AI Tailors a New Fit for Fashion's $850 Billion Returns Problem

A shirt that bunches at the shoulders. A dress that hangs just a bit wrong. This detailed fit feedback, once only possible in a dressing room, is now coming from artificial intelligence. Retailers, grappling with a returns crisis that saw nearly $850 billion in goods sent back last year, are deploying a new generation of AI to let shoppers visualize clothing fit before they buy.

The goal is straightforward: curb the staggering volume of returns, which for online orders approaches 20% of sales. Most returned items are a direct hit to profits, often costing more to process than the item's original value. 'Finding ways to minimize returns can be a significant driver of profitability,' notes Guggenheim analyst Simeon Siegel.

Startups like Catches are at the forefront, using generative AI and physics simulation to create 'digital twins' for virtual try-ons with what CEO Ed Voyce terms 'mirror-like realism.' The technology, now live on sites like luxury brand Amiri's, considers how fabric moves with a body, aiming to bridge the gap between online browsing and in-person fitting. 'The confluence of technologies now makes this solvable,' Voyce says, pointing to the ability to run high-fidelity visuals in the cloud at a cost that delivers a return for brands.

Retailers are pairing this tech with policy shifts. Zara's introduction of online return fees helped protect margins, while ASOS credited a 160-basis-point drop in its returns rate with boosting profitability. Tech giants, including Google and Shopify, are also embedding try-on tools directly into shopping journeys.

The potential payoff is substantial. Catches projects its tool can increase conversion by 10% and deliver a 20-30x ROI for partners. Yet analysts urge perspective. AI is a tool, not a cure-all. 'What you sell will always be more important than how you sell,' Siegel concludes. 'Remembering that dictates who truly benefits from AI.'

Source: CNBC