Business requirements and technical realization
Apparel e-commerce companies face return rates as high as 25-40%, mainly due to improper sizing/fitting.Pixelcut'svirtual try-onThe function generates real fitting results.
Operation Flowchart
- Step 1: Prepare the material
Upload garment layouts (white background recommended) and model templates (or full body shots uploaded by customers) - Step 2: AI Matching
Select "Virtual Try-On", the system automatically matches the garment to the model's body type, and supports adjusting the naturalness of the pleats. - Step 3: Presentation from multiple angles
Generate front/side/back views (Pro version feature), add scale parameters
Tips for Increasing Conversion Rates
- Generate model demos with different skin tones for the same garment
- With "recoloring" to show optional colors
- Output GIF to show dynamic fitting effect
- Instant previews embedded in product detail pages via APIs
caveat
Need to mark "AI simulation effect" to avoid legal risks; suggest to keep 10% error tips
This answer comes from the articlePixelcut: a one-click AI tool for editing photosThe
May not be reproduced without permission:AI productivity tools " How to implement a virtual try-on feature for apparel e-commerce to reduce return rates?
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