AI & Machine Learning
Virtual Try-On Feature for Cosmetic Multi-National
AI-powered virtual makeup experience that revolutionized online cosmetics shopping
Business Challenge
A leading cosmetic multinational company faced significant challenges with online sales conversions. Customers were hesitant to purchase makeup products online without trying them first, leading to low conversion rates and high return volumes.
Key Challenges:
- • Low online conversion rates due to inability to try products
- • High return rates (35%) for color-mismatched products
- • Limited customer engagement on digital platforms
- • Difficulty showcasing product variety and shades
- • Competition from brick-and-mortar stores with try-on facilities
- • Need for innovative digital customer experience
Our AI Solution
We developed an advanced AI-powered virtual try-on system using computer vision and augmented reality technologies that allows customers to virtually apply makeup products in real-time using their device camera.
AI Features Implemented:
- • Real-time facial landmark detection and tracking
- • Advanced color mapping and skin tone analysis
- • AR-based lipstick, eyeshadow, and foundation application
- • Machine learning-driven shade recommendations
- • Cross-platform compatibility (web, mobile, AR mirrors)
- • Social sharing capabilities with virtual looks
Technical Implementation
Computer Vision
- • 68-point facial landmark detection
- • Real-time face tracking (30 FPS)
- • Lighting condition adaptation
- • Multiple face angle support
AI Engine
- • Deep learning color matching
- • Skin tone classification (16 categories)
- • Texture mapping algorithms
- • Personalized recommendations
Key Features
Product Categories
- • Lipstick (300+ shades)
- • Foundation (50+ tones)
- • Eyeshadow (200+ colors)
- • Blush and highlighter
User Experience
- • Instant product application
- • Before/after comparison
- • Look saving and sharing
- • Video recording capability
Results & Impact
Business Impact:
- • 40% increase in online sales conversion
- • 60% reduction in product returns
- • 300% increase in customer engagement time
- • 85% customer satisfaction with virtual try-on
- • 50% increase in average order value
- • 95% accuracy in color matching
Before Implementation
- • 12% online conversion rate
- • 35% return rate
- • 2 min average session time
- • Limited customer engagement
After Implementation
- • 17% online conversion rate
- • 14% return rate
- • 8 min average session time
- • High social media sharing
Project Details
Industry
Beauty & Cosmetics
Company Type
Multi-National Corporation
Project Type
AI & Computer Vision
Duration
8 months
Technologies Used
Computer VisionDeep LearningAR/VRTensorFlowOpenCVWebGLJavaScriptReact Native
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