No matter how simple a metric’s name makes it sound, the details are often downright devilish. What is a website visit? What is revenue? What is a customer? Go one level deeper with a metric like customer acquisition cost (CAC) or customer lifetime value (CLV or LTV, depending on how you acronym), and things can get messy in a hurry. In some cases, there are multiple “right” definitions, depending on how the metric is being used. In some cases, there are incentive structures to thumb the definitional scale one way or another. In some cases, a hastily made choice becomes a well-established, yet misguided, norm. In some cases, public companies simply throw their hands up and stop reporting a key metric! Dan McCarthy, Associate Professor of Marketing at the Robert H. Smith School of Business at the University of Maryland, spends a lot of time and thought culling through public filings and disclosures therein trying to make sense of metric definitions, so he was a great guest to have to dig into the topic!

Links to Items Mentioned in the Show

• CLV Ultra by Theta


• (Book) The Chairman’s Lounge: The Inside Story of How Qantas Sold Us Out by Joe Aston


• (Article) Why You Should Get Lost More Often by David Epstein


• (Book) The Explorer’s Gene: Why We Seek Big Challenges, New Flavors by Alex Hutchinson


• (Podcast) Fritterin’ Away Genius 


• Zodiac (acquired by Nike)


• Charlie Javice


• (Slides) Dan’s CAC lecture


• Blue Apron’s IPO Filing Implies Troubling Customer Retention


• Theta


• (Soundcloud) Customer Lifetime Value – The LP

Photo by patricia serna on Unsplash

Episode Transcript

0:00:06 .0 Announcer: Welcome to The Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language.

0:00:15 .4 Michael Helbling: Hi everybody, welcome. It’s the Analytics Power Hour. This is Episode 272. It was pretty early on in my career when I learned that the way we tracked revenue and marketing differed from from other departments. In fact, there were three different acceptable definitions depending on who you were talking to. In data and analytics, we don’t really talk about that too often, but it really starts to matter as those metrics become more complex and are imbued with meaning intended or not. And today we’re diving into a world where sometimes the numbers don’t feel like they add up. They go on these complex journeys involving weighted averages and obscure formulas and maybe a little sprinkle of dark magic. Because sometimes the most important numbers in your business are the ones that nobody actually understands, maybe including the people who created them. Okay, so we’re gonna talk about it. And of course I’m joined by my co host today, Moe Kiss, director of data science at Canva.

0:01:17 .9 Moe Kiss: Hi there. How are you doing?

0:01:19 .7 Michael Helbling: Hey. Good. Sorry, I usually ask you how you’re doing and I kind of left it, so that’s fine.

0:01:25 .8 Tim Wilson: Gotta keep you on your toes.

0:01:26 .9 Michael Helbling: And of course speaking of things that no one understands, Tim… No, I’m just kidding Tim. My other co host, Tim Wilson, co founder and head of solutions at facts & feelings. Hey Tim.

0:01:40 .3 Tim Wilson: How you going?

0:01:41 .2 Michael Helbling: Thank you. I’m going quite well. And I’m Michael Helbling, I own and run Stacked Analytics. So we wanted to bring in a guest who could help us navigate this discussion. I think we found the perfect one. Professor Dan McCarthy is a leading expert at the intersection of marketing, statistics and finance. He serves as an associate professor of marketing at the University of Maryland’s Robert H. Smith School of Business, where he’s recognized for pioneering the field of customer based corporate valuation. His research has been published in numerous journals, as well as in publications like the Wall Street Journal, Harvard Business Review, and the Financial Times. Outside of academia, he co-founded Zodiac, a predictive analytics firm acquired by Nike in 2018, and and later co-founded Theta, a company specializing in customer based valuation models. He holds a PhD in Statistics from the Wharton School of the University of Pennsylvania. And today he is our guest. Welcome to the show, Professor McCarthy.

0:02:35 .8 Dan McCarthy: Yep. Thanks so much for having me.

0:02:38 .0 Michael Helbling: Do people call you Professor McCarthy or Dan or what do you go by?

0:02:42 .7 Dan McCarthy: They usually do. And I usually promptly say, “Just call me Dan.”

0:02:45 .9 Michael Helbling: Oh, okay, well, I’ll call you Dan then. That’s perfect.

0:02:49 .9 Tim Wilson: Do you call. Do you call Dr. Peter Fader just Pete? Is he… Like, is that…

0:02:54 .7 Dan McCarthy: That’s what I do, yeah.

0:02:56 .1 Tim Wilson: Okay.

0:02:56 .7 Dan McCarthy: There’s a lot of Professor Faders, too. Yeah.

0:03:00 .6 Michael Helbling: Well. And yeah, and we had the fortune to have Dr. Fader on our show a few years back as well, which was awesome. All right. So I think diving into a conversation like this one of the things that we recently went. Went through was some material I think you presented probably to one of your classes, perhaps about constructing customer acquisition costs or CAC. And that was sort of a conversation we sort of had a little bit about, okay, yeah look at this and see how he’s breaking it down. But you spend a lot of time kind of like pulling metrics apart that are kind of big for companies. Like, first off, maybe what got you headed that direction in terms of research and work and then maybe share anything you want to share about sort of like that direction.

0:03:49 .0 Dan McCarthy: Yeah. I’ll be frank. I think a lot of that really stemmed from Zodiac and Theta. I think that in academia, there’s not much appreciation for getting the number exactly right. The bookkeeping exercise is not… It’s not that sexy. It’s not that exciting, but it’s incredibly important. I mean, if you’re a firm, it really pays to know, is my CAC $40 or is it $100? And depending on what you choose to include or exclude, you really can see these really big swings in the numbers. And because it’s such an important metric, there’s a lot of companies, public and private, that will basically do whatever they can to make the numbers look as good as possible. So for CAC, it would be to make the numbers look as small as possible. And so part of it is really to understand when you start tearing apart pre-IPO prospectuses, what are you going to see and what is real and what is bullshit. Pardon my French.

0:04:57 .4 Tim Wilson: Totally allowed.

0:04:58 .0 Dan McCarthy: You know, it’s just… Yeah, it’s amazing how certain companies will try to kind of dip their hand into the candy jar and just go a little too far. There’s… I think, the realm of reasonableness where they’re doing things. Maybe I wouldn’t fully agree with