Many companies are also experimenting with automated solutions. Robots can be deployed in sorting centres to reduce labour costs by up to 30 % and accelerate processing times by 50-60 %, while AI analytics identify fraudulent returns patterns and suggest operational improvements. Automated refurbishing facilities also disassemble products up to three times faster than human workers, reducing waste and solidifying sustainability credentials.
Transportation and handling of returned goods contribute substantially to retailers’ carbon footprints, especially when returns are excessive or fraudulent. Incorporating circular economy models
– the designing of products for easier reuse, repair and recycling – helps reduce environmental impact while generating cost savings.
Clear, visible and consistent return policies play a pivotal role in reducing return volumes and improving customer satisfaction. Retailers aim to balance consumer convenience with cost containment by offering incentives like store credit or exchanges, tightening return windows or introducing return fees for non-defective goods.
Jonathan notes:“ Our insights show that a data-driven, customised approach is key to reducing fraud while delighting genuine customers.”
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