Ecommerce Product Weight and Dimensions Schema for AI Shopping Agents

Why Physical Dimensions Matter for AI Agent Matching

When a user asks an AI shopping agent for "a suitcase that fits in an overhead bin" or "a microwave under 18 inches wide for a studio kitchen", the agent needs to perform a numeric constraint match: does this product's width value fall below 18 inches? This requires the dimension to exist as a structured, unit-aware numeric value — not buried in a paragraph of description text.

Text parsing can extract "18 inches wide" from a description, but it cannot reliably:

• Distinguish product dimensions from package dimensions
• Convert between unit systems (inches vs. centimeters) to compare against a user's query
• Determine which axis is which when dimensions are listed in a non-standard order
• Handle ambiguous statements like "fits a standard 18-inch space" (clearance ≠ product width)

Schema.org's dimension properties solve all four problems with explicit axis labels, unit codes, and numeric values that AI agents can compare directly.

Core Schema.org Dimension Properties

The schema.org Product type has four built-in physical property fields:

Note: schema.org does not have a length property on Product. Use depth for the front-to-back or longest dimension. For products where "length" is the primary dimension (e.g., a rope, a cable, a board), use depth with an explicit unitText label, or use additionalProperty with propertyID: "length".

UN/CEFACT Unit Codes Reference

The unitCode field on QuantitativeValue uses UN/CEFACT Recommendation 20 codes. Use these for maximum AI agent compatibility:

Full JSON-LD Example: Carry-On Luggage

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Hardshell Carry-On Spinner — 22\" Cabin Max",
  "weight": {
    "@type": "QuantitativeValue",
    "value": 3.2,
    "unitCode": "KGM",
    "unitText": "kg"
  },
  "width": {
    "@type": "QuantitativeValue",
    "value": 38,
    "unitCode": "CMT",
    "unitText": "cm"
  },
  "height": {
    "@type": "QuantitativeValue",
    "value": 56,
    "unitCode": "CMT",
    "unitText": "cm"
  },
  "depth": {
    "@type": "QuantitativeValue",
    "value": 22,
    "unitCode": "CMT",
    "unitText": "cm"
  },
  "additionalProperty": [
    {
      "@type": "PropertyValue",
      "propertyID": "dimensions",
      "name": "Dimensions (W × H × D)",
      "value": "38 × 56 × 22 cm (15\" × 22\" × 8.7\")"
    },
    {
      "@type": "PropertyValue",
      "propertyID": "shippingWeight",
      "name": "Shipping Weight (packaged)",
      "value": "3.8 kg"
    },
    {
      "@type": "PropertyValue",
      "propertyID": "cabinCompliant",
      "name": "Cabin Carry-On Compliant",
      "value": "IATA standard: 56 × 45 × 25 cm — this bag qualifies"
    }
  ]
}

Desk organizer with capacity volume

{
  "@type": "Product",
  "name": "Bamboo Desk Organizer — 5 Compartment",
  "width": { "@type": "QuantitativeValue", "value": 24, "unitCode": "CMT", "unitText": "cm" },
  "height": { "@type": "QuantitativeValue", "value": 10, "unitCode": "CMT", "unitText": "cm" },
  "depth": { "@type": "QuantitativeValue", "value": 14, "unitCode": "CMT", "unitText": "cm" },
  "weight": { "@type": "QuantitativeValue", "value": 420, "unitCode": "GRM", "unitText": "g" },
  "additionalProperty": {
    "@type": "PropertyValue",
    "propertyID": "dimensions",
    "value": "24 × 10 × 14 cm (9.4\" × 3.9\" × 5.5\")"
  }
}

Shopify Liquid Implementation

Shopify stores weight in the variant weight field (accessible as variant.weight in grams). Dimensions require a product metafield. Recommended metafield structure:

{% comment %}
  Metafields (all in namespace 'dimensions'):
  - width_cm   (number_decimal)
  - height_cm  (number_decimal)
  - depth_cm   (number_decimal)
{% endcomment %}

{% assign v = product.selected_or_first_available_variant %}
{% assign weight_kg = v.weight | divided_by: 1000.0 %}

"weight": {
  "@type": "QuantitativeValue",
  "value": {{ weight_kg }},
  "unitCode": "KGM",
  "unitText": "kg"
},

{% if product.metafields.dimensions.width_cm %}
"width": {
  "@type": "QuantitativeValue",
  "value": {{ product.metafields.dimensions.width_cm }},
  "unitCode": "CMT",
  "unitText": "cm"
},
"height": {
  "@type": "QuantitativeValue",
  "value": {{ product.metafields.dimensions.height_cm }},
  "unitCode": "CMT",
  "unitText": "cm"
},
"depth": {
  "@type": "QuantitativeValue",
  "value": {{ product.metafields.dimensions.depth_cm }},
  "unitCode": "CMT",
  "unitText": "cm"
},
{% endif %}

Dimension Markup by Product Category

Prioritize dimension markup for categories where size is a primary purchase qualifier:

Product vs. Shipping Dimensions

AI agents matching size constraints are looking for product dimensions — the physical size of the item itself, not the shipping box. Use schema.org's weight/width/height/depth for product dimensions, and additionalProperty for shipping dimensions:

"additionalProperty": [
  {
    "@type": "PropertyValue",
    "propertyID": "shippingWeight",
    "name": "Shipping Weight (packaged)",
    "value": "3.8 kg"
  },
  {
    "@type": "PropertyValue",
    "propertyID": "shippingDimensions",
    "name": "Shipping Box Dimensions",
    "value": "42 × 60 × 28 cm"
  }
]

Shopify's shipping weight (the value you set in product variants for shipping calculations) is the packaged weight. If you need to expose the bare product weight, store it in a dimensions.product_weight_kg metafield.

Weight and Dimensions Markup Checklist

1. Create metafields in Shopify Admin: dimensions.width_cm, dimensions.height_cm, dimensions.depth_cm (number_decimal type)
2. Populate metafields for all products where size is a purchase qualifier (prioritize luggage, furniture, appliances, fitness, storage)
3. Add weight to your Product JSON-LD using variant.weight (already stored in Shopify in grams — divide by 1000 for KGM)
4. Add width, height, depth from metafields with unitCode: "CMT"
5. Add an additionalProperty with propertyID: "dimensions" and a human-readable dual-unit string for NLP fallback
6. Use additionalProperty for shipping weight and shipping box dimensions — keep separate from product dimensions
7. For volume-critical products (containers, bottles), add additionalProperty with propertyID: "capacityVolume"
8. Validate JSON-LD with Google's Rich Results Test after Liquid template changes
9. Ping IndexNow with updated product URLs

Related Resources

• Shopify Schema Markup Guide — full JSON-LD implementation guide for Product, Offer, and QuantitativeValue blocks.
• Shopify Variant Option Naming for AI Agents — how size options in variant pickers relate to structured data dimensions.
• Shopify Digital Product Delivery Schema — fileSize and contentSize patterns for digital goods.
• AI Shopping Agent Product Ranking Factors — full 18-signal model including physical attribute completeness.

Frequently Asked Questions

Audit Physical Attribute Coverage Across Your Catalog

CatalogScan scans your product catalog for missing weight and dimension signals, incorrect unit codes, and physical attribute markup gaps — then ranks them by impact on size-filtered AI agent query coverage.