The Customer Confidential Podcast

Now There’s a Way to Link Customer Behavior to Share Price

Dan McCarthy of Emory University’s Goizueta Business School and cofounder of Theta Equity Partners explains how “customer-based corporate valuation” makes customer behavior a critical element of financial valuation.


Now There’s a Way to Link Customer Behavior to Share Price

If the purpose of business is to create a customer, as Peter Drucker famously observed, why do CEOs so often feel forced to make choices that produce quick profits and short-term boosts in share price, but damage the customer experience in the long run? And if it is shareholders that push them into those decisions, why would shareholders pressure executives to damage the value of the company?

Although earning customer loyalty is firmly in the interest of both shareholders and management, today’s financial reporting practices actually obscure the value of customers. If you’re a CEO, you likely see the value of improving customer experience, but how do you prove to shareholders that that will be reflected in share price? And if you’re a shareholder, how do you gauge whether a company’s investments in customer experience and products are the right ones?

That’s a question my latest guest thinks about a lot. Dan McCarthy is an assistant professor of marketing at Emory University’s Goizueta Business School and a cofounder of Theta Equity Partners, a firm that’s doing pioneering work in what it calls customer-based corporate valuation (CBCV)—an approach aimed at helping executives and investors better understand and measure the value of a firm by looking at the strength of its customer base.

Dan and his colleague Pete Fader wrote an article that appeared in the January/February 2020 issue of the Harvard Business Review called, “How to Value a Company by Analyzing Its Customers.” Dan’s and Pete's article appeared alongside my own as part of a spotlight section called, “The Loyalty Economy.” As you might guess from listening to us, Dan and I actually speak frequently, because even though we come at the issue of customer loyalty from very different angles, our approaches are fully in sync and complementary. I spend my time working with executives who are trying to help their company reach its full potential value by earning customer loyalty, while Dan spends his time trying to figure out what that loyalty is worth to shareholders, and how to measure it.

Today's episode is the first part of our conversation about the art and science of customer-based corporate valuation. Also, if you’re curious about how the math works, you can check out a simplified version of the model here and also see how it was applied to Lyft prior to the ride-hailing company’s initial public offering.

You can listen to my conversation with Dan on Apple PodcastsSpotifyStitcher or your podcast provider of choice, or through the audio player below.

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In the following excerpt, Dan explains one way his firm takes traditional analysis methods and adapts them into a model to generate data that more truly reveals what’s going on inside a corporation.

Rob Markey: Let's talk about what would you need in order to do customer-based corporate valuation that would be different than, or in addition to, what you would have in a traditional [financial analysis].

Dan McCarthy: So imagine that you're looking at a discounted cash flow valuation spreadsheet. The only two things that are going to change are we're going to replace the row corresponding to revenues, and then the row corresponding to say, advertising expense, or, you know, customer acquisition expenses.

You pull it over to this other tab on the spreadsheet and that tab houses the customer model. And the customer model will govern: This is my forecast for what future acquisitions will be. And that's going to be a function of, say, the historical rate of customer acquisition, some estimate of how big the total available market market (TAM) is, and our belief about the company's ability to have long-term penetration into that TAM. And maybe, you know the extent to which the company will expand its TAM in the future.

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Rob Markey: That's not that different from what you would do with traditional cash flow projections. What you're doing is cash flow projections at a more granular level, meaning at the customer level or, or maybe better said, at the cohort level, like a [year’s] worth of new customers. Is that fair?

Dan McCarthy: Yeah, that's right. Instead of, typically when I've heard of a total applicable market, when people talk about that, oftentimes it's five years from now there's going to be two billion of sales in this category, and we expect them to have 50% of that.

Rob Markey: So, very top-down.

Dan McCarthy: Yeah, yeah, it's plausible. It gets you right to sales, sure. But let's see how you're going to get there. You need to be able to acquire an adequate number of customers, retain them, and get them to spend. So basically, you know, not to rush ahead, but we're going to bring all these processes together. And we're going to end up with that same sort of implied view. But the way that we're going to get there is to impose this actual level of discipline on the model. It's going to say, “Yeah, so this is what the retention has been in the past. So, are you saying that it's going to get from here to here?” And just forcing people to be more explicit about each of those assumptions.

Rob Markey: Well, it's marrying a bottom-up analysis with the traditional top-down. Meaning you take this: What's the total market? What's the share of the market? What are they going to be spending on marketing year over year as a percent of sales? That's the top-down...the bottom-up says, “Well, okay, so how many customers are they going to be acquiring and how many of the existing customers they already had are they going to keep? And what's the implication there? And how much is it going to cost per customer to acquire people? And are the future cohorts of customers going to perform better or worse than the ones that they already have?”

Dan McCarthy: That's right. And actually I liked the way that you put it, that it's a marriage. Because I’ll be the first to say in some of our previous work, we kind of described it a bit more as a dichotomy. You know, that we're doing it from the bottom-up and this is a different, but potentially complementary way to top-down. When in fact, for one, there are very top-down elements to what we're doing. And for two, there's nothing that would hold us back from say, incorporating things like GDP growth. That those are very much things that can be built into the model. We could just posit that, the economy will make people more prone to making purchases, more prone to be inquired, et cetera, et cetera. So I think the real comparison is, do we want it to be purely top-down, or do we want it to be both top-down and bottom-up at once?

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