The Semantic Classification Bridge is a data modeling design pattern used to represent complex product attributes in a reusable and scalable way. Instead of relying on flat enums or repeated fields inside product shapes, this pattern separates classification data into dedicated documents that can be enriched, related and shared across many products. This provides better consistency, supports localization, and improves the storytelling capability of product data.

The semantic classification bridge separates product identity from classification logic.
Products keep their core data. Classification is represented as independent documents that may include descriptions, imagery, metadata and relations. The bridge is created by linking products to these classification documents using reference components. This enables a flexible and expressive product model that can evolve without structural changes to product shapes.
Using classification as separate documents allows for richer storytelling and governance across large catalogues.
Key benefits:
Use this pattern when:
In Crystallize, classifications are modeled as documents with their own shapes. Products reference these documents via component relations.
This allows:
A typical approach is: