MasterCard Just Took A Stake In A Hot Big Data Startup
MasterCard knows what everyone buys. Some 1.8 billion people use its cards at 34 million stores worldwide.
Retailers can sift through their own records to understand what their customers buy. But they can't as easily figure out the shopping habits of people who buy from other stores.
That's the kind of information that MasterCard hopes to sell to them as it moves into the $5 billion big data analytics market.
Last week, the company's subsidiary, MasterCard Advisors, took an undisclosed stake in a big data analytics company called Mu Sigma.
The two will offer joint products together using MasterCard's databases and Mu Sigma's analytics technology.
Mu Sigma is a Chicago- and India-based company that raised a whopping $133 million since it was founded in 2008. That includes a $108 million in 2011 lead by General Atlantic. Its customers include Walmart and Microsoft.
We asked Gary Kearns, the MasterCard executive vice president spearheading this project to explain MasterCard's plans:
BI: What kind of data will Mastercard will be selling?
Kearns : We aggregate information across the 34 million merchants who accept MasterCard, and create analytics, reports and insights off this rich data. We do not sell the actual transaction data - we sell products like benchmarking reports (how is my business performing compared to other merchants?), and analytics (how can I better understand what my customers might want to purchase?).
We would also sell this retailer weekly information about its sector – for example, women’s apparel sales each week – so that they could better benchmark their performance.
BI: Can a company use this to find out details about a competitior?
Kearns : We never sell a company information about a specific competitor – it is always a larger, anonymous group.
BI: What kinds of interesting things can a company learn from your reports?
Kearns : A large retailer was able to understand, at an aggregated and anonymous level, what its customers do before and after they shop there. This large retailer would then be able to offer its customers certain incentives to come there and spend more on the items that they may have purchased before and after visiting them.
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