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Innovation

eBay launches Interests, a curated product page built from shoppers' data

The Interests feature aims to show shoppers products that are individualized to their preferences.
Written by Natalie Gagliordi, Contributor
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eBay is turning to data and algorithms for a new customized shopping feature. It's called Interests, and it aims to show shoppers products that are individualized to their preferences.

The feature prompts shoppers to answer a series of questions to gauge their interests and then correlates their answers with trends in their browsing history. The system then spits out a homepage of curated products that the shopper would likely want to see.

Or as the company puts it, "eBay now adapts to give everyone their own unique store."

"Our shopping experience should be as individual as each shopper on eBay," said Bradford Shellhammer, head of browse and personalization for eBay. "By asking people to tell us a little bit about their interests, we're delivering a personalized store built around the things you care about most."

Interests is currently available on eBay's mobile app in the US for iOS and Android. The company plans to roll it out to mobile web and desktop over the coming months.

The Interests feature comes nearly a year after eBay -- which now has more than 171 million active buyers -- launched its first AI-powered site feature for sellers. Last July, the company introduced a new visual search feature that lets shoppers use a photograph to find products for sale on the site.

The technology behind the feature was developed in 2015 during the eBay's annual Hack Week event. Since then, eBay said it's had a designated team of engineers working to incorporate more AI-based services into the company's e-commerce experience.

More recently, eBay hired Jan Pedersen, former VP of data science at Twitter, to join the company as vice president and chief scientist for artificial intelligence. Pedersen leads eBay's AI efforts, including strategy, computer vision, natural language understanding, and machine learning.

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