Customer Valuation: An Interview with Peter Fader, Professor of Marketing, the Wharton School of the University of Pennsylvania

PF: A couple of things. One is the times. So, this is early 1980s, and we're just starting to invent the kind of tracking capabilities that we have today. I mean, her pitch to me was, "We are building the electron microscope of the customer. We are gonna have the capability to tag, and track, and predict, and manage in a way that we could never imagine." She was hundred percent right. So, part of it was just gonna be a fertile area with lots of nails to hammer. So, part of it was just that, part of it was my own background as a math major. I wasn't sure what I was gonna do, but I was spending a lot of time thinking about being an actuary. So, just looking at kind of the risks, and the probabilities, and all that sort of thing about how...

SS: Maybe the polar opposite of marketing, I might add.

PF: Well, no, but her point... You're right. But her point was we can use the same actuarial models instead of saying, "How long is it gonna take until you die? It's gonna be how long it's gonna take until you buy?" And the same basic patterns are gonna apply again. A hundred percent right. So, yeah. This fairy godmother of mine, her name is Leigh McAlister. She's now professor at University of Texas. She just had just incredible foresight about what marketing would become, what kinds of skills would help you bubble up to the top and the kind of people who should be able to transform the field and to make it to something different than the usual stereotypes. And I'm not sure how transformative I've been, but I've been happy to go along for the ride.

SS: It's remarkable because it was the '80s, even database marketing was just sort of fresh out of the crib at that point. So, yeah. She was quite prescient in envisioning a future of data-driven marketing, if you will.

PF: Absolutely. And that was a big part of it, a metaphor that stayed with me, that she looked at some of the things that were going on, database marketing, direct marketing, late-night infomercials, and saying those kinds of practices should be more rule than exception. They really would apply to more businesses. Even businesses that look at those kinds of sectors and go, "We don't want anything to do with that." But they could still benefit from it. And today, so many companies are doing that kind of performance marketing without recognizing the debt that they owe to those old-school direct marketers. They think they've invented something new.

SS: And you're quite right. My dad, as an example, worked for 35 years at "Reader's Digest." And a lot of those practices, consider those were the days of mainframe computing, not what we have today. They were doing predictive modeling way back then.

PF: And in many ways better than what a lot of companies are doing today. Because, actually, back then, they're actually much more scientific about it. The data was so hard to come by, it would take so long before you'd get the next report. And so you weren't drowning in data, that whole metaphor just didn't exist back then. And so if you're gonna wait two months to get the next, you know, whatever, Nielsen Reports in, what are you gonna do in between? And the answer is, they would think. They would think about, "So what do these numbers mean? What kind of hypotheses do we have for them? What kind of experiment could we run to test that hypothesis?" It was just much more thoughtful because of the absence of data. And so, a lot of the frameworks and approaches that they came up with are just as good today. But today, we're just not at best, we're either just replicating that old stuff or doing dumb things. And we're not as scientific about it. We talk about data science. There's not a lot of science in data science.

SS: Well, we also tend to get distracted as marketers, right? So, the latest, greatest thing, and we haven't learned the basics yet, which is really what you've been doing, is helping this idea of foundational analysis. And just by the by, my career was spent in direct marketing, CRM database marketing. So, I'm obviously conversant with a lot of the attention you pay to customer value, customer value stratification, customer valuation, etc. We use it with our clients, we call it a customer portfolio analysis. You've got this idea - we're gonna come back to this about a customer audit - which I love. And the book, by the way, is much needed. We'll come back to that. I do wanna dwell a little bit on the book, "Customer Centricity," which won you a lot of fame. You wrote it in 2011, which is a long time ago now. What's remarkable to me is it sold 100,000 or nearly 100,000 copies, I think you said. You know, it's this wonderfully written 20,000-some-odd-word treatise on customer value. This idea of focusing on high-value customers, on customer lifetime value. And as we've just been talking about, those principles have been around for a long time. So, two questions, really, what inspired you to write the book at the time? And then the other question is, I look at your sales and go, "What?" What accounts for its astounding success? [10.39]

PF: It's actually shocking because you'll never find this book in a bookstore. It was published by Wharton Digital Press, as it was called at the time, now Wharton School Press. And the whole idea is, let's just kind of print on demand, so you'll never see it in a bookstore. So, there was no book tour for it or anything. It's just people, companies coming up with a lot of these ideas on their own I'm happy to say, that we need to be more data driven. Hey, our customers aren't all created equal. How can we leverage those differences instead of running away from them? And so for a lot of it is, it really is right time, right place. And I'm not saying this with some kind of false humility, any humble bragging, because like I said, it's less about me changing the world of marketing, but the world of marketing changing and just me offering just some direction for those who are trying to look for that new way of doing things. And the reason why I wrote the book is because this is not what I do for a living. I don't write lightweight books that have no math in them. I'm a serious academic, and I just write journal articles just filled with Greek. But I'm a math guy. And I build these models, again, very often standing on the shoulders of giants and collaborating with a lot of other smart people. And these models work really well. Our ability to forecast how many customers are gonna acquire, or how long they're gonna stay, or how often they're gonna buy from us, they work super well. And so for a good part of, say, the 2000s, if we turn back the clock to 20 years ago, I'd be just yelling at companies, "You got to try this stuff. It works. You got to give it a try. Here you go. Here, I'll give you videos, and R code, and technical notes, and spreadsheets. Just try it, will you?" And most companies would ignore me. They'd say either, A, "We're busy. We got a job to do. We're not gonna mess around with your nonsense." B, "You're an academic. You're not in the real world. What do you know?" And, C, "It's all very technical. There's a lot of math there." So, people would find every reason to either reject my stuff or to push it way down in the organization, "You know, yeah. Okay, yeah. Sure, there's someone who works for someone who works for me, and she'll deal with that stuff fine. But I'm the CMO. Not for me." And so that's a big reason why I wrote the first book, is to try to aim higher. Let's try to create some C-level appeal and C-level pressure that you're kind of missing the point. The world is changing, and you're not changing with it. So, if I could find a way, it's not so much to dumb down my models, no, no, no, but to layer a managerially relevant veneer over them, a Trojan Horse, to try to create a little bit of, like, "Whoa, what are we doing here? How are we gonna make it better?" And, of course, the answer to that would be, "I got some models for you." But let's not lead with the models. Let's lead with the so what?

SS: Well, the ethos, really.

PF: Exactly. So, let's just kind of clarify what we're talking about, motivate it. Talk about a little shock and awe, why you're doomed to fail if you don't follow. I mean, a bit of an overstatement, and that was it. The book was written out of frustration that companies weren't embracing a lot of these methodologies.

SS: Well, what's so impressive is that your book succeeded where a lot of other books along the same lines, I might add. Again, my shelf filled with books from the '80s about relationship marketing into the '90s, about CRM, and so on, and so forth. None of those books resonated to the degree that yours has. And maybe it's because of its simplicity.

PF: Let's not go too far with it. I mean, there are some folks who have kind of broken out of the pack and have sold a lot more books than I have. I'm thinking about, you know...

SS: Peppers & Rogers.

PF: Peppers & Rogers. And, yeah. Exactly. A couple of others floating around over there. And again, a lot of their work was inspirational for me, too. Mine just has a bit more of an edge to it. It's almost the snark involved in there. My willingness, and maybe naivete, you might say, to kind of go after specific companies and say, "You know, you're not as good as everyone says you are." [15.12]

SS: Nordstrom.

PF: To name names, Nordstrom, Starbucks, Apple, Walmart. And I wasn't doing that just for a kind of pure shock value. In fact, I really believed in the things I was saying, and I just happened to catch a lot of these companies at the time that they were starting to wake up. So, you point out that the first version of book one was written in 2011. And then when it came time to, and the folks at Wharton School Press said, "Okay. We need to update it, you know, a lot has happened 10 years since then." And so as I started writing the new version of book number one, you know, the new version came out in 2020, I read the old version and said, "You know what? I still believe in 90% of this stuff, so I'm not gonna write a new book. I'm just gonna treat that as a time capsule." So, I can say, A, "I still believe in the same stuff I believed in back then." B, "To the extent there are things that I was wrong about where I've changed my thinking about it, I'll admit that. I'll admit that." And, C, "Forget about me. The world itself has come a long way." And one of my favorite, favorite stories is which we open the book with. Usually, you have a preface that when you read a book, you ignore it. But here is, you must read this before you enter the time capsule.

SS: I love the preface. Yeah.

PF: And I tell the story about Starbucks. And after being really harsh about them, how...

SS: That community that they form, yeah.

PF: Exactly. How they kind of woke up and said, "You know what? Even though he's being mean to us, this is exactly what it is that we're trying to do." And I've had similar conversations with some of those other companies. So, again, it's not so much that I transformed them at all, is that they realized that the way they would achieve growth couldn't be the way it had been for the previous 20 years. They needed to do something different. They were already starting to think kind of in the same direction as I was, and I just happened to kind of be there saying the stuff that they were starting to think. And then they just sort of said, "You know what? Let's follow along."

SS: Well, it's interesting because in 2011, people reading your book would have said, "Yeah. We got to create a loyalty program for our high-value customers, or recognition program, or customer appreciation." Today, it's about building community around those very same customers. I had an interview with Mark Schaefer, not too long ago, and he's all over this concept of community marketing as a way to bring your advocates together. And many of those, obviously, are the high-value customers.

PF: Yes. So, a couple of things on that. One, yes, for the high value... Let me go flip it around what you said. For the high-value customers, we must create community, whether it's community of other users, whether it's community regarding other partners in the ecosystem who could all be working with together. We're seeing much more collaborations today across brands than we ever saw before. That's a really good sign. But at the same time, some people go a little bit too far with it and it's almost like if we build it, they will come. Let's just build a community and then money will come raining down from the sky. No. And so we need...

SS: It's hard to do.

PF: And you wanna make sure you're measuring it. You wanna make sure you're bringing the right people together. You wanna make sure that you're checking how valuable were they and how much is this community activity increasing their value or helping us to acquire customers who are more valuable than the ones we'd acquire otherwise. So, for me, it's always gonna come back to customer lifetime value. And that's just gonna help us do the community thing or really any kind of marketing activity, just more rigorously, more accountably, more comparably. And so, for me, it's once again leading back to the models and the measurement.

SS: Well, totally. Because one of the issues, of course, that community marketers face is the pushback they get from the financial folks because it's so hard to prove that return on investment. And we're gonna come back to that question for sure, as we go through this conversation today. I do wanna ask you this question. We've made a lot of, as you said, we've made a lot of progress in terms of companies accepting the idea that they need to put the customer at the center of their thinking.

PF: Not the customer.

SS: The best customers.

PF: The best customers. Thank you. Sorry.

