India’s rapidly expanding fashion e-commerce sector is deploying predictive intelligence systems to tackle one of retail’s costliest challenges: product returns that can drain up to 40 percent of each item’s value. As the market accelerates toward $98.45 billion by 2032 from its current $21.6 billion valuation, major retailers are turning to machine learning and behavioral analytics to curb the financial and environmental toll of reverse logistics.
The technology shift comes as returns plague online fashion retailers worldwide, with India’s apparel sector experiencing return rates between 25 and 40 percent—significantly higher than the 9 percent seen in physical stores. Each return costs retailers between 25 and 40 percent of the product price when factoring in shipping, restocking, and lost resale value.
Major Retailers Deploy AI-Powered Size Recommendations
Myntra, India’s leading fashion marketplace, reported in November that half of its revenue now flows through AI-driven size and fit recommendations, according to CEO Nandita Sinha. The platform has invested heavily in predictive systems that assign return-risk scores at checkout and provide real-time interventions such as peer-driven sizing insights like “70% of customers suggest sizing up”.
“These features help reduce returns but also cognitive overload, helping customers decide quickly,” Sinha explained at a recent industry event, noting the company’s shift toward becoming an “AI-first organization”. Together with Flipkart, Myntra captured 89 percent of India’s fashion e-commerce order volumes in 2025.
The predictive systems use machine learning to identify habitual bracketing behavior—when consumers order multiple sizes with the intent of returning most items—and flag products with disproportionate return rates caused by inaccurate descriptions or inconsistent sizing. Retailers implementing AI-driven size guidance have seen return rates drop by up to 24 percent, according to a 2023 True Fit study.
Environmental and Financial Stakes
The returns crisis extends beyond profit margins to environmental impact. E-commerce returns generate up to 24 million metric tons of CO2 emissions annually worldwide, with fashion accounting for a substantial portion. In India, where online shoppers often rely on peer reviews and community feedback, integrating predictive intelligence can significantly influence purchasing decisions.
Personalization technology underpinning these AI systems can reduce customer acquisition costs by as much as 50 percent while lifting revenues by 5 to 15 percent, according to McKinsey research. This dual benefit of reducing returns while improving customer engagement has made predictive intelligence systems increasingly attractive to retailers operating in India’s competitive market, where the fashion e-commerce sector is projected to grow at a compound annual rate of 24.2 percent through 2032.
Global fashion brands including Zara and Uniqlo have introduced return fees ranging from $2 to $7 in various markets, while ASOS suspended accounts of serial returners. These reactive measures, however, risk eroding customer loyalty—a concern pushing Indian retailers toward proactive AI solutions that address the root causes of returns while maintaining customer satisfaction.