Shopify furniture dimensions schema:
hasMeasurement JSON-LD for home furnishings stores

Why furniture needs hasMeasurement, not just description text

When a user asks an AI shopping agent for "a sectional sofa that fits along an 8-foot wall", the agent performs a numeric constraint check: does this product's width value fall below 96 inches? This requires dimension data to exist as a structured, unit-aware numeric value in the product's JSON-LD.

Furniture product descriptions commonly include phrases like "84W × 37D × 33H inches" or "Available in standard and apartment sizes." These are readable by humans but not reliably machine-processable for numeric filtering because:

• The agent cannot determine which number maps to which axis without explicit labels
• Inches and centimeters may both appear in the same description — the agent cannot be certain which was used for each value
• Description dimensions may be rounded, nominal, or refer to the shipping box rather than the product itself
• "Apartment size" is not a numeric value the agent can compare against a constraint

hasMeasurement solves all four problems: each QuantitativeValue entry has an explicit axis label (name), a numeric value, and an unambiguous unit code (unitCode). AI agents can directly compare value: 84 + unitCode: "INH" against the user's 96-inch constraint — no NLP parsing required.

The hasMeasurement property: what it accepts

hasMeasurement is a schema.org property on the Product type. It accepts an array of QuantitativeValue objects. Each object represents one physical measurement of the product.

measurementType values for standard dimensions

The measurementType property accepts a schema.org URL from the WearableMeasurementType enumeration. For furniture, the relevant standard values are:

For furniture-specific functional dimensions — Seat Height, Arm Height, Desk Surface Height, Drawer Depth — there are no standard schema.org enum URLs. Use a descriptive name property instead. AI agents index the name field for these specialized measurements.

UN/CEFACT unit codes for furniture

Always include both unitCode and unitText. The unitCode is used by AI agents for numeric unit-aware comparisons. The unitText is the human-readable fallback for NLP parsers that display dimension values in their responses.

Complete JSON-LD example: 84-inch performance velvet sofa

This is the recommended full implementation for a seating product. It covers overall dimensions, the critical seat height measurement, weight, and non-measurable attributes via additionalProperty.

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Elara 84-Inch Performance Velvet Sofa — Mid-Century Modern",
  "description": "Solid white oak frame with brushed brass legs and performance velvet upholstery. 84-inch 3-seat sofa seats 3 adults comfortably. Ships in 2 boxes; assembly required (est. 45 min).",
  "image": "https://your-store.myshopify.com/cdn/shop/products/elara-sofa.jpg",
  "brand": { "@type": "Brand", "name": "Elara Home" },
  "material": "Solid White Oak, Performance Velvet",
  "color": "Slate Blue",
  "hasMeasurement": [
    {
      "@type": "QuantitativeValue",
      "name": "Width",
      "value": 84,
      "unitCode": "INH",
      "unitText": "inches",
      "measurementType": "https://schema.org/Width"
    },
    {
      "@type": "QuantitativeValue",
      "name": "Depth",
      "value": 37,
      "unitCode": "INH",
      "unitText": "inches",
      "measurementType": "https://schema.org/Depth"
    },
    {
      "@type": "QuantitativeValue",
      "name": "Height",
      "value": 33,
      "unitCode": "INH",
      "unitText": "inches",
      "measurementType": "https://schema.org/Height"
    },
    {
      "@type": "QuantitativeValue",
      "name": "Seat Height",
      "value": 17.5,
      "unitCode": "INH",
      "unitText": "inches"
    },
    {
      "@type": "QuantitativeValue",
      "name": "Weight",
      "value": 142,
      "unitCode": "LBR",
      "unitText": "lbs",
      "measurementType": "https://schema.org/Weight"
    }
  ],
  "additionalProperty": [
    { "@type": "PropertyValue", "name": "Frame Material", "value": "Solid White Oak" },
    { "@type": "PropertyValue", "name": "Leg Finish", "value": "Brushed Brass" },
    { "@type": "PropertyValue", "name": "Upholstery", "value": "Performance Velvet" },
    { "@type": "PropertyValue", "name": "Assembly Required", "value": "Yes" },
    { "@type": "PropertyValue", "name": "Assembly Time", "value": "45 minutes" },
    { "@type": "PropertyValue", "name": "Room Type", "value": "Living Room" },
    { "@type": "PropertyValue", "name": "Style", "value": "Mid-Century Modern" },
    { "@type": "PropertyValue", "name": "Seats", "value": "3" },
    { "@type": "PropertyValue", "name": "Max Weight Capacity", "value": "600 lbs" }
  ],
  "offers": {
    "@type": "Offer",
    "price": "1299.00",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "url": "https://your-store.myshopify.com/products/elara-sofa"
  }
}

Why Seat Height is the most important functional dimension for seating

Ergonomic queries — "chair with 18-inch seat height for a standard desk", "sofa with low seat height under 16 inches for a contemporary look" — depend entirely on Seat Height being present as a machine-readable value. Overall Height (floor to top of back) and Seat Height (floor to top of seat cushion) are different measurements; AI agents treat them as distinct. A sofa with 33-inch overall height and 17.5-inch seat height will appear in queries for both — but only if both measurements are present in hasMeasurement.

additionalProperty for non-measurable furniture attributes

additionalProperty with PropertyValue objects handles structured attributes that aren't numeric measurements: materials, finishes, style, room type, and capacity ratings. These are indexed by AI agents for attribute-matching queries like "white oak sofa with brass legs" or "mid-century modern living room sofa under $1,500". Use explicit property names — "Frame Material" not just "Material" — for reliable attribute matching across furniture subcategories.

