As Chinese e-commerce firm Alibaba prepares for what could be the biggest IPO in history, University of Michigan professor Puneet Manchanda dug into its Taobao website data to help solve a lingering chicken-and-egg question.
Taobao.com is the world's largest customer-to-customer shopping site with nearly 500 million users and more transaction value than Amazon and eBay combined. The company gave Manchanda, a marketing professor at Michigan's Ross School of Business, access to its data to discern whether buyers or sellers were driving transactions.
It was long assumed buyers were the primary drivers of traffic, but Manchanda's research showed that sellers get the ball rolling. His research with Junhong Chu of NUS Business School in Singapore has implications for how companies like Taobao and others set policies for buyers and sellers.
"There's very little information on these platform markets and it's not clear that companies know which side is more important when they're doing the matchmaking," Manchanda said. "It's difficult to get information right from the site's beginning to study this cross-network effect on how buyers affect sellers and vice versa, but Taobao gave us the data because they wanted to know."
The prevailing wisdom that buyers were more important for driving traffic comes from the belief that it's buyers who have the money to spend. But the research showed those buyers won't come if a website doesn't have enough to sell.
Their analysis revealed that the cross-network effect of a seller—the probability that it induces a buyer to join—is 3.5 times that of a buyer inducing a seller. Taobao tweaked some policies to become more "seller friendly" after it saw the results.
His analysis also revealed that product variety is critically important for buyers. That can help companies induce more buyers by fast-tracking sellers who bring something new to the table, he said. Based on these results, Taobao started running programs to encourage dormant buyers to "wake up" and start buying again.
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Chu, Junhong and Manchanda, Puneet, "Quantifying Cross-Network Effects in Online C2C Platforms" (September 2014). Available at SSRN: ssrn.com/abstract=2494948