Structured Data — Products

Product-level structured data is the single most impactful GEO investment for any ecommerce site. Without it, AI systems must guess relationships between variants, reviews, pricing, and brand — and they frequently get it wrong.

This page covers every schema type needed for a complete, AI-readable product knowledge graph.

Why Product Schema is Critical

Without structured data, AI systems:

Treat each product variant as a separate, unrelated product
Fragment review authority across isolated entities
Cannot build accurate product family graphs
Lose confidence in entity matching and citation

With strong product schema, AI systems can:

Understand entire product families as connected entities
Consolidate reviews and ratings to the canonical product group
Follow explicit variant relationships
Trust pricing, availability, and specification data

1. ProductGroup Schema

ProductGroup is the parent entity for any product that has multiple variants (sizes, colors, materials, configurations). This is the most critical ecommerce schema type for GEO.

Without ProductGroup: each color of a shoe appears as a completely separate, disconnected product.
With ProductGroup: the AI understands "New Balance 990v6" as one product family with 12 color variants.

Correct Structure

{
  "@context": "https://schema.org",
  "@type": "ProductGroup",
  "@id": "https://www.example.com/product/5-inch-senko/#productgroup",
  "name": "5\" Senko Worm 10pk",
  "description": "Soft plastic stick bait for bass fishing. Known for its horizontal fall and subtle shimmy action. Effective weightless, wacky rigged, Texas rigged, or neko rigged.",
  "url": "https://www.example.com/product/5-inch-senko/",
  "productGroupID": "517",
  "category": "Soft Plastic Fishing Baits",
  "brand": {
    "@id": "https://www.example.com/#brand-yamamoto"
  },
  "variesBy": [
    "https://schema.org/color"
  ],
  "hasVariant": [
    { "@id": "https://www.example.com/product/5-inch-senko/#variant-greenpumpkin" },
    { "@id": "https://www.example.com/product/5-inch-senko/#variant-watermelon" }
  ],
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "reviewCount": "523",
    "bestRating": "5",
    "worstRating": "1"
  },
  "review": [
    {
      "@type": "Review",
      "reviewRating": {
        "@type": "Rating",
        "ratingValue": "5"
      },
      "author": {
        "@type": "Person",
        "name": "John D."
      },
      "reviewBody": "Best soft plastic for bass. The action on the fall is unmatched — especially weightless in clear water."
    }
  ]
}

GEO Benefits of ProductGroup

AI systems group all variants under one canonical entity
Reviews and ratings consolidate at the parent level (more authoritative)
Shopping Graph recognizes the product family correctly
Conversational queries like "best Senko colors" resolve to the right entity

2. `hasVariant` and `isVariantOf`

These two properties create an explicit, bidirectional relationship between a ProductGroup and its individual Product variants. Without them, variant relationships must be inferred — and AI systems often get it wrong.

Parent (ProductGroup)

"hasVariant": [
  { "@id": "https://www.example.com/product/5-inch-senko/#variant-greenpumpkin" },
  { "@id": "https://www.example.com/product/5-inch-senko/#variant-watermelon" }
]

Child (Product)

{
  "@type": "Product",
  "@id": "https://www.example.com/product/5-inch-senko/#variant-greenpumpkin",
  "name": "5\" Senko Worm — Green Pumpkin",
  "sku": "YAM-5S-GP",
  "color": "Green Pumpkin",
  "isVariantOf": {
    "@id": "https://www.example.com/product/5-inch-senko/#productgroup"
  },
  "offers": {
    "@type": "Offer",
    "priceCurrency": "USD",
    "price": "7.99",
    "availability": "https://schema.org/InStock",
    "url": "https://www.example.com/product/5-inch-senko/?color=green-pumpkin"
  }
}

Rules

Every variant Product must have isVariantOf pointing to the ProductGroup
The ProductGroup must list every variant in hasVariant
Bidirectional — both directions must be present for full graph cohesion

3. `variesBy`

variesBy tells AI systems what dimension changes between variants. Without it, engines guess the variant dimension.

"variesBy": [
  "https://schema.org/color"
]

For products that vary by multiple dimensions:

"variesBy": [
  "https://schema.org/color",
  "https://schema.org/size"
]

Supported schema.org dimension values:

Product Type	Typical `variesBy` Values
Apparel	`color`, `size`
Fishing baits	`color`
Electronics	`color`, `storageOption`
Footwear	`color`, `size`
Crossbows	`color`
Knives	`material`, `color`

4. Stable `@id` Values — Absolute URLs

The @id field creates a permanent, machine-readable identifier for every entity. This is one of the most commonly broken areas in product schema.

