Sizing Returns Cost 25% of Apparel Revenue
Customers order multiple sizes and return what does not fit, costing brands 25-35% in return shipping and restocking. Generic size charts do not account for brand fit variations. Customers do not know their measurements. Inconsistent sizing across products causes frustration.
Perfect Fit Recommendations Every Time
AI size recommender where customers answer 4 questions (height, weight, fit preference, problem areas), system analyzes return data and reviews to understand how each product fits, recommends size with confidence level, and learns from customer feedback--reducing sizing returns 35%.
Customer quiz: height, weight, usual size, fit preference (tight/loose)
AI analyzes: return patterns, reviews mentioning fit, size distribution data
Recommends size: "Size M (90% confidence) - This item runs large"
Explains reasoning: "Based on your height 5'9\", we recommend M. 78% of similar customers kept M."
Learns from feedback: "Was recommendation correct?" improves future accuracy
Mobile-optimized widget integrates with product pages
From Measurements to Recommendation
Customer Input
Customer browsing jeans enters: 5'10\", 175 lbs, usually size 32, prefers regular fit.
AI Analysis
System checks jean return data: \"Size 32 has 45% return rate for 'too tight' from similar customers.\"
Size Recommendation
Recommends size 33: "This jean runs slim. 82% of customers your build wear 33."
Feedback Loop
Customer purchases 33, keeps it. System learns: refines recommendation for similar customers.
Key Features
Fit Type Detection
Understands: slim fit, regular fit, relaxed, oversized. Recommends based on customer preference and product cut.
Body Type Matching
Matches customer to similar builds who purchased. "Customers your height/weight kept size 32 88% of time."
Review Mining
Analyzes reviews: "Runs small", "Size up", "True to size". Incorporates into recommendations.
Confidence Scoring
Shows confidence: "95% confident - strong data" vs. "65% - limited data for this product."
Size Recommendation Stack
Who Benefits?
Apparel Brands
Reduce sizing returns from 30% to 18%. Save $100K+ annually in return shipping and restocking.
Footwear Retailers
Recommend shoe sizes accounting for brand fit differences. Nike vs. Adidas size differently.
Plus-Size Fashion
Provide confident recommendations where sizing is notoriously inconsistent. Build customer trust.