eBay Is Developing Technology to Catch Bad Buyers - EcommerceBytes

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eBay told sellers it’s working to protect them from bad buyers, though it also downplayed the scale of the problem.
During the recent Seller Check-in event this month, eBay Senior Director, Head of Protections Ian Bednowitz said his team was developing technology to help crack down on eBay bad buyers using a “predictive approach.
But eBay needs sellers’ help, Bednowitz said, and he called on them to report bad buyers.
You can watch the full Seller Check-in video or jump to the part of Bednowitz’s presentation on bad buyers at about minute 21:14 in the video below.
“We don’t touch the item, so the only way that we know if there’s a bad buyer is if you tell us” – or if eBay identifies suspicious behavior when it looks at trends and data on claims.

eBay Is Developing Technology to Catch Bad Buyers - EcommerceBytes

eBay told sellers it’s working to protect them from bad buyers, though it also downplayed the scale of the problem. During the recent Seller Check-in event this month, eBay Senior Director, Head of Protections Ian Bednowitz said his team was developing technology to help crack down on eBay bad buyers using a “predictive approach.” eBay will also use third-party vendors to identify shoppers who are engaging in bad buying behavior on platforms outside of eBay. Bednowitz described three types of “bad buyer” behavior: 1) The buyer files a false SNAD claim (the buyer files a not-as-described claim when in fact it’s a remorse return). 2) The buyer returns a used or damaged item. 3) The buyer returns an empty box or a different item. He presented a slide that showed these three behaviors and some of eBay’s seller protections. But eBay needs sellers’ help, Bednowitz said, and he called on them to report bad buyers. “We don’t touch the item, so the only way that we know if there’s a bad buyer is if you tell us” – or if eBay identifies suspicious behavior when it looks at trends and data on claims. In another slide, he provided examples of such behavior: “Excessive eMBG claims or chargebacks, especially for newer buyers or buyers who have evidence of padding their feedback.” “When we get a report from you, that helps us prioritize looking at those buyers,” he said. The slide also described “Predictive Approaches” eBay is working on (“under development”): “Data science models, identity linkage to previously suspended accounts, third party vendors.” “It’s a very important area of investment for my team and for eBay,” he said. “We’re going to use data science to try and anticipate when a buyer might be abusive, might be a bad buyer, so that we can take actions in advance. “We’re looking to do more linkage to other accounts across that buyers may have so they can’t come back again if we’ve caught them before; and use third-party vendors who have information about their behavior on other platforms.” Bednowitz said if buyers return a different item or an empty box – which he characterized as “virtual shoplifting” – then eBay will completely suspend them from the platform. “We’re taking this seriously, and we’re investing in this,” he said. “We need your help to report these buyers.” But, he said, there’s black-and-white and there’s gray. “If we look at reports of all the buyers, there are a broad set of buyers that are reported by just one seller. But when we look at how many of these buyers are reported by more than one seller, it goes down to less than 10%. “So there’s a whole lot of buyers out there where they say something was a SNAD, and you may disagree as a seller. They may have opened an Item, done something that they don’t think is damaged and you do, but their intention isn’t always to be a bad buyer. But we need your data,” he said – if that 10% is really 20%, then getting those reports from more than one seller really helps. You can watch the full Seller Check-in video or jump to the part of Bednowitz’s presentation on bad buyers at about minute 21:14 in the video below. Readers might also find the presentation on returns to be interesting, it starts at about minute 16:46.
The Original Article can be found on EcommerceBytes

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