SS: But to your point, I mean, the question I'd like to ask marketers is where is your next dollar likely gonna come from? The answer, of course, is your best customers. Yet marketers today still throw a lot of money at acquisition. They call it performance marketing these days. What accounts for this continuing to connect? [19.56]

PF: Oh, easy, easy, easy. A couple of things. It's just that we respond to what's right in front of us. We're humans. So, number one, we're very sensitive to costs. Thanks to companies like Google, we know exactly how much it costs when someone clicks on that sponsored search ad. We know exactly what it costs as someone goes through the funnel. And so we're just really painfully attuned to cost, cost, cost. And all I'm trying to do is - I'm not saying ignore costs. In fact, I wanna measure them even more carefully and allocate even more costs that we sometimes don't associate with customers. But I wanna create equal impact for value. I wanna say that the projected value of a customer should be right there at that same level of what it's costing us to acquire them. That if we can make value as visceral, tangible, measurable as cost, that's gonna change the calculus right there. And so, that's been happening quite a bit. So, when it comes to acquisition, can we bring in as many customers as we can, as cheaply as possible? Because both of those things, the cost of acquiring and, "Oh, look, new customers. Yay, we got to be doing something right." Even if they're crappy customers. That if we can focus a little bit more on, let's say, quality instead of quantity, it might, first of all, shift the balance away from just acquisition at all costs to the care and feeding of these customers after we acquire them and to let us be held accountable for those kinds of activities.

SS: Well, there's good growth and bad growth, and we're gonna come back to that conversation and the Byron Sharp question a little later on. So, just to go back to your point, though, marketers seem to be caught up in attribution modeling and attribution measurement - last click analysis because they're performance marketers, right? They're measuring bottom of funnel. There's a whole bunch of costs that have to be invested in the top of the funnel, too, just to obviously build awareness, and salience, and all those traditional brand managers. And there seems to be a disconnect between the brand marketing community and the performance marketing community with the performance guys winning because that's what the CFO actually pays attention to.

PF: And I have kind of a love-hate relationship with both camps because the performance marketers, again, I love they're doing stuff with data, and technology, and all that kind of thing, but it's very, very, very short-term oriented. We got to get that next click, we got to get that next conversion as opposed to lifetime value, which is, again, harder to measure, and therefore, it's not showing up in the usual performance marketing toolkit. And to the extent it is, it's gonna be some kind of dumbed-down average version of it as opposed to the rich, accurate ways we should be measuring lifetime value. And the branding people, again, they're the antithesis of that, that they wanna avoid accountability and measurement at all costs. They're saying, "It's all about the brand, it will take care of itself." And while there's some truth to that, it doesn't mean we can't measure it. So, I love the fact that they have the long-term perspective, as opposed to the short-term performance marketers. I love the fact that the performance marketers have that quantifiable perspective as opposed to the brand people, let's just create the best of all worlds. And I think lifetime value is that perfect thing that isn't fully embraced by either of those camps but really can help unite them.

SS: Well, the two issues being, it tends to be a bit of an abstract concept for all the reasons we were talking about earlier and you're shining light on, no, it doesn't have to be. And here's how you could go about it, which is tremendous value, certainly in terms of, not just acquisition but the whole sale relationship. And I wanna get into little meat and tails around CLV modeling momentarily. But let me step back, though, because you have an interesting resume in that three decades into academia, you get the entrepreneurial bug and you start this company called Zodiac. So, my question there is, what made you wanna start an analytics company? I guess maybe because you saw the gap. And then the other interesting thing is, I think three years later, Nike, you got the attention of Nike and they bought your company. Tell me a little bit about that story.

PF: So, a lot of the origin story is the same origin story of the books, that we're running these models, they're really good. People are ignoring them. And so start writing the books, just to try to create some of that shock and awe, like, "Oh, we're doomed to fail if we don't follow," which is, again, I'm overstating it, but you get the idea. And that was good. People would start paying attention. But the models that I was dishing out, like I was saying, the spreadsheets, the videos, all the stuff I was giving people, that was a lot of the academic stuff. And what we saw is that we needed to, if nothing else, just to scale the models from kind of academic grade to full commercial scale, as well as to add some other bells and whistles that might not be interesting academically, but are very, very practical. And we'd figured all this stuff out, and the journals weren't gonna pick it up. What am I gonna do with it? That's why we started Zodiac was, really, it was equal parts gospel-spreading that it's one thing to get people to wake up. It's one thing to lead the horse to water, but now, let's kind of shove his head in it or something. I don't know, whatever. Let's make sure that they can now do the right things, use lifetime value. And don't trust them to figure it out. Let's do it for them. Let's do it in the best possible way. And so that's what we were doing at Zodiac. And it worked. Every time we'd work with a company and we'd run the lifetime value thing and we'd see how well the models validated and the impact of the implications that would arise from the models, it was like, "This is cool. This is great." So, it was less an entrepreneurial thing. I mean, it was an entrepreneurial thing and we worked with venture capitalists and all that sort of thing. But it really was more just to create a platform, a podium, a way to get the word out there that I couldn't do purely sitting in my chair here in my academic office. And it served beautifully. Lots of great examples. It created lots more buzz in the industry, lots of just testimonials from companies and others saying, "Hey, work with us next." It just wouldn't happen unless we kind of really took control like that. And ultimately, as you said, when Nike bought the company in March of 2018, what an incredible testimonial that was. Not a big company but, A, a company doing it from a position of strength, not desperation. And, B, a company that wouldn't ordinarily associate with this kind of stuff. A company that traditionally was a B2B company, just selling boxes of footwear to Walmart and Foot Locker, all of a sudden saying, "No, that's not good enough for us anymore. We wanna have direct relationships. We wanna know who's buying what and what other things we can surround them with." Kind of a perfect case study of everything that I've been talking about turned out beautifully. And even today, here we are five years later, the fact that we're telling that story, and companies continue to ask about Zodiac, even though it's long gone, it shows what just a great move it was. (27.40]

SS: So, you could argue, though, Nike is maybe the most advanced progressive marketer in the world. Had you been doing work with them, did they see evidence of the success?

