Online eyewear faces a unique challenge: convincing a buyer (and an AI agent) that glasses can be purchased without physically trying them on. AI agents verify the presence of virtual try-on, lens and frame warranty, and prescription lens options before recommending. Structured data must include bridge width, UV protection, and customization options. Verity Score analyzes 4 industry-specific zones.
01 · The checklist
The data engines look for on a eyewear product page
Excerpts from the sector checklist, ranked by weight: what blocks a recommendation when missing, then what reinforces trust. The full audit monitors 100+ signals.
Required content
Industry-specific audit zones
Garantie verres et montures visible sur PDP (durée, casse, rayures)
Virtual try-on ou essai à domicile visible above-fold sur PDP
Options verres (progressifs, anti-reflet, transitions) clairement listées
Réseau opticien ou prise de RDV accessible depuis la PDP ou header
Trust signals
Expected UX patterns
Virtual try-on via camera or photo upload with face detection
Face shape guide to recommend the ideal frame
02 · Industry benchmarks
Reference values for a eyewear page
Internal reference valuesPer-sector reference targets defined by Verity Score, not measured on a sample of stores.
03 · Required schema.org
The markup engines can read
Copy the structure and adapt the values to your pages.
"additionalProperty": [{"@type": "PropertyValue", "name": "Bridge Width", "value": "18", "unitText": "mm"}]"additionalProperty": [{"@type": "PropertyValue", "name": "UV Protection", "value": "UV400"}]05 · Frequent questions
Your questions about AI engines
Is virtual try-on detected by AI agents?
Yes. AI agents detect virtual try-on presence and value it as a strong trust signal. It's a major differentiator for AI recommendation in eyewear.
How should I structure frame dimensions for AI?
Use additionalProperty with name='Bridge Width' value='18' unitText='mm'. AI agents use this data to match recommendations with morphological preferences.
Should UV protection be in schema.org?
Yes. Add additionalProperty name='UV Protection' value='UV400'. It's a key filtering criterion for AI agents, especially for sunglasses.
Does an optician network impact GEO score?
Yes. The audit evaluates optician network presence or appointment booking availability. It's a strong trust signal for both AI and buyers.
What specific zones does Verity Score analyze for eyewear?
lens and frame warranty, virtual try-on, prescription lens options and optician network. Plus 39+ cross-industry zones.
Do sunglasses and prescription frames fall under the same EU regime?
No, and the confusion is expensive. Sunglasses are personal protective equipment under Regulation (EU) 2016/425, with harmonised standard EN ISO 12312-1:2022 defining filter category (0 to 4), luminous transmittance and UV protection. Prescription frames are Class I medical devices under Regulation (EU) 2017/745 (MDR), and therefore subject to EUDAMED registration, mandatory since May 28, 2026. Expose filter category for your sunglasses and medical device status for your frames : these are two distinct proofs AI agents can verify.
Which ChatGPT product feed fields are useful for eyewear?
The OpenAI spec (Agentic Commerce developer docs, consulted August 13, 2026) provides model_3d_url for a 3D product model, extending your virtual try-on into the feed itself, plus size, size_system and variant_dict to carry frame dimensions (bridge width, lens width, temple length) variant by variant. Also populate material for the frame material : it's a frequent filtering criterion (acetate, titanium, metal).
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