To get more color on that subject, I rung up MasterCard Advisors' Gary Kearns, group executive for the company's information services business. He happened to be in Sydney, Australia on business, and indulged me before slipping away to Bondi Beach.
ZD: MasterCard. Big data. Connect the dots for ZDNet readers.
GK: If you look at the MasterCard business model, we've got 1.8 billion MasterCards out there, issued by 22,000 banks. It's accepted at about 34 million merchants. Every time someone uses a MasterCard, there is certain information captured in that transaction: an amount [of money], a merchant name, the date, the time, and the card number. We get that information so that you can process the transaction.
When that transaction comes through, we strip out the account number and anonymize it. I have three MasterCards, so I show up in our database as three anonymous cards. We don't have identifiable information, but we do have incredibly rich information about how people buy. It gets added to that database -- say, $42 at J.Crew at 8 p.m. on Thursday, February 7th --- and we aggregate that information, billions and billions of transactions. So to a retail store, restaurant, hotel, whatever -- we provide benchmarking: how's my business performing relative to some competitive set? J.Crew, relative to an apparel index?
We also do a lot of analytics. You look at big data...people are swimming in it, but they're thirsty. They've got social, demographic, SKU, location, transaction, credit bureau -- all these different data types. What's the recipe to make that decision? If I'm a bank and I want to increase Gary's credit line, what's the recipe to use to make that decision?
We never sell data [by itself] -- it's always enhanced. We make models to predict things. Who's likely to stop using their credit card? Who's likely to spend three times the average on apparel with me? Sometimes, we'll combine it with other data sources that we buy. To me, the deal with Mu Sigma is, how do we do that to scale, to merchants or governments around the world?
As I've been thinking about big data, [the question that customers have] is, how do we make it consumable?
ZD: What, exactly, is Mu Sigma bringing to the table? MasterCard has been doing this for quite awhile.
GK: One of the things about a transaction is that it's messy. At a point-of-sale machine, the name of the merchant is a free-text field. "Walmart" might be "WMT123." We've spent a lot of time over the last few years just developing the rules, algorithms, engines to clean this data and make it usable.
I joined this company two years ago when we started this information business. While MasterCard has done this over the last several years, the business is relatively new. [It exists] in order to help a variety of merchants globally be able to implement this stuff. To deliver that globally, you need scale. I can develop amazing analytics, but they're no good if I can't use them. Mu [Sigma] helps us scale that.
The biggest thing I hear from customers of all sizes is, "I don't know how to use it so that when I'm doing a campaign next week, what do I do differently?" You need that analytic ability.
It's really about acceleration, not about something I was missing. It's a $5 billion [big data] market going to $50 billion. I want to go after that market.
ZD: But doesn't MasterCard itself have scale? I'm still not clear on what Mu Sigma brings to the table in that regard.
GK: Ah. I've got a big team of scientists, the analytic team that works with various customers around the world. What I also find appealing and attractive is that Mu Sigma, if they're working with the merchant, they're going to be working on a broader array of analytic needs. The analytics we bring is around our transactional data. Mu might be working with SKU data, or social data, or demographic information. They're working end-to-end analytics, and I'm bringing transactional data.
The other piece is, they have figured out -- through Mu Sigma University, and how they build talent -- something very unique about how to scale the business. To be able to add 800 -- I'm just throwing a number out here; whatever it is, it's huge -- people a year, get them in quickly, trained and engaged? That McKinsey report predicted a shortage of analytic scientists in the next few years. That's important.
ZD: OK, so where does MasterCard go from here? Where are the next opportunities?
GK: There are 34 million merchants out there around the world that accept MasterCard. I think that I can help every one of them meet what they're trying to do: grow their business, acquire their customers, be more relevant to their existing customers. We're developing a variety of products for that.
For small merchants -- Joe's Pizza, Frank's Deli, a hair salon -- we have the Market Vision Report. We can help them to know how their campaigns are doing relative to their competition, a benchmark group. That kind of information, I think, is incredibly relevant and valuable.
For the large guys, they already know what their customers are doing. Let's take J.Crew. They know what their customers do when they shop in the store; they have that data. That's really interesting to them. What they don't know is, what do their customers do when they're not with them? Before and after they walk in the store? They would love to know that. They could have certain promotions that might cause you or me to do something more in their store.
Nobody else has that insight. It's privacy by design -- anonymous, aggregated -- but it's tremendously powerful.
ZD: Is growth for analytics simply leveraging MasterCard's existing network of customers? Or are there areas of the world where more adoption is to be had?
GK: There's a lot of opportunity to bring actionable insights that businesses, banks can use. There are also new businesses. Investors like the data because they like to monitor the macro information. Advertisers want to know how to better reach customers.
We're in 210 countries and territories -- we're busy in all regions of the world. MasterCard is doing a lot around mobile and financial inclusion; in South Africa, we just worked with a bank to develop a biometric, pre-paid card to fight fraud and leakage. That brings a lot of additional MasterCard holders to bear.
You can look at it as a continuum. In India, the amount of cash versus cards is still pretty high, but there's obviously good growth occurring. You look at Sweden, you basically can use your card for absolutely everything there. But per my South Africa example, they all understand that there are a lot of benefits to transitioning from a predominantly cash economy to cards, for safety and security.