The Wall Street Journal ran an interesting piece (registration and subscription may be required) just before Christmas that detailed how some e-retailers are mining their own data to figure out how to influence the behavior of chronic returners – those consumers who buy, buy, buy with little intention of keeping the products they’ve ordered online.
In “Rampant returns plague e-retailers,” writer Shelly Banjo cites a Kurt Salmon stat that as much as a third of all Internet sales result in returns. And with firms like Zappos.com making returns free or less costly to consumers, shoppers have fewer and fewer reasons not to ship items back.
The fascinating part of the article, from an MR standpoint, is the intersection of big data, predictive analytics, behavioral economics and, potentially, research that it points to. As the e-tailers are mining their own sales data to develop strategies for combating returns, there’s an opportunity to use focus groups and other forms of qualitative to dig deeper into the thought processes of the chronic returners.
(The article mentions “wardrobers,” a subset of the frequent-returners who buy items to wear once and return, along with other shoppers who order clothes “just for the fun of trying them on at home,” without any intention of actually keeping them. Who ARE these people? Returning anything, no matter where you bought it, is a hassle. I can’t imagine willingly ordering something online that I know I won’t be keeping!)
Banjo cites the example of fashion discounter Rue La La, which is testing a program in which it reminds shoppers during the checkout process that the last five times they’ve ordered both small and medium sizes of an item, for example, they’ve only kept the medium. While some may say that the actual hard sales data is a more solid foundation upon which to base a strategy (the thinking being that it’s better to go by what consumers actually do than what they say they would do), conferring groups of these types of shoppers could uncover some of the emotional or other issues underlying the behavior and help determine what kinds of incentives to offer or actions to take to make returns less chronic. Home-shopping stalwart QVC, for example, found that after returns spiked for an at-home facial toning device, it began e-mailing purchasers an instructional video on how to use the gadget and saw return rates drop by 30 percent.
Again, I’m a believer in the research process, and perhaps clever corporate strategists don’t need to talk to consumers to get inside their heads and determine what’s driving their behavior when they can see the evidence of that behavior on their CRM dashboards. But I think relying solely on the numbers might only net them part of the story.