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Product Identity Model: ASIN, SKU, Variant and EVA Product

Product Identity Model: ASIN, SKU, Variant and EVA Product

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Products in EVA are not defined by a single identifier. Instead, they are built using multiple identifiers coming from different systems.

Each channel has its own way of identifying products, and EVA creates a unified product identity by connecting these structures.

The Big Picture

A single product can exist as different entities across systems.EVA does not replace these identities. It connects them into one unified product model.

The Identity Layers

Amazon identity (ASIN-based)

Amazon products are structured around:

  • ASIN
  • Parent ASIN
  • SKU

The ASIN represents the product listing, while SKU represents the seller-specific inventory unit.

A single Parent ASIN may contain multiple child ASINs.

Shopify identity (variant-based)

Shopify products are structured differently.

Each product can have multiple variants, and each variant includes:

  • Variant ID
  • SKU
  • Price
  • Inventory

This means one Shopify product may result in multiple rows in the catalog.

EVA identity (Unified Product)

EVA creates a new identity layer when products are matched.

This is called the unified product.

A unified product can include:

  • One or more Amazon ASINs
  • One or more Shopify variants

This creates a single product representation across systems.

The Logic

EVA does not assume products are the same across channels.

Instead, it follows this logic:

  1. Treat each channel identity independently
  2. Use matching to connect related entities
  3. Create a unified product only after confirmation

The unified product becomes the reference point for cross-channel operations.

Relationship Structure

The model can be summarized as:

  • One unified product

    → can include multiple Amazon ASINs

    → can include multiple Shopify variants

This allows EVA to handle:

  • Product bundles
  • Multi-variant products
  • Cross-listings

Why This Matters

Without a structured identity model:

  • The same product could appear disconnected across systems
  • Performance data would be fragmented
  • Decisions would be based on incomplete information

With this model:

  • Product performance can be analyzed holistically
  • Actions can be applied consistently
  • Data remains structured and traceable

Key Value Pillars

Multi-source compatibility

Supports different product structures across channels.

Flexible product mapping

Handles one-to-one and one-to-many relationships.

Consistent product identity

Creates a single reference point for analysis and actions.

Pro Insight

SKU is often the strongest signal when matching products across systems.

While titles and prices can vary, SKU alignment usually indicates the same underlying product.