Shift
From search engines to answer engines.
Traditional SEO was built for a list of links.
AI assistants generate answers instead.
That changes how discovery works and how brands compete.
Category primer
Generative Engine Optimisation (GEO). The new layer of product discovery.
GEO is the emerging discipline of structuring product content so AI assistants can understand and recommend it. Geoffy's approach to GEO is called Reference Engineering — we publish coherent, first-party Reference Pages that AI assistants can read, trust, and recommend across every level of buyer intent.
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
Definition
A simple GEO definition
GEO means structuring product information so AI assistants can interpret and recommend products.
Why this matters
Why traditional SEO is not enough.
AI systems evaluate structure, context and trust differently.
Most product pages were not written for machine reasoning.
SEO vs AEO vs GEO
SEO, AEO and GEO: what is the difference?
They are related, but they solve different discovery problems.
SEO is mostly about ranking pages, AEO is about concise extracted answers, and GEO is about making products recommendation-ready inside assistant-generated responses.
SEO: rank in results
AEO: extracted answers
GEO: AI recommendations
Model
SEO
rank pages in search engines.
Model
AEO
appear in extracted answers and snippets.
Model
GEO
be included in AI-generated answers and recommendations.
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
Discovery paths
The route from question to recommendation changes across each model. GEO focuses on the full recommendation journey.
SEO: User -> Google -> list of links -> click
AEO: User -> search engine -> extracted answer
GEO: User -> AI assistant -> synthesised answer -> product recommendations
Core concept
Geoffy's approach to GEO: Reference Engineering
GEO is a category. Reference Engineering is how Geoffy practises it. We structure product meaning so AI assistants can understand, compare, and recommend your catalogue with confidence.
Reference Engineering focuses on recommendation readiness — not rankings, not keyword volume, not click-through. The output is a Reference Page: a first-party, coherent, question-answer surface engineered for how AI models actually read.
Geoffy makes products easier for AI assistants to interpret, compare, and recommend at scale.
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
In practice
Discovery happens through questions.
AI assistants respond to natural-language product questions.
GEO builds pages that answer those questions clearly.
How teams implement GEO
Reference Pages are the building blocks.
Geoffy builds Reference Pages at scale — each one engineered around a real customer question. Every Reference Page contains everything an AI assistant needs to recommend your product with confidence: structured meaning, first-party content, and coverage across the Intent Tiers (Broad, Mid, Ultra).
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
Coverage
Coverage across every level of customer intent.
From broad questions to highly specific use cases, GEO coverage expands where AI recommendations are made.
Platform support
Built for modern commerce platforms.
Geoffy connects directly to commerce and content platforms to build a first-party AI discovery layer.
Shopify
available now
WordPress
available now
Magento
planned
BigCommerce
planned
Adobe Commerce
planned
Trust model
Transparency matters.
Not all GEO approaches are equal. Some rely on hidden content, cloaking, or synthetic tactics that break the moment AI models update. Geoffy's Reference Engineering is visible, first-party, and structured by default.
This animation illustrates how Geoffy converts ecommerce catalogue data into GEO bundles - structured discovery pages designed to help AI assistants understand when a product is relevant to a user's question.
No cloaking
No hidden prompts
First-party pages
Structured outputs
Transparent outputs
FAQ
Common questions about GEO
Everything you need to know about GEO.
Is GEO replacing SEO? +
No. GEO is a distinct practice focused on AI recommendations, not search ranking. Geoffy's specific practice within GEO is called Reference Engineering — structured, first-party Reference Pages that sit alongside SEO, not instead of it.
Do GEO pages replace product pages? +
No. Reference Pages live alongside product pages — they are first-party discovery surfaces engineered for how AI assistants read, not replacements for existing product listings.
Do GEO strategies require hidden content? +
No. Geoffy's Reference Engineering is visible, first-party, and structured by default.
Which platforms does Geoffy support? +
Shopify now. WordPress now. Magento, BigCommerce and Adobe Commerce planned.
Why does structured data matter? +
It helps machines interpret content reliably.
Next step
Start publishing Reference Pages today.
Turn your catalogue into AI-readable discovery pages and structured outputs.
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Structured outputs enabled
First-party pages published
Discovery coverage expanding