Returns will pass the trillion dollar mark this year, with US ecommerce returns growth outpacing sales growth, per our forecast. “It’s important for retailers and brands to look at their returns, because those ultimately eat into their margins,” said our analyst Sky Canaves.
“Consumers have started to become very conditioned to engage in certain types of returns behaviors because it’s convenient, it’s easy, [and] it can be free in many cases,” said Canaves.
Generous return policies, once a competitive advantage, have become targets for exploitative behaviors including:
Consumers promoting these behaviors or "hacks" for returning on social media have worsened ecommerce return issues.
It's not just a consumer behavior issue. Inaccurate product information, inconsistent sizing, and quality issues lead to more returns.
With 3 in 4 US households subscribed to Amazon Prime, per our forecast, free returns have become an expectation for many consumers. But shoppers realize that is changing.
“More consumers are accepting that certain retailers are going to charge for return shipping,” Canaves said. “The era of easy, free returns is not really feasible for a lot of brands and retailers.”
Consumers are often willing to pay for returns, especially if they view it as paying for a membership or loyalty program that offers returns as a benefit, rather than as a charge specifically for returns.
The best approach for retailers to avoid losses from returns is to keep consumers satisfied with their first purchase.
“Bracketing is a hassle,” Canaves said. “Consumers would rather not bracket if they didn’t have to because they’re not getting the accurate information about fit, sizing, and other features.”
AI tools can help prevent bracketing by creating detailed product descriptions, enhancing imagery, labeling frequently returned products, and summarizing reviews, Canaves said.
AI and augmented reality tools can visualize products like furniture in a consumer’s home; however, consumers have hesitated to use this technology for apparel.
AI tools using “passive data” like previous consumer purchases or existing customer data to assess size are more likely to be adopted, Canaves said.
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