Until now, evaluating firms has been a question of forecasting future revenues off of past revenues. But with increasing access to new data, astute forecasters are deploying new methodologies. Among these is customer-based corporate valuation. And it’s a field that fascinates Goizueta Assistant Professor of Marketing Daniel McCarthy because it’s “equal parts marketing and equal parts Wall Street.”
A passion for finance and numbers led to a six-year hedge fund stint and a Statistics PhD from Wharton. But while pursuing his doctorate, McCarthy discovered an emerging discipline that integrates statistical-based predictive analysis and “looking at what customers do.” It became his passion and the focus of his research.
“If you’re generating revenue, it’s coming from your customers. Customer-based corporate valuation (CBCV) entails looking at data regarding the flow of customer acquisitions over time, how long they stay, the orders they place and how much they spend,” he says “We run this data through best-in-class predictive models for customer behavior to produce forecasts – of revenues, as well as marketing expenses and ultimately cash flows. Wall Street meets marketing.”
Of course, accessing data doesn’t come without challenges., including the question of privacy.
“The flavor of the month for predictive models right now is machine learning, where you throw in a bunch of data and algorithms spit out predictions based on historical patterns,” McCarthy notes. “That’s fine, but it requires a huge amount of data, some of which might not be available in the near future because it is sensitive.”
The CBCV methodology efficiently works with smaller volumes of data that are fully privacy-preserving, says McCarthy.
“We typically use data that comes from corporate filings and is highly compliant in terms of privacy regulation: we know how many customers a firm has acquired over a quarter, for example, but nothing about specific individuals. As long as we have the right aggregate data, we can predict nearly as well as if we had all of the granular data.”
McCarthy’s work on customer acquisition, retention, and corporate valuation has brought him to the forefront of a phenomena of the Covid-19 shock: the explosion in valuation of the U.S. restaurant food delivery sector “I wanted to understand what’s driving the spike for Uber Eats, Door Dash and others: new customers, existing customers coming back in greater numbers; and if so, why?”
He has a paper coming in spring 2021 that, he hopes, will shed empirical light on this “billion dollar question” for many organizations in this sector.
McCarthy’s research keeps him close to business. It also delivers insights of extremely high value to organizations. Has he been tempted to move into entrepreneurship himself?
“I have co-founded two firms using my models over the years. It’s heartening that so many diverse stakeholders find this area of diligence compelling. But if I’d wanted to be in industry, I would have stayed at the hedge fund.”
Academia and scholarship, he says, afford a unique opportunity and the intellectual and creative freedom to go deep into problems. “I love the fact that you can just take nine months and say: I am going to devote this time to look at this one little problem that many people would not find interesting, but that I find absolutely fascinating. I also really enjoy the teaching. I enjoy being able to learn these things and then feel like I’m able to give back to next generation leaders. At the end of the day, I feel very good about.”
Learn more about Daniel McCarthy and his research.
