Home > Enhancing Visual Search Accuracy: Yessheet Yupoo & AI-Powered Tagging System

Enhancing Visual Search Accuracy: Yessheet Yupoo & AI-Powered Tagging System

2025-07-02

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:

  1. Prioritized "holographic jacket" searches moved above the fold
  2. "None more Y2K looks" cluster organized by descending popularity
  3. 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

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