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Catalog Enrichment

[ Glossary ]

Catalog Enrichment

Catalog enrichment is the process of adding detailed metadata to product listings — occasion tags, style attributes, fit notes, complete-look pairings — beyond the standard title, price, and category fields.

Category ·

Fashion ecommerce

A bare catalog (title, price, category, size) contains the minimum data needed to sell a product through a browse-and-filter interface. An enriched catalog adds the metadata an AI system needs to reason about the product in context: what occasions it suits, what aesthetic register it belongs to, what it pairs well with, and how it fits. Enrichment can happen manually, through AI-assisted tagging from product images and descriptions, or through a combination — AI proposes tags, a human reviews. The investment is one-time per product, but it compounds: every AI recommendation that references an enriched product benefits from the added context.

A bare catalog (title, price, category, size) contains the minimum data needed to sell a product through a browse-and-filter interface. An enriched catalog adds the metadata an AI system needs to reason about the product in context: what occasions it suits, what aesthetic register it belongs to, what it pairs well with, and how it fits. Enrichment can happen manually, through AI-assisted tagging from product images and descriptions, or through a combination — AI proposes tags, a human reviews. The investment is one-time per product, but it compounds: every AI recommendation that references an enriched product benefits from the added context.

Why it matters

AI stylists are only as good as the data they reason over. A catalog with occasion tags, style attributes, and fit notes produces meaningfully better AI recommendations than a bare catalog with titles and categories. Enrichment is a one-time investment that improves every recommendation that references it.

How Elara uses it

See how Elara indexes your catalog

See how Elara enriches your Shopify catalog to power better recommendations.

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Related terms

Outfit Assembly — The AI-driven process of selecting multiple catalog pieces that work together as a complete look. Natural Language Search — Letting shoppers describe what they want in everyday language rather than keywords. Style Graph — A per-shopper taste model that learns from every interaction to produce increasingly personalized outfit recommendations.

Defined by

Mehul Agarwal, Founder & CEO

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