eCommerce - FASHION

Personalized Sizing That Fits Every Shopper

goal

Challenge Faced

Inconsistent sizing across brands and regions is a major cause of returns and poor customer experience. Traditional size charts often fail to meet individual needs.

solution

Our Solution

We developed an AI-driven size and fit engine that analyzes past purchase data, body shape, and brand-specific measurements to recommend the perfect size for each shopper.

Tools we used

Unreal Engine

Approach

Step-by-Step Workflow

Step 1

Collect user height, weight, and style preferences.

Step 2

Analyze order history and return patterns.

Step 3

Apply AI matching with brand sizing datasets.

Step 4

Display recommended size during checkout.

Quantifiable Benefits

Reduction in return rates from size mismatches
0 %
Faster purchase decisions
0 %
Increase in repeat buyers
0 %
Improved customer trust in brand consistency
0 %

Who’s Using This

Global fashion marketplaces with multi-brand catalogs

Innovation 1

Sportswear and footwear companies

Innovation-2

Apparel startups targeting personalized shopping

Private Surgical Training Institutes

Why It Matters

Personalized fit recommendations improve the buyer journey and reduce the costly cycle of shipping, returns, and replacements.

case studies

Real Results. Real Impact.

See how these use cases helped industry leaders transform operations with AI & XR.

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