E-Commerce Product Catalog Enrichment
Multi-modal annotation project enriching product catalog with detailed attributes, visual features, and semantic relationships to power advanced search, recommendations, and virtual try-on experiences.
The Challenge
The client had 5 million+ product listings with inconsistent descriptions, missing attributes, and poor-quality images. They needed comprehensive product annotation including attributes, categories, visual features, and text sentiment to improve search relevance and conversion rates.
Our Solution
Deployed hybrid annotation approach combining automated ML pre-labeling with human verification. Created custom taxonomy covering 2,000+ product attributes across 50 categories. Implemented active learning pipeline reducing annotation costs by 60% while maintaining quality.
Project Specifications
Data Volume
5M+ product listings, 15M+ images
Team Size
200 e-commerce specialists
Duration
4 months
Accuracy
98.1%
Annotation Types
Tools & Technologies
Deliverables
Sample Annotations
Apparel Attributes
Detailed tagging of style, color, pattern, material, fit, and occasion across 2M+ fashion items
Product Categorization
Hierarchical category assignment with 5-level taxonomy covering electronics, home goods, and fashion
Visual Feature Extraction
Automated extraction of visual attributes like brand logos, color palettes, and style elements
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