Core Concepts

Before diving into the features, it's helpful to understand the key concepts and terminology used throughout MerchantOps.

Product Lakehouse

The Product Lakehouse is a staging area where raw product data lands before being promoted to your main catalog. Think of it as an inbox for your product data.

When you upload a document or import products, they first appear in the Lakehouse where you can:

• Review extracted data for accuracy
• Verify column mappings from source files
• Clean up any parsing issues
• Promote approved products to the Catalog

This two-stage approach ensures that only verified, quality data enters your main product catalog.

Catalog

The Catalog is your main product database containing verified, enriched products. Products in the Catalog have been through the ingestion process and are ready for export to your ecommerce platforms.

Key capabilities in the Catalog:

• Full-text search across all product fields
• Filtering by brand, product type, enrichment status, and more
• Batch operations (enrich, export, delete)
• Individual product editing
• Version history tracking

Attributes

Attributesare the individual properties that describe a product. Examples include "Color", "Size", "Material", "Weight", and "Warranty".

Each attribute has:

• Key: A unique identifier (e.g., color, weight_oz)
• Name: Human-readable display name
• Type: Data type (enum, text, number, boolean, date)
• Values: For enum types, the allowed values list

The Attribute Dictionary is where you define all available attributes for your organization. This ensures consistency across all products.

Attribute Types

Product Types

Product Typesare templates that define which attributes are relevant for a category of products. For example, a "Golf Club" product type might require attributes like "Shaft Flex", "Loft Angle", and "Club Type", while a "Golf Ball" product type might require "Compression" and "Cover Material".

Product Types help with:

• Ensuring products have all required attributes
• Guiding the AI enrichment process
• Organizing your catalog by category
• Filtering and faceted search

Enrichment

Enrichment is the process of enhancing product data using AI. When you enrich a product, MerchantOps:

1. Analyzes the existing product data
2. Searches brand websites for additional information
3. Extracts attributes from product pages
4. Generates AI-optimized, discoverable descriptions
5. Standardizes values against your attribute dictionary

Each product has an Enrichment Status:

Products also receive an Enrichment Score (0-100) indicating the quality and completeness of the enriched data.

Jobs

Jobs are background tasks that process data asynchronously. Long-running operations like document ingestion, batch enrichment, and exports run as jobs so you can continue working while they process.

Job types include:

• document_ingestion: Processing uploaded files
• enrichment: AI product enrichment
• crawl: Web scraping brand websites
• export: Generating export files

You can monitor job progress in real-time on the Jobs page, including percentage complete, items processed, and any errors.

Versions

MerchantOps maintains a complete version history for each product. Every time a product is modified (manually or through enrichment), a new version is created.

This allows you to:

• View how a product has changed over time
• Compare different versions side-by-side
• Revert to a previous version if needed
• Track who made changes and when

Technologies (Brand Sources)

Technologies represent brand or vendor sources in the Lakehouse. When you upload products from a vendor catalog, MerchantOps groups them under a Technology entry.

Technologies can have:

• Source URLs for web scraping
• Linked products from that brand
• Custom metadata about the brand

Next Steps

Now that you understand the core concepts, you can:

• Create your account and set up your organization
• Upload your first document to start importing products
• Set up your attribute dictionary to define your product schema