The Case For Customer Lifetime Value - Why Is This So Hard? | Daniel McCarthy | CMO Confidential

This episode explores the complexities and importance of understanding and implementing customer lifetime value (CLV) in business strategies.

1. Customer lifetime value (CLV) is essential for understanding long-term profitability.
2. Accurate CLV calculation requires a deep dive into analytics and predictive modeling.
3. Marketing departments often struggle to justify their budgets, which CLV can help address by linking marketing spend to future revenue.
4. Business schools need to update their curricula to include more real-world applications like CLV.
5. The episode illustrates practical examples of how companies successfully implement CLV strategies.

1: Introduction to Customer Lifetime Value

This chapter outlines the fundamental concepts of customer lifetime value and its importance. Mike Linton: "Welcome to CMO Confidential, where we dive into the complexities of marketing leadership."

2: McCarthy's Background and Expertise

Discussion on Daniel McCarthy's career and his contributions to the field of marketing analytics. Daniel McCarthy: "I've focused on applying statistical methodologies to solve contemporary marketing problems."

3: Challenges of Implementing CLV

Explains the difficulties businesses face when trying to implement CLV effectively. Daniel McCarthy: "Getting cultural alignment and buy-in at all organizational levels is crucial for CLV implementation."

4: Case Studies and Real-World Applications

McCarthy shares insights from his practical experiences with companies like Warby Parker. Daniel McCarthy: "These real-world applications show the direct impact of CLV on business strategies."

5: The Future of Marketing Education

Discussion on how marketing education needs to evolve to include analytics and data-driven decision-making. Daniel McCarthy: "There's a gap in most MBA programs when it comes to teaching the practical applications of concepts like CLV."

• Start integrating CLV models into business strategies to better predict and enhance long-term profitability.
• Educate marketing teams on the importance and methodology of CLV to foster a more analytics-driven culture.
• Align marketing objectives with overall business goals using CLV as a guiding metric.
• Advocate for the inclusion of modern marketing analytics topics in business school curricula.
• Regularly update and refine CLV models to reflect changes in customer behavior and market conditions.

A CMO Confidential Interview with Dr. Daniel McCarthy, Assistant Professor of Marketing at Emory's Goizueta Business School. Dan discusses how marketing has recently taken its knocks, why he created a CLTV class, how companies can start developing their own models, and how customer math can be used to increase marketing accountability. Key topics include: why it is challenging to agree on key modeling variables like acquisition cost; how CLTV can bridge the translation gap between marketers and finance; and why business schools are slow to evolve. Tune in to hear Warby Parker and Wayfair case studies.

People

Mike Linton, Daniel McCarthy

Companies

Emory University, Theta Equity Partners, Zodiac, Nike

Content Warnings:

None

Mike Linton

The CMO Confidential Podcast is a proud member of the I Hear Everything podcast network looking to launch or scale your podcast? I hear everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit ihereverything.com dot. Welcome to CMO Confidential