B2B Product Data
For manufacturing websites, GEO is often blocked by inconsistent technical parameters. AI systems cannot confidently recommend a supplier when product specs mix units, hide tolerances, or bury certifications in images.
Parameter structure rules
| Rule | Bad format | Better format |
|---|---|---|
| Unit consistency | 800mm / 80 cm / 0.8m on the same page | Use one primary unit and map unitCode where possible. |
| Tolerance visibility | “high precision” | Positioning accuracy: 0.008 mm; repeatability: 0.005 mm. |
| Certification mapping | “CE approved” as text only | Certification name, issuer, certificate number, scope, and expiry date. |
| Application context | Generic feature list | Match specs to buyer scenarios: material, throughput, environment, compliance. |
Product Schema example
Use additionalProperty with PropertyValue for measurable B2B specifications. Do not stuff all parameters into one description field.
{
"@context":"https://schema.org",
"@type":"Product",
"name":"Example CNC Machining Center",
"brand":{"@type":"Brand","name":"Example Brand"},
"additionalProperty":[
{"@type":"PropertyValue","name":"X-axis travel","value":"800","unitCode":"MMT"},
{"@type":"PropertyValue","name":"Spindle speed","value":"12000","unitText":"rpm"},
{"@type":"PropertyValue","name":"Positioning accuracy","value":"0.008","unitCode":"MMT"}
]
}
Recommended B2B specification table
- Product model or series name.
- Core performance parameters with units.
- Operating environment and material compatibility.
- Certification and test standard references.
- Customization boundaries: MOQ, OEM/ODM scope, drawings required, tooling/NRE if applicable.
AI Citation Risk
If important specs exist only in images, PDFs without text layers, or inconsistent tables, AI engines may ignore them or hallucinate them. Structured HTML tables plus JSON-LD reduce that risk.