Online returns
Online orders were returned at a rate of 19.3% in 2025, compared to 15.8% across retail overall — totaling an estimated $849.9 billion in merchandise returns industry-wide.
Of all retail returns in 2025 were classified as fraudulent by retailers, including practices like overstated return quantities and "box of rocks" empty-box returns.
Virtual try-on performance
In a fashion marketplace pilot, shoppers who used virtual try-on added items to cart 52% more often and converted to purchase 35% more frequently than shoppers who didn't use it.
Source: Business of Fashion, "Generative AI Is Revolutionising Virtual Try-On"
Roughly half of U.S. online shoppers say they're interested in using virtual try-on while shopping — meaning adoption still has significant room to grow as accuracy improves.
Source: The Interline, "Virtual Try-On Hasn't Met The Bar For Consumer Adoption"
AI in fashion
41% of consumers say they trust generative AI search results more than traditional advertising, and 85% report being more satisfied with AI-assisted shopping than conventional online shopping methods.
Source: McKinsey & Business of Fashion, The State of Fashion 2026
Fashion executives now name artificial intelligence as their single biggest business opportunity for 2026, ranking it ahead of product differentiation and sustainability credentials.
Source: McKinsey & Business of Fashion, The State of Fashion 2026
Wardrobe waste
The equivalent of one garbage truck of textiles is landfilled or incinerated every second, and an estimated $500 billion in value is lost annually to clothing that's barely worn and rarely recycled.
Clothing production doubled between 2000 and 2015, while the average length of time a garment stayed in active use dropped 36% over the same period — and a separate global survey of 18,000 households across 20 countries found people consistently underestimate how much of their own wardrobe goes unworn.
Source: Ellen MacArthur Foundation, A New Textiles Economy; Movinga global wardrobe survey (via FashionUnited)
Why this matters for ViaStyl
Three of these numbers point at the same underlying problem: shoppers can't reliably tell how something will look or fit until it's too late, which drives returns, waste, and decision fatigue simultaneously. That's the specific gap virtual try-on and AI wardrobe cataloging are built to close — previewing fit before a purchase, and surfacing outfits from what's already owned instead of defaulting to new purchases.
See the technology behind these numbers
ViaStyl combines AI virtual try-on with wardrobe cataloging built around reducing exactly this kind of guesswork.
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