GEO · ON-PAGE GEO
On-page GEO: give the model something specific enough to recommend.
Engines can only recommend what they can parse and verify. On-page GEO is the structured product truth - schema, attributes, feeds, and question-shaped content - that makes your catalog quotable.
Most catalogs fail here before anything else. Thin attributes and marketing-language descriptions give a model nothing checkable to say, so it reaches for a competitor whose data actually answers the constraint.
What the work is
Product schema and structured data
Product, Offer and AggregateRating markup, validated, so every item can be cited precisely rather than approximately.
Attribute depth and feed health
The specification fields models match constraints against. Missing attributes are the single most common reason a product drops out of a narrowing conversation.
Question-shaped content
Use-case and comparison content written the way buyers ask, so there is something to quote for intents your PDP does not answer.
Entity consistency
One coherent brand and product identity across your site, feed and third-party listings, so the model resolves you as a single trusted entity.
Deliverables
- Schema audit and implementation across templates
- Attribute and feed gap analysis at SKU level
- Question-shaped content plan built from panel data
- Re-measurement against the locked prompt panel
The rest of GEO
GEO overview
How the three pillars fit together.
Answer Engine Optimization
Where broader GEO builds the conditions for a model to trust you, AEO is the sharp end: structuring a specific, checkable answer to a specific question so cleanly that the engine prefers to quote you over paraphrasing someone else.
Off-Page GEO
This is where most brands are weakest and where the surfaces are most consistent: the sources AI cites for buying decisions are rarely brand-owned.
Digital PR & Authority
Authority is the slowest pillar and the one competitors cannot copy.
Questions
What counts as on-page GEO?
Everything an engine reads on your own properties: structured data, product attributes, merchant feed quality, page content, and the consistency of your brand and product identity across all of them.
Which fix matters most?
Usually attribute completeness. In our own panel data, products that dropped out of AI shelves overwhelmingly lacked the specific evidence needed to match a shopper's stated constraint — price alone did not carry them.
Do I need to rebuild my PDP?
Rarely. Most of this is data and markup work behind the existing template, plus targeted content for intents the PDP does not cover.