Problem
As a retailer, you may be enriching product data manually by copying and pasting between systems, reformatting content, and relying on team-specific processes. This results in inconsistent listings, slower time-to-market, and higher error rates across sales channels. Common limitations include:- No standardized validation of required fields.
- Manual processes prone to human error.
- Lack of a centralized system for enrichment across teams.
- Difficulty optimizing product content for different sales channels.
Solution
With fabric Product Catalog, you can enrich product data with precision and scale. Using structured schemas, validations, formulas, and AI-powered content, you can ensure every product is channel-ready before publishing.Key capabilities
- Configure attributes globally, by category, or by individual product.
- Attribute formulas that auto-generate values like product names, weights, and sizes.
- Update multiple products in bulk with CSV imports.
- Tailor product descriptions for SEO, channel standards, and brand voice with Product Catalog AI.
Example Scenario
A home goods retailer sells through three channels: a branded ecommerce site, Amazon, and regional marketplaces in North America. Each channel has unique requirements:- Amazon: Structured specs with character limits.
- DTC site: SEO-optimized, brand-aligned copy.
- Marketplaces: Localized content and unit conversions.
- A global data structure supports both universal and channel-specific attributes.
- Calculations populate attributes, such as volume or weight.
- AI tools generate channel-specific descriptions.
- Validations ensure required fields are completed before publishing.
- Bulk tools streamline mass edits and updates.
Outcome
- Higher data accuracy: Fewer errors across channels.
- Reduced manual work: Bulk and AI tools speed up enrichment.
- Improved conversion: Optimized listings drive better customer engagement.
- Lower return rates: Accurate, tailored content reduces buyer confusion.