Fashion retailers worldwide face persistent size and fit challenges, leading to customer frustration and high return rates. To tackle this, many brands and startups are deploying artificial intelligence (AI) both online and in physical stores. AI-driven tools like virtual try-ons, size recommendation engines, body scanning, and data-driven fit analysis are helping shoppers find the right fit more accurately, improving customer satisfaction and reducing costly returns.
Below are real-world examples of how companies are using AI to improve size and fit in both online and in-store retail contexts.
Zalando
European online fashion leader Zalando has invested heavily in AI for sizing. It uses advanced algorithms on user data and purchase history to recommend the best size for each individual, which has lowered return rates and increased customer satisfaction. In 2023, Zalando introduced a new feature that lets shoppers generate their body measurements using just two smartphone photos, creating a virtual avatar for a personalized fitting-room experience. This AI-driven approach helps shoppers find clothing that matches their body shape more closely, bridging the gap between online shopping and a realistic fitting room.
Amazon
Amazon’s retail CEO noted that “the biggest reason people return [clothing] is fit issues,” so Amazon developed an AI model that ingests all the brands’ size charts, customers’ purchase and return history, and feedback. The AI can now generate personalized fit recommendations – for example, advising a shopper to buy a certain size but warning “the sleeves are probably going to be short on you,” based on the customer’s body data and others’ feedback. By preempting fit issues in this way, Amazon’s AI personalization aims to reduce return rates (saving costs) and increase customer satisfaction. All these examples show how AI-driven personalization in 2020–2025 has directly contributed to higher conversion rates, larger basket sizes, and fewer returns, thereby boosting retailers’ top-line revenues and customer loyalty.
Walmart
Walmart acquired startup Zeekit to power an AI virtual fitting room. The technology uses real-time image processing, computer vision and deep learning to simulate how clothes would look on a shopper’s body, accounting for the person’s body dimensions, size and even fabric drape. On Walmart’s website and app, customers can choose a model that matches their body type or even use their own photo, allowing them to “see” the fit before buying. This boosts confidence in sizing and is aimed at reducing returns due to poor fit.
Nike
Nike uses an AI-powered augmented reality foot scanner in its mobile app to solve shoe sizing issues. The Nike Fit feature lets users scan their feet with a smartphone camera; the app then captures 13 data points to create a 3D model of the foot and recommends the ideal shoe size. By providing exact size suggestions, Nike’s AI tool helps customers get a better fit in footwear, minimizing return rates and increasing customer satisfaction. This technology tackles the long-standing issue of customers wearing the wrong shoe size and reduces the guesswork in online shoe shopping.