Furniture-specific dimensions by category

Shopify Liquid template for hasMeasurement

Store all dimension values in product metafields under the dimensions namespace (type: number_decimal for numeric values, single_line_text_field for text attributes). The Liquid template outputs a complete hasMeasurement array with conditional blocks for optional measurements.

{% comment %}
  Metafields namespace: dimensions
  Required numeric: width_in, depth_in, height_in, weight_lbs
  Optional numeric: seat_height_in, arm_height_in, surface_height_in
  Optional text: assembly_time, room_type, style, max_weight_capacity
  All dimension metafields are type: number_decimal
{% endcomment %}

{% assign mf = product.metafields.dimensions %}

"hasMeasurement": [
  {% if mf.width_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Width",
    "value": {{ mf.width_in }},
    "unitCode": "INH",
    "unitText": "inches",
    "measurementType": "https://schema.org/Width"
  },
  {% endif %}
  {% if mf.depth_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Depth",
    "value": {{ mf.depth_in }},
    "unitCode": "INH",
    "unitText": "inches",
    "measurementType": "https://schema.org/Depth"
  },
  {% endif %}
  {% if mf.height_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Height",
    "value": {{ mf.height_in }},
    "unitCode": "INH",
    "unitText": "inches",
    "measurementType": "https://schema.org/Height"
  },
  {% endif %}
  {% if mf.seat_height_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Seat Height",
    "value": {{ mf.seat_height_in }},
    "unitCode": "INH",
    "unitText": "inches"
  },
  {% endif %}
  {% if mf.arm_height_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Arm Height",
    "value": {{ mf.arm_height_in }},
    "unitCode": "INH",
    "unitText": "inches"
  },
  {% endif %}
  {% if mf.surface_height_in != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Surface Height",
    "value": {{ mf.surface_height_in }},
    "unitCode": "INH",
    "unitText": "inches"
  },
  {% endif %}
  {% if mf.weight_lbs != blank %}
  {
    "@type": "QuantitativeValue",
    "name": "Weight",
    "value": {{ mf.weight_lbs }},
    "unitCode": "LBR",
    "unitText": "lbs",
    "measurementType": "https://schema.org/Weight"
  }
  {% endif %}
]

Adding metric equivalents for international stores

For stores that sell in both US and EU markets, output a second set of hasMeasurement entries in centimeters alongside the inch entries. Liquid's times filter converts from inches to centimeters (multiply by 2.54):

{% comment %}Metric equivalents — append after each inch entry{% endcomment %}
{% if mf.width_in != blank %}
{% assign width_cm = mf.width_in | times: 2.54 | round: 1 %}
{
  "@type": "QuantitativeValue",
  "name": "Width",
  "value": {{ width_cm }},
  "unitCode": "CMT",
  "unitText": "cm",
  "measurementType": "https://schema.org/Width"
},
{% endif %}

Use the same pattern for depth, height, and seat height. Weight conversion (pounds to kilograms: divide by 2.205) uses Liquid's divided_by filter.

Metafield reference table

Create these metafield definitions in Shopify Admin under Settings → Custom Data → Products. Set all dimension fields to number_decimal type — this enforces numeric input and prevents text strings from entering dimension fields. Text attribute fields use single_line_text_field.

Common mistakes in furniture dimension schema

How AI agents use furniture dimension data

The dimension-filtering capability of AI shopping agents works through a structured lookup against indexed product graph data. When the agent receives a query like "find me a dining table that seats 8 and fits in an 8-foot dining room", it:

1. Parses the constraint: Width < 96 inches (8 feet)
2. Parses the attribute: seats 8 adults (maps to additionalProperty: Seats or seatingCapacity)
3. Queries its product index for Product nodes with a hasMeasurement entry where name = "Width", unitCode = "INH", and value < 96
4. Cross-filters against the seating capacity attribute
5. Returns matching products with dimension values cited explicitly in its response

Furniture stores that implement hasMeasurement on their full catalog — not just a few hero products — capture the entire surface area of size-constrained queries. Stores that use description text only are invisible to step 3.

Frequently asked questions

Related guides

• Ecommerce product weight and dimensions schema — QuantitativeValue patterns, unit codes, and Liquid snippets for general physical attribute markup
• Shopify schema markup: what AI agents actually read — full JSON-LD implementation guide covering Product, ProductGroup, Offer, and AggregateRating
• Ecommerce product schema markup: complete JSON-LD reference — every schema.org field AI shopping agents use in 2026
• CatalogScan blog — Shopify AI-readiness guides, structured data walkthroughs, and catalog optimization case studies

Audit dimension schema coverage across your furniture catalog

CatalogScan scans your Shopify product catalog for missing hasMeasurement entries, absent unitCode values, and dimension markup gaps — then ranks products by impact on size-filtered AI shopping query coverage.