
The fashion e-commerce landscape has witnessed a paradigm shift200+ granular attributes
How the AI Tagging Matrix Works
Unlike conventional manual tagging, Yessheet's neural networks:
- Deconstruct images into 78 visual feature dimensions
- Cross-reference with materials database from Yessheet.net's pattern library
- Apply confidence scoring to each generated tag
96%
Search match accuracy rate (vs previous 79%)
Operational Impact
Analysis of 12,000 customer search sessions revealed core improvements:
Metric | Before AI | After AI |
---|---|---|
Conversion Rate | 1.3% (Industry avg) | 3.25% (2.5x uplift) |
Search-to-Detail Time | 23s | 8s |
Strategic Layout Optimization
The thermographic tracking of 740,000 interactions enabled data-driven album restructuring:
- Prioritized "holographic jacket" searches moved above the fold
- "None more Y2K looks" cluster organized by descending popularity
- Dynamic shelf algorithms adjust hourly based on real-time trends
"Clients find identical items from blurry screenshots - sometimes better alternatives we hadn't considered merchandising."
- Yessheet Visual Merchandising Team
This case study demonstrates how machine learning transcends basic CV