Rule: Always Use Absolute URLs

// BAD — relative URL, breaks in cached/detached contexts
"@id": "/product/senko/#productgroup"

// GOOD — absolute URL, works everywhere
"@id": "https://www.example.com/product/senko/#productgroup"

Why It Matters

AI crawlers frequently process:

Detached JSON-LD fragments (scraped or cached)
Partial page renders (JavaScript-heavy pages)
Headless browser captures without base URL context

Absolute URLs eliminate ambiguity, improve graph portability, and ensure entities are matched correctly across crawl sessions.

Naming Convention for `@id` Fragments

Use consistent, predictable fragment patterns:

Entity	`@id` Pattern
ProductGroup	`{canonical-url}#productgroup`
Product variant	`{canonical-url}#variant-{slug}`
Organization	`{site-root}/#organization`
Brand	`{site-root}/#brand-{brand-slug}`
BreadcrumbList	`{page-url}#breadcrumbs`

5. Brand Schema

Brands are first-class entities in AI knowledge graphs. Explicitly declaring brand entities improves product-brand association, Shopping Graph trust, and entity authority.

{
  "@type": "Brand",
  "@id": "https://www.example.com/#brand-yamamoto",
  "name": "Yamamoto",
  "url": "https://www.example.com/brands/yamamoto/",
  "logo": {
    "@type": "ImageObject",
    "url": "https://www.example.com/images/yamamoto-logo.png"
  }
}

Reference the brand by @id from ProductGroup rather than repeating the full object:

"brand": {
  "@id": "https://www.example.com/#brand-yamamoto"
}

6. Offer Schema

Offer supplies pricing, availability, and currency data that AI commerce systems use heavily for shopping answers and product comparisons.

{
  "@type": "Offer",
  "priceCurrency": "USD",
  "price": "7.99",
  "availability": "https://schema.org/InStock",
  "url": "https://www.example.com/product/5-inch-senko/?color=green-pumpkin",
  "priceValidUntil": "2026-12-31",
  "itemCondition": "https://schema.org/NewCondition",
  "seller": {
    "@id": "https://www.example.com/#organization"
  }
}

Availability values:

Value	Meaning
`https://schema.org/InStock`	Available to purchase
`https://schema.org/OutOfStock`	Currently unavailable
`https://schema.org/PreOrder`	Available for pre-order
`https://schema.org/Discontinued`	No longer manufactured
`https://schema.org/LimitedAvailability`	Low stock

7. AggregateRating Schema

AggregateRating provides social proof and authority signals that AI systems weight heavily during recommendations and comparisons.

Critical rule: Attach AggregateRating to the ProductGroup, not individual variants. Attaching it to variants splits rating authority.

"aggregateRating": {
  "@type": "AggregateRating",
  "ratingValue": "4.8",
  "reviewCount": "523",
  "bestRating": "5",
  "worstRating": "1"
}

Field	Notes
`ratingValue`	Average rating as a decimal string
`reviewCount`	Total number of reviews
`bestRating`	Max possible rating (typically `"5"`)
`worstRating`	Min possible rating (typically `"1"`)

8. Review Schema

Individual reviews provide real-world usage context and consumer sentiment that AI systems summarize when answering recommendation queries.

{
  "@type": "Review",
  "reviewRating": {
    "@type": "Rating",
    "ratingValue": "5",
    "bestRating": "5"
  },
  "author": {
    "@type": "Person",
    "name": "John D."
  },
  "datePublished": "2026-03-15",
  "reviewBody": "Best soft plastic I have ever used. The horizontal fall triggers bites that nothing else will."
}

Embed 3–5 representative reviews in the ProductGroup review array. Prioritize reviews that:

Mention specific use cases (best for clear water, best weightless)
Compare to competitor products
Include technical language (action, sink rate, hook gap)

These review types align most closely with conversational AI queries.

9. AdditionalProperty Schema

Technical attributes are the most GEO-valuable product data you can add. AI systems prefer measurable, objective facts over marketing language.

"additionalProperty": [
  {
    "@type": "PropertyValue",
    "name": "Length",
    "value": "5 inches"
  },
  {
    "@type": "PropertyValue",
    "name": "Type",
    "value": "Soft plastic stick bait"
  },
  {
    "@type": "PropertyValue",
    "name": "Best Rigging Methods",
    "value": "Wacky Rig, Texas Rig, Neko Rig, Weightless"
  },
  {
    "@type": "PropertyValue",
    "name": "Target Species",
    "value": "Largemouth Bass, Smallmouth Bass"
  },
  {
    "@type": "PropertyValue",
    "name": "Material",
    "value": "Salt-impregnated soft plastic"
  },
  {
    "@type": "PropertyValue",
    "name": "Sink Rate",
    "value": "Slow — horizontal fall"
  },
  {
    "@type": "PropertyValue",
    "name": "Recommended Hook Size",
    "value": "1/0 to 3/0 wide-gap offset"
  }
]

Attributes with the highest GEO value by product type:

Product Type	High-Value Attributes
Fishing baits	length, weight, material, sink rate, target species, hook size, action type
Crossbows	draw weight, arrow speed, power stroke, axle-to-axle width, trigger pull
Knives	blade length, steel type, blade thickness, edge geometry, handle material
Game cameras	resolution, trigger speed, detection range, wireless capability, battery life
Hearing protection	NRR rating, frequency response, battery life, Bluetooth range
Apparel	material composition, waterproof rating, insulation weight, fit type

Complete Ecommerce Schema Example

The following example combines all product schema elements into a complete @graph block:

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "@id": "https://www.example.com/#organization",
      "name": "Example Baits",
      "url": "https://www.example.com",
      "logo": {
        "@type": "ImageObject",
        "url": "https://www.example.com/logo.png"
      }
    },
    {
      "@type": "Brand",
      "@id": "https://www.example.com/#brand-yamamoto",
      "name": "Yamamoto",
      "url": "https://www.example.com/brands/yamamoto/"
    },
    {
      "@type": "ProductGroup",
      "@id": "https://www.example.com/product/5-senko/#productgroup",
      "name": "Yamamoto 5\" Senko 10pk",
      "description": "Soft plastic stick bait for bass fishing. Horizontal fall, subtle shimmy action.",
      "url": "https://www.example.com/product/5-senko/",
      "productGroupID": "517",
      "brand": { "@id": "https://www.example.com/#brand-yamamoto" },
      "variesBy": ["https://schema.org/color"],
      "hasVariant": [
        { "@id": "https://www.example.com/product/5-senko/#variant-greenpumpkin" }
      ],
      "aggregateRating": {
        "@type": "AggregateRating",
        "ratingValue": "4.8",
        "reviewCount": "523"
      },
      "additionalProperty": [
        { "@type": "PropertyValue", "name": "Length", "value": "5 inches" },
        { "@type": "PropertyValue", "name": "Target Species", "value": "Largemouth Bass, Smallmouth Bass" }
      ]
    },
    {
      "@type": "Product",
      "@id": "https://www.example.com/product/5-senko/#variant-greenpumpkin",
      "name": "Yamamoto 5\" Senko — Green Pumpkin",
      "sku": "YAM-5S-GP",
      "color": "Green Pumpkin",
      "isVariantOf": { "@id": "https://www.example.com/product/5-senko/#productgroup" },
      "offers": {
        "@type": "Offer",
        "priceCurrency": "USD",
        "price": "7.99",
        "availability": "https://schema.org/InStock"
      }
    }
  ]
}

Common Implementation Mistakes

Mistake	Impact	Fix
Attaching `AggregateRating` to individual variants	Fragments review authority	Move to `ProductGroup`
Using relative `@id` values (`/product/#group`)	Breaks entity matching in cached contexts	Use absolute URLs
Missing `isVariantOf` on child products	Breaks bidirectional graph	Add to every variant
Omitting `variesBy`	Weakens variant grouping	Add for every ProductGroup with variants
Missing `productGroupID`	Reduces Shopping Graph matching confidence	Add the internal product ID
No `additionalProperty`	AI falls back to marketing copy	Add measurable technical attributes
Schema injected client-side only	AI crawlers may miss it entirely	Render schema in initial HTML (SSR)

Why Product Schema is Critical​

1. ProductGroup Schema​

Correct Structure​

GEO Benefits of ProductGroup​

2. hasVariant and isVariantOf​

Parent (ProductGroup)​

Child (Product)​

Rules​

3. variesBy​

4. Stable @id Values — Absolute URLs​

Rule: Always Use Absolute URLs​

Why It Matters​

Naming Convention for @id Fragments​

5. Brand Schema​

6. Offer Schema​

7. AggregateRating Schema​

8. Review Schema​

9. AdditionalProperty Schema​

Complete Ecommerce Schema Example​

Common Implementation Mistakes​