Coffee on the third floor with Prof. Sanjog Misra

Sanjog Misra, Professor of Marketing and Neubauer Family Faculty Fellow

Sanjog Misra, Professor of Marketing and Neubauer Family Faculty Fellow

Sanjog Misra, the Charles H. Kellstadt Professor of Marketing and Neubauer Family Faculty Fellow believes there’s a marketing evolution underway. A clairvoyant to this marketing evolution, Misra has long established himself in the field of quantitative marketing both through his research and his numerous consulting projects. Outside of academia, Misra has most notably worked as an advisor to Convertro, a multi-touch attribution service. Convertro was sold to AOL, now Verizon, where Misra continues his role as an advisor.

On his initial interest in data-driven marketing: “I started off as a theorist but realized that theory by itself is incomplete. I started looking into ways of testing theory, and that’s what got me into looking at data. Initially it was looking purely at research topics and trying to find data to corroborate theoretical results. At some point, I realized that it’s not enough to simply test theory. Since I’m in a business school, it’s more challenging and more interesting to try and see whether the methods we develop can actually make a difference in how firms operate and whether it can create value for consumers, firms, and non-profits.”

While most of us are somewhat familiar with the role of data science as it’s applied to online, large scale, real time marketing decision making where humans cannot be involved, Misra’s sees this as just as the beginning: “there’s going to be a shift in marketing, and it’s already taken off. One is that we’re going to see humans being replaced by machines and algorithms in what I’ll call ‘menial’ marketing jobs. Anything that can be automated will be automated. Humans will be Level 2—managing algorithms or managing people who manage algorithms.” How can Bausch & Laumb redesign its compensation scheme to precisely align with the incentives that motivate its sales force? If MGM sends you a promotion and you end up staying at the Bellagio, how can they better distinguish those who were incentivized to stay because of the promotion from those who received the promotion because they were more likely to stay there for other reasons? While questions around incorporating human motivation into firm decision making has traditionally lied in the realm of psychology—and in some cases, intuition—Misra has tackled these questions through his quantitative marketing approach.

On the role of analytics in the online world: “Imagine that you have a website and you have 10 different ads created but you don’t know which one is the best one. The old, old approach would be to get an expert—an ad agency—that would create these for you, pick the best one for you, then you would run that. The next approach is to test ads with a randomized control trial, figure out the best one, then implement it. The next approach is to say that ‘we’re losing money. If we test 10 of them for a certain amount of time, we’ll find that 9 of them were not the best. So we just showed a whole bunch of our customers ads that ex-post we know are not really good.’ How do we do this in an efficient way? This is where k-bandits come in. You start with all 10 ads, then as you learn that one is better than the other, you slowly move money or exposure to the few that are performing better—not completely, because you might be wrong. You’re learning about the effectiveness of each and redirecting traffic as you learn. Very soon, you converge to the ones that work.  The holy grail is to be able to do this for each unique individual at scale—the ad, the product, or the price that works for each individual.” The speed at which companies are able to do this is what Misra sees as the axis where companies will compete to exploit revenue.

Misra’s Digital and Algorithmic data course—being offered this Spring—gives students the opportunity to tinker with these issues: “the idea of algorithmic marketing is that every time you have to make repeated decisions at scale, you need an algorithm. We go behind the scenes of how these algorithms work.” Inspired by his research and consulting work, the course explores real-life product recommendation and matching algorithms, while also giving students the opportunity to try and improve the algorithms of start-ups Misra has partnered with. And for any OkCupid users out there, the course will give you a peek at how the website has (or hasn’t!) been able to help you find “the one.”

The beauty of Misra’s research interests is how easily they have lent themselves to bridging the gap between academic research and the pressing challenges of firms and non-profits. Don’t worry, though, Misra has no intention of leaving us. Citing the flexibility in exploring research topics and designing his own courses, Misra describes academia as “the best job in the world.” For those of us who will be leaving Booth soon, Misra advises us to prepare ourselves for management roles that will involve more management of data and more management by data. Whether it’s in the improvement of algorithms, finding ways to use data more cleverly, or the service component of making data-driven insights more digestible, Misra sees the algorithmic revolution as just beginning: “My class is not about marketing. It’s about the direction business is taking. If you’re in operations or finance or consulting or entrepreneurship, you don’t really have a choice. The role of the MBAs isn’t going to change. You’re still going to be managers. But the question is going to be what you’re managing.”

Araba Nti, Class of 2017

Araba Nti, Class of 2017

Araba is a second-year student who enjoys her coffees on the third floor