gets harder than it looks.
The companies winning AI search aren't writing more content. They built a knowledge graph first. Then the pages wrote themselves.
Dr Anna Harrison — Founder, RAMMP
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