Intelligent Product Classification with LLMs: Transforming Retail Catalog Management
A global online retailer managing a catalog of over 1 million SKUs faced increasing complexity in product classification. Maintaining accurate, searchable product categories became an operational burden with a constant inflow of supplier-uploaded items, often incomplete, duplicated, or inconsistently labeled.
Manual tagging by internal teams took days, lacked consistency, and often led to:
- Misclassified or uncategorized products
- Poor searchability and recommendations
- Increased returns due to wrong product placement
- Frustration for both customers and merchandising teams
The Challenge: Product Chaos in Retail Catalogs
- Product titles and descriptions from suppliers varied widely in tone, detail, and structure
- Category trees were deep, multilingual, and often changed seasonally
- Manual classification couldn’t keep up with the daily product inflow
- Retail teams lacked a central intelligence layer to validate and standardize data
The Amantra Solution: LLM-Based Catalog Classification Engine
Amantra implemented an Intelligent Document Processing solution to automate product classification, adapting seamlessly to complex retail data structures and dynamic taxonomies. The system can't:- Parsed and understood product titles, descriptions, and attributes
- Enriched missing metadata by extracting insights from unstructured product text
- Assigned the most accurate category using contextual semantic understanding
- Flagged edge cases or ambiguous products for human review (human-in-the-loop)
- Continuously improved through feedback from merchandisers
Solution Highlights
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- Multilingual Support for International Catalogs
- Self-Training LLMs to adapt to seasonal and regional taxonomies
- Context-Aware Classification for Ambiguous SKUs
- Taxonomy Management Interface for admin control
- API Integration with PIM and e-commerce CMS systems
Client Testimonial
"Amantra LLM-based system doesn’t just tag products it understands them like a merchandiser would. We’ve significantly improved catalog hygiene and customer experience." — Head of Digital Commerce, Global RetailerWhy LLMs Are a Game-Changer for Retail Catalogs
LLMs bring semantic understanding to product data, enabling AI to:- Decode unstructured supplier input
- Auto-fill missing details
- Map products to complex, hierarchical taxonomies
- Learn continuously from user behavior and admin feedback