Returns are often seen as an inevitable cost of doing business in ecommerce. But leading brands are proving that doesn’t have to be the case. With the right AI tools, it’s possible to dramatically reduce returns—without hurting customer experience.
Personalized Sizing EnginesSizing is one of the most common reasons for returns, especially in fashion and footwear. AI uses historical data, reviews, body shape indicators, and material feedback to recommend the best size for each individual shopper.
One Nordic apparel brand implementing this strategy cut size-related returns by 28%, simply by showing “recommended fit” badges on their product pages.
Smart Pre-Purchase Nudging. By analyzing return-prone behavior, like adding three sizes to cart or purchasing multiple variations of one item, AI can trigger contextual nudges. These might be educational popups, fit guides, or alerts about common reasons for returns.
These nudges reduce buyer confusion and manage expectations upfront, leading to more confident purchases and fewer returns.
Dynamic Return Conditions. Not all customers should get the same return policy. AI can help you segment users and tailor conditions based on risk profiles. For example, serial returners might only get store credit, while loyal shoppers receive free return perks.
This builds fairness into your policy and nudges high-risk behavior in a better direction, without punishing loyal customers.
Data-Driven LoyaltyOn top of return risk prevention, AI can identify and reward customers who consistently keep their purchases. These signals help refine loyalty campaigns and VIP treatment that builds lasting value.
Why It Works
These strategies build trust with customers while aligning incentives. Return rates drop, customer satisfaction stays high, and margins improve, fast.