PF: Oh, yeah. Yeah, they were a client, just like dozens of other companies. And I remember so well, you know, a couple of weeks before the acquisition, where they came to us and said, "We want it all." And we said, "Oh, that's great. Terrific. We'll hire more engineers, data scientists, and customer success managers. We'll make sure that all of your needs are met." And they said, "No, no, no, you don't understand. We want it all." "So, what do you mean you want it all?" And basically, in the end, we had to fire our other clients and we were thinking, "Is this smart?" But, yeah, it was. It actually worked out really well. And I actually give Nike credit for going that next step beyond being a mere client to grabbing the whole thing and embracing it, and not just the models but even the philosophical aspects of it, as well as all of our employees and saying, "We need you to build all of this stuff from scratch internally." Again, very, very bold move on their part. And I don't wanna draw too much cause and effect here, but you look at their performance over the years since they bought the company, every quarter beating investor expectations. Is it because of our thing? Nah. But it's because of their own mindset, their own willingness to kind of march to their own beat and it's picking up the skills that they needed along the way.

SS: Well, as you say, they've shifted away from retailers as a distribution channel and are now pretty much direct to consumer and have their own shops as well.

PF: Yeah, their own shop as well. That's right. And even when they do work with retailers, and they still do, to a large extent, the way they manage those relationships, the way they measure them, it's just a very, very different way of operating than it had been. Unfortunately, it's still more exception than rule, the way that they're operating. Instead of every company saying, "We got to do the Nike thing," a lot of people say, "Well, that's Nike, they're different." Well, you could be different too, so...

SS: Well, let's face it, there's a lot of shoe manufacturers out there, and Nike found a way all the way back to the Michael Jordan signing to separate themselves from the pack, so...

PF: And very different ways, very different reasons. But you're right, they've always thought their own way.[30.01]

SS: Well, again, why I call them the most progressive marketer probably in the world. And now, so continue with the entrepreneurial track here. Five years ago, you started another company, which is pretty impressive, Theta. I think I have that right.

PF: Yeah, Theta. That's right.

SS: And its purpose, and I'm totally intrigued by this because I had a podcast interview with Neil Bendle, who I'm sure you know.

PF: Of course.

SS: And fascinating, funny, very amusing, very interesting guy. And we got into a bit of this conversation about customer valuations, etc. So, the company, as I understand it, is designed to help companies do corporate valuations for M&A work, in part, using CLV, if I understand that correctly. Is that correct?

PF: Yeah. So, I'll tell you the back story. So, while we're at Zodiac, most of the companies that we're working with, we were calculating lifetime value, but that was kind of a means to an end. They wanted to know basically which email to send to which customer at which time. "So, should we send a different message to the high-value customers and the low-value customers, and all that sort of thing?" So, it really was more about using CLV to enhance and measure the effectiveness of marketing tactics. It was all about that interactive platform to figure out slicing and dicing, and all that sort of thing. But one of our clients was a private equity firm out of LA, and they didn't want the interactive platform. They didn't care about any of the tactical stuff. They just wanted to know, we're thinking about buying that digitally-native, women's accessory company. What are they actually worth? And the point is, if we can project, here we go again, how many customers are we gonna acquire, and how long are they gonna stay, and how often they're gonna buy, and how much they're gonna spend, and add that up, that's the value of the company. And so, as we were selling to Nike, I remembered very well that their principal came to me and said, "Listen, maybe you can get a carve-out from... Nike doesn't care about any of that stuff. You think you can get a carve-out?" And Nike agreed to it. So, there's a combination of factors. One is just sheer opportunity to be able to work with investors. Number two is, when Nike bought Zodiac, there was, not surprisingly, a very strict non-compete. So, we were forbidden from doing any of the marketing tactical stuff for a number of years, yet we still wanted to play with our models. So, we needed to have this other outlet. And reason number three, which I can't emphasize enough, is my co-founder at both of those companies and my former Ph.D. student, my frequent co-author, Dan McCarthy, who came to this from a financial standpoint. He had worked at a couple of different hedge fund-type things before coming back to Wharton to get his Ph.D. The guy's super smart. And so, I've always spoken about the general idea of, "Hey, finance people should care about this stuff too." A lot of colleagues in the field, including Neil, have spoken about things like that. But it was Dan who was uniquely positioned to take all the goodness of the models, elevate them even higher, and figure out how to build the bridge to finance in a way that, not only would the models work but that we could speak about it credibly instead of saying, "Hey, finance people, you're doing it all wrong. You got to listen to us marketers." Yeah, that's gonna go well. To be able to speak their language and understand their issues, their desires, their limitations, and have our models fit their needs, Dan did that and has done that superbly well. And that's just opened up all kinds of opportunities, both for Theta, as the ongoing research and just the broader conversation about how we can get this customer-centricity thing going.

SS: Well, again, it's one of those things we've been talking about for years. Peppers & Rogers, we were talking about them earlier, wrote a book on this, “Return on Customer”, and their clarion call to the Wall Street to say, "Hey, you guys got to..." And that was written two, three decades ago. And the other one now on the bandwagon for this, of course, is Fred Reichheld with his NPS model because he's realizing the biggest barrier to this is nobody really makes the connection between NPS and the corporate values. So, he's written the whole book just dealing with that subject. So, I really see the need for what you're doing. My question here, though, is accountants are conservative. And if you were gonna pursue a career as an actuary, you certainly know that culture. And it's hard to change generally accepted accounting principles. Concepts like customer asset value, even brand equity, are buried under goodwill on the balance sheet. It's never called out. It's never visible. Is part of your mission here to get that mentality or mindset … [35.02]

PF: So, interesting. I love it. I love it. I love it. So, back in the old days... The answer is yes. But to get more specific, back in the old days, I was always saying, "Along with other marketers, we need to project all that lifetime value. We need to add all of it up." And that became - no, I didn't come up with this idea, others did - the idea of customer equity.

SS: Equity.

PF: And I made a big deal about that, that we should be putting all of that projected value in financial statements. And it made sense until I met Dan McCarthy, and Dan said, "No, no, that's just not gonna happen. Not only is no company, no finance executive ever gonna do that. You know what? They shouldn't. We should not be putting kind of forward-looking projected numbers on accountable financial statements because they're not accountable." So, a couple of things on that. Number one, when I rewrote the book, you know, here's the time capsule from 10 years ago, and I disavowed certain things.

SS: Customer equity being one.

PF: First and foremost, there's a little footnote on the customer equity chapter saying, "I don't believe this anymore," thanks to Dan. So, instead, let's come up with accountable auditable measures that would be very tightly associated with lifetime value and customer equity, but things that we really could measure and report in a standardized way. So that was a big part of Dan's dissertation, is what kinds of easily observable metrics could we have at our fingertips that would be strongly indicative of lifetime value, customer equity, that we could report that would basically serve as a strong proxy for them? Again, I can go on for days and days about that, so let's do so in a way that's gonna meet the best of both worlds, that it would meet those kind of conservative, descriptive standards of accounting, but at the same time would be strong indications of how much gas you have in the tank. And it's been great. We're actually getting public companies to start disclosing some of these customer metrics, which on their own, it's like, "Okay, whatever. It's a metric." But if you know what you're doing, you know how to reverse engineer the whole thing, you could take those metrics and turn them into forward value. So, this is a big part of both our research and our gospel-spreading agenda.

SS: Well, it's interesting because I went through the write-up on your site about Warby Parker, and I found it fascinating going through that, the projected cash flow and basically coming to the conclusion that they're kind of maybe overvalued a little bit, but they...

PF: They were overvalued at the time of the IPO.

SS: Right. At the time of the IPO.

PF: Fast forward, a year and a half, now they're grossly undervalued. Now, who knows by the time people see this where they'll be. And the whole point is to that analysis and so many of our analyses is that while the pendulum on the stock market is swinging wildly, let's not worry about stock prices. Let's just worry about the unit economics, the value of customers. And basically, if you think about it, the way that people buy glasses is pretty much the same today as it was a year and a half ago. The unit economics of a given customer or the mix of their customers is pretty much the same as it was a year and a half ago. The value of the company hasn't really changed very much. And so, these estimates that we're gonna come up with are not only more diagnostic, and interesting, and ultimately accurate but they also tend to be much more reflective of actual customer behavior, often much more stable than just the kind of whims of Wall Street.

SS: There's huge opportunity with companies today collecting more and more first-party data and sitting on these vast troves of big data. The sorts of modeling you're doing relies on fairly granular transactional analysis. What happens with the companies that aren't quite there yet? Do you have workaround solutions for them or do you have proxies for them?

PF: Absolutely. I can take that in three different directions. So, first of all, if you're just getting going and you haven't set up the proper CRM system yet, or you don't have enough data to really trust the models, yeah, you wanna start with a proxy. And I'm good with that because I wanna make sure, to me, as much as I love customer lifetime value measurement, I wanna make sure that we have the right culture in place, the right infrastructure. We know what we're gonna do with it. It's not a magic wand. And so, I have no problem using a proxy measure like Net Promoter Score or maybe someone's credit score. Again, those things aren't gonna be nearly as accurate and forward-looking as a proper CLV. But if we can just start to get going, to say, "You know, what makes the promoters different from the detractors and how do we build the business around them, and so on?" I am totally fine using different kinds of proxy measures to get going. In fact, in some ways, let's find that we can run the business more effectively by celebrating these value proxies. And it's gonna make it that much easier, that much more motivating for us to, okay, you know what? Now let's do it the right way. So, I'm fine to walk before we run. And again, NPS can be very, very useful in that regard. [40.10]

SS: Well, let me run another metric by you, and this is associated with my question around, so growth. For most CMOs I look out today, and the metric that matters seems to be most to them is often revenue growth, right? They're even changing titles from CMO to Chief Revenue Officer and velocity, growth velocity. Is my category growth outpacing market growth, right? Am I doing better than the market would suggest that I am? So, my question there is, when you're talking about proxies, as an example, should share of wallet maybe be the main metric here?

PF: Nah. Share of wallet can be derived from the metric, so we happen to have several papers on it. So, I have nothing against that metric. The problem is, even at the individual level, it's still lumping together a bunch of different behaviors. If you think about it, when I talk about the components of lifetime value and I sound like a broken record, it's how long are you gonna stay, how often are you gonna buy, and how much are you gonna spend when you do? It's really important for me to be able to break things down into those components and project them out separately. And share of wallet is kind of bringing them all together. So, in that sense, it's a nice holistic measure, but by itself, it's not gonna give me... If your share of wallet as a whole is, let's say, leveling off or decreasing, is it because customers aren't staying as long, they're not buying as often, they're not spending as much when they do? So, when I start looking at metrics, I want metrics that would help me single out and project one of those behaviors or another. Again, that's back to Dan McCarthy, back to what we do with Theta is figuring out the appropriate metrics for each separate behavior so we can kind of reverse engineer each different behavioral component, and therefore get a more accurate, more diagnostic revenue projection.

SS: So, on the CMO's dashboard, there's the traditional metrics, market share, penetration, share of wallet, share of expenditures, whatever the term you wanna use. And your argument here is that CLV deserves equal, if not superior …

PF: Actually, no, no, no. So, CLV is the North Star that pulls everything together. But again, I recognize the limitations. We're never going to report CLV externally, so let's instead report the things that would let us understand the components of CLV. So, let's report things about either customer retention or repeat buying. What percent of our customers who did something with us last period are still doing stuff with us now? So, that's gonna pick up one aspect of it, that's how long is the relationship gonna last? The other would be, among the active customers, how many purchases on average or economically valuable interactions did they make with us, that's gonna pick up how often are you buying. And the third part, how much are you spending when you spend? What's ARPU, average revenue per user? So, I wanna basically come up with separate metrics that pick up these separate kinds of behaviors, project each one out, and then bring it all together. So, it's interesting that, as much as we talk about lifetime value all the time, when we're doing customer-based corporate valuation, again, the kind of work that we'll do with Theta, we're rarely doing that with lifetime value. We're gonna calculate lifetime value and we'll report that to you. And you could look to see how these customers are doing compared to those customers. But the main thing that's driving the valuation will be that next level down set of components related to retention, repeat purchase, and spend together.

SS: Right. Exactly. And we call it the cascading scorecard here, where you have at the top level, really business outcome measures that the CMO, CEO cares about and then the diagnostic measures, and so on, and so forth, right down to the bottom tier. A hard thing to do unless you have a company like yourself available to do some of those correlations. And I wanna touch on this because I know this is another bit of a touchy subject, which is Byron Sharp...

PF: Oh, not touchy at all.

SS: ...about penetration trump's loyalty. And I just wonder, does his message contradict yours? And let me just explain myself. It seems that his stick is growth only comes by attracting as many buyers, I don't care what kind of buyers, as possible. But what you get, to me, if you have that strategy, is a lot of one-and-done buyers. You have price-driven buyers, you have light buyers, you have promiscuous buyers, you have brand switchers, you got a lot of dilution that, frankly, is a distraction for the business to cater to those customers. So, what's your perspective on his thinking? [45.01]

PF: Well, let me first start by saying I am probably the strongest advocate for Byron Sharp and the Ehrenberg-Bass Institute down there at the University of South Australia. I'm probably the strongest advocate in the entire Western Hemisphere.

SS: You teach it, right? You teach it, yeah.

PF: I teach it, hours and hours of it. If you notice, you can't see it. But up on the bookshelf, I have every Byron Sharp book over there, and I bring them to class and I say, "I don't have a textbook for my course, but if I did, this is probably it. I want people to read it. I want people to know it." It turns out that Byron is 80% correct. And in that 80%, everything that you said and everything that I'm sure a lot of your listeners know about, focusing on penetration, focusing on getting the message out there broadly, focusing on a variety of different benefits instead of nichefying yourself around one. I agree. I agree. I agree - for 80% of the customers. Because you described that most of our customers, if we believe in 80/20 rules, that 80% of our customers are...they're not gonna stay that long, they're not gonna do much, and there's not much we can do.

SS: They may not even be your customers.

PF: I love that point. And something that we emphasize a lot in the new book, we'll talk more about that. So, for the so-so customers, which constitute most of your customer base, 100% agreeing with Byron. He's wrong on the other 20%, which is to say he grossly underestimates the value of the high-value customers. And it turns out that the basic model that's at the heart of what Byron does, which I believe in, too, the NBD-Dirichlet multinomial model, it's a wonderful model, but it's missing one component, which is basically how customers change over time. It's a static model. And when we bring in, what we call non-stationarity, allowing customers to evolve over time, something which, by the way, Byron's mentor, Andrew Ehrenberg full well knew, he'd refer, in occasion, reluctantly, to the idea of a leaky bucket. That when we bring that one piece into the model, and it's important, then those high-value customers actually become even more valuable and more important. And that's where all this focus on the right customers for strategic advantage comes in, that we got to make sure that we're doing the President's Gold Medal, Red Carpet, Blue Ribbon Club for those high-value customers, but recognizing there's very few of them and that most of our customers are, "Meh." And with those other customers, it's gonna be all about the empirical laws of Byron Sharp. So, I actually feel there's a very clear reconciliation between the two approaches. And I'll even say that I think Byron and I have just a wonderful relationship. Almost all of our exchanges are very, very positive, even if we disagree about what happens with the right tail of the customers. So, full speed ahead. And I want everyone to read and think about that work, just to recognize that the high-value customers, they're different and we ingneed to do different things with and for them.

SS: But the logic of CLV, and it's, to me, flawless logic, is that if I've spent money acquiring a customer, and some customers, I may lose money actually acquiring them, and credit card companies know this. They know that it's gonna take them three, three and a half, sometimes four years to get payback on those customers. They've been using CLV modeling forever to drive their business models. But I just wanna come back to this idea of management of those segments because, ultimately, it comes down to budget. So, market CMO gets 12% of the budget and then spends, to your point, 80% on acquisition and 20% on customer management, and customer management being relationship management, shouldn't it kind of be the reverse?

PF: Well, yes and no. It all depends on how that acquisition budget is being spent. If it's being spent, as it is by most companies on purely performance marketing, let's bring in as many customers as we can as cheaply as possible, that's a problem because we're gonna acquire a whole bunch of “meh” customers hoping and praying that they could become good. They probably won't. If instead, we're spending that budget a little bit more on quality instead of quantity, then it might not. Now, if it's 80% on acquisition, 20% on retention development, that is a little too imbalanced, I'll agree. But it's not so much the overall quantity of dollars that companies are spending on acquisition, it's how they're spending it. And that tends to be what's more troublesome is, again, that this hunt for low-cost quantity as opposed to high-cost quality. [49.43]

SS: Well, and I think, too, I think the other challenge is, this goes back to the attribution modeling. Because today, let's face it, marketing messaging, and advertising is having diminishing effect of this. We're seeing budgets diminishing quite significantly in ad spending. I don't know what that portends for the future of the ad business. Eventually, that phrase, advertising, is gonna disappear, is gonna become a reality. The question is, do marketers lose their budgets at that point, or do they find a way to more productively spend that money by improving the experience of customers?

PF: So, if we can find a way to spend that money more effectively and do so in an accountable manner, go back to the CFO and say, "Okay. Here's all the different campaigns I tried. Here's all the different technology I invested in. Here is the ROI on each of those things measured by lifetime value. So, here are the kind of campaigns we're gonna let go of. Here's the kind of campaigns we're gonna ramp up. We're gonna run some experiments." If we can have just a real accountable conversation about it where we're just totally upfront about how we're measuring these things, and we're doing so in a completely standardized way, we're not changing every quarter depending on what mood we're in, I think we can maybe even increase the marketing budgets because we're doing so in a responsible way that a lot of marketers would rather not or don't even know how to do.

SS: Well, to be able to show linear effects, say, between satisfaction, loyalty, and improved revenues. I mean, Fred Reichheld claims that that can be done, but there's plenty of cynics around that, too.

PF: You know, I love Net Promoter Score. And I love Reichheld's work. Before he even could spell NPS, he wrote the book, "The Loyalty Effect."

SS: I read it in the mid-90s.

PF: It's a fantastic book.

SS: It is, and it holds up by the way.

PF: It's amazing. I wave it around all the time because it's a really important lesson. The whole point of that book is not all customers are created equal. If we can find the right ones, they're gonna stay with us a long time, buy very often, spend a lot when they do, they're gonna be cheaper to serve. They're gonna recommend us to other people. Now, not every customer is gonna be that, and we can't turn the so-so into those beautiful swans. But if we can figure out what makes those customers different and cater to them and acquire more like them... And we need a metric that's going to reflect how good a job we're doing at finding and caring for those customers versus the so-so ones. And that's how we invented Net Promoter Score, was this looking around for a metric that reflected the heterogeneity among the customer base. Remember, we're not taking an average satisfaction score. We're taking the difference. I love that. And the problem is, a lot of people forget the original motivation of NPS and they say, "Oh, we just maximize our NPS. We got to get to NPS 60 by next year. We got to turn those ugly ducklings into beautiful swans." And you can't do that. So, we can't blame NPS, we can't blame Fred, we can't blame Bain Consulting for it. In fact, we're doing wonderful, wonderful work with his partner on a lot of the books, Rob Markey.

SS: Yeah, Rob.

PF: We've written a number of articles and a lot of presentations together. He totally believes in everything we're saying and understands that if we can do this more financial sort of thing, it can bring more clarity, more value to NPS. It can let us dovetail perfectly between the kinds of behavioral metrics that we're focusing on and the attitudinal nature of an NPS. And each one makes the other better. So, full speed ahead with all that. We just wish that people knew what they were doing and knew why they're even working with that metric in the first place.

SS: Well, and certainly there's misunderstanding and misuse. There's a whole bunch of issues around that, which I talked to Fred about. But there is this cause and correlation question with loyalty. Let's say, whether it's NPS as the metric or some composite metric that looks, not just at likelihood to recommend but looks at true emotional loyalty, that is, "Am I gonna go out of my way to buy this product that's not available on the shelf?" I mean, really true... the type of loyalty that Apple gets, as an example, and other really successful brands. So, the question is, whatever those metrics are, it's been building the business case for it that shows the connection to the bottom line, and that's been the challenge all along, hasn't it? And that's where you fit in really.

PF: Exactly. So, what I wanna do is I wanna find that just right middle ground between the overall valuation and kind of these emotional activities and measures. And, for me, it's gonna be these same basic, boring building blocks I keep talking about: acquisition, retention, repeat purchase, spend. Because those are the things that we really need to focus on, how many customers acquiring and how long they're staying. Now, it's not enough just to have metrics around them. We need to understand why things are working. And that's gonna take us to the more qualitative measures. Problem with so many companies is they'll do the qualitative stuff or they'll do the attitudinal thing, and they'll do it across the whole customer base. So, what are the hot buttons for the customer? That's why I corrected you earlier, saying, we can never talk about the customer. Let's do it separately by, let's say, lifetime value tiers. Let's look at our top 10% of customers and see what is it they're seeing. What are they saying, what are they doing? What are their needs, benefits, frustrations? And how is it different from tier number two, or three, or four, or five? So, let's figure out what are the kind of emotional buttons for each type of customer, each value tier of customers, rather than trying to do it on an overall basis. And you're getting stunning insights about that. [55.32]

SS: I couldn't agree more is that one of the issues, again, challenges within the industry is this separation of church and state between attitudinal surveying and behavioral analysis. And because the attitudinal side was driven by researchers, who weren't that comfortable, really with the other side, and vice versa, I might add. But if you bring those two things together, it's extremely powerful. I do wanna ask a big question, and you allude to it in your "Customer Centricity" book, but obviously at a very high level. First of all, the concept of CLV and financials metrics, as I said at the start, marketers aren't comfortable with numbers. Low financial literacy, blah, blah, blah. First of all, should customer accounting, or the sorts of techniques and modeling that you do where you're trying to tie it to the balance sheet, should that be an independent department from marketing, basically run as a bridge between finance and marketing?

PF: Bless your heart. Such an important question. And first, let me say, you know, guilty as charged, not that you're accusing me of anything. But I spent all this time, a lot of the research, just focusing on how can we take revenue and break it down to the components and slice and dice and project it forward. And too often we either neglect or greatly downplay the role of costs in the equation, whether it's acquisition costs or the costs of the ongoing care and feeding of customers. Another amazing wake-up call from Dan McCarthy, who's pointed this out. And so many of the conversations that we'll have with companies is on the cost side is let's make sure that we have all of the costs involved. Like, "You know what? We just built a new store." And you might say, "Well, that has nothing to do with the customers. That's pure overhead." But, you know, if it's helping us acquire more customers and getting them to stay with us longer and buy more often, then some aspects of that store should be showing up in the customer accounting. So, yes. It's really, really important to do it right, to do it conservatively, to do it in an auditable manner, and to weave it in with all of the more revenue and value metrics that we're coming up with. And we're getting really good on the revenue and value side, but it's still pretty messy on the cost side. And the fact that a marketing professor would have something to say about cost measurement is not good. I mean, I shouldn't be leading the conversation, at least. So, yeah. It's really, really important to have just as much care about which costs, and how we measure them, and how we weave them in with revenues.

SS: Well, it's so interesting because I had a technical question for you, which I was gonna leave out of this conversation because we were running out of time. But it dealt exactly with that issue, because one of the things I've wrestled with, with CLV modeling is cost allocation. Fixed versus variable, cost of acquisition, cost of goods, cost to serve, general overhead, actual direct and indirect marketing costs, how do they get allocated? How does that factor in? How do you spread it across the base customers, keep the lights on, blah, blah, blah? So, I'm glad to hear that you got to crack the code on that somehow, right?

PF: Yes. And there shouldn't be a code to be cracked. There should be big, obvious, transparent, agreed-on standards. It should be blaring at us instead of a code. And we don't even rule out the possibility that to keep writing all these books and things, that we could have one just on accounting for customer costs. Now, obviously, again, you're not gonna just count on marketers to do that. We need to have conversations with some of our accounting colleagues, and we've been having very productive conversations with them. I think there's a lot of work that needs to be done. We've made such progress on the upside. We need to kind of match it on the cost side. Once again, Dan has really, really led the way both on motivating that, as well as getting into some of the nitty-gritty about those allocations.

SS: Are you working with Neil and his association on refining and integrating some of these core concepts?

PF: So, we're having lots of conversations about it. No formal collaborations, although Neil and Dan speak very, very frequently about it. The two of them are extremely close, but it's not like we don't have any formal relationship or any formal endorsements, just a lot of mutual respect and a recognition that we all have to raise our game on that front.

SS: Yeah. Well, you're all working really toward the same goal, frankly, aren't you?

PF: Exactly. Look, part of it is, not only do we want to have the most accurate measures and all that sort of thing but we want to have absolute respect. We don't want the people in accounting or finance to be looking at us as just a bunch of lightweight marketers. That we want them to look and say, "You know what? They really do have something to contribute that's of value to me." And I think we've been making a lot of good progress in that regard.

SS: Right. Well, that's a great way to end this. I can't tell you how much fun I've had with this conversation because so rarely do I meet a person who's actually on the same wavelength with respect to customer analysis. And your books have done a tremendous service to the industry and trying to advance the conversation, you yourself, obviously on the speaking circuit and so on. So, I look forward to your next book, maybe even your next company, who knows?

PF: Yeah, there's lots of good stuff yet to come. It's only just getting better and more interesting. So, look forward to keeping the conversation going.

That concludes my interview with Peter Fader. As we learned, a bottom-up analysis of the buying behaviour within the customer base can reveal how much future growth will be driven by existing customers versus first time buyers. Once that number is determined, a company can back into an acquisition strategy and budget, knowing the precise shortfall between corporate growth targets and forecasted customer revenue. Companies need to stratify their customer base from best to worst based on past spending. They need to understand the health of that customer base based on changes in buying behaviour, average revenue per customer, the rate of spending velocity, churn rates and a host of other component measures. And then they need to convert that knowledge into a customer-centric strategy that will pay disproportionate attention to the high value customers.

Stephen Shaw is the Chief Strategy Officer of Kenna, a marketing solutions provider specializing in delivering a more unified customer experience. Stephen can be reached via e-mail at sshaw@kenna.