With about 500 million registered users, 60 million daily visitors, and 48 thousand items sold per minute, Alibaba’s Taobao, who just celebrated its tenth birthday, must have the largest online shopping database in China. If every user purchased one more item when visiting Taobao because of the recommendations generated by data-powered algorithms, the sales number would be huge.

At the 2013 Innovation Summit on Big Data today, Yang Tao, a data scientist at Alibaba, said their approaches did help Taobao retailers sell more items and users find more they’d like to purchase.

One patented approach is a recommender built on top of data sets of user groups. It divides Taobao users into thousands of groups based on user profile information and what they have bought; for instance, middle-aged rich ladies who are living in third-tier cities. In each group there are several users who are expert at certain category of goods or good at exploring less-known Taobao stores. Algorithms based on the above-mentioned settings would help surface goods to group members based on the purchase history of the expert users.

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Tracey Xiang

Tracey Xiang is Beijing, China-based tech writer. Reach her at traceyxiang@gmail.com