Mastercard Names Raj Seshadri President Of Data And Services

Retail in recent years has become a very data-intensive industry. In his keynote address to the National Retail Federation (NRF) earlier this week, Microsoft CEO Satya Nadella said the industry as a whole throws off 40 terabytes of data an hour.

That’s both a tremendous opportunity — in terms of providing stronger security, better customer experiences, more customized commerce journeys and, on the whole, better outcomes for both merchants and customers. It’s also a tremendous challenge, however, as data on its own isn’t useful. Data successfully parsed and translated into action items is — but successfully using data is quite a bit more complicated than merely amassing a lot of it.

And, as the world has been thinking about data and its relevance to the rapidly resetting commerce ecosystem, Mastercard announced that Raj Seshadri would be the person officially taking on both these challenges and possibilities on the card network’s behalf as the new president of data and services. Seshadri will report directly to President and CEO Ajay Banga; she replaces Kevin Stanton, who has taken on a new role as chief transformation officer.

“Given where we are today, where things are fundamentally different in ways one couldn’t have imagined as recently as 10 years ago, it is a very exciting time to be working in this area and I am thrilled to be taking on this new role,” Seshadri told Karen Webster in an interview.

She noted that she doesn’t quite have a full playbook written just yet, as it was only one-half day in the job when she and Webster spoke, but the relationship between data and the future of retail is coming into focus. She noted that the data story is increasingly about corralling it correctly and then applying the right technical tools to drive actionable insights.

Asking The Right Questions

At the beginning of the 21st century, it didn’t make much sense to talk about retail channels — because there was only one channel through which it was all compressed — the physical store. Two decades in, it still doesn’t make sense to talk about retail channels, but for a very different reason, Seshadri said. There are a lot of channels these days, and with the rise of the IoT and voice-connected commerce, more are appearing each day. However, consumers themselves don’t segment their commerce journeys by channels; they enter them with growing expectations that they are going to be able to move seamlessly between digital and physical experiences.

Providing for those expectations requires data, but given the almost overwhelming flow of it coming out of retail, it also requires a correct mindset in working with it.

“You can be swimming in data and if you don’t know what you are trying to do … it won’t help you,” she said. “Data is a facilitator, but only if you are asking the right questions. You are coming up with the right answers that push you in a more future-forward direction.”

Ask the right questions and get the right actionable answers is simple to say, not so simple to do, particularly in a highly dynamic environment like commerce. The rewards, she said, are clear. When you can examine the data in a way that does separate the signal from the noise and that is when it becomes possible to knock down friction points, make commerce experiences on both sides of the transaction and ultimately engage more spending. Data correctly leveraged provides the insights that make it possible to provide those more tailored experiences.

But even then, Seshadri told Webster, that possibility only becomes actuality when those data insights are wedded to the right tools.

Tapping The Right Tool Box

Knowing what to do is only half of any battle, Seshadri noted, because there is the altogether different challenge of actually executing it. Again, the coin has two sides when it comes to this. The good news is how far the innovation has come in terms of what we can model and what kinds of tools and techniques that can be thrown at the future of retail reinvention.

“With [artificial intelligence] AI and machine learning, things are possible now that just weren’t a decade ago,” she said. “We can now rethink and reevaluate things with math that we’ve never been able to.”

Bring those advanced tools to the ever-growing-larger data sets retail is creating, she said, and they will unearth patterns and areas for expansion that no one would have ever known to act upon, because they would not have been identifiable.

Now, she noted, they aren’t only visible, but actionable: powered by data and parsed by increasingly advanced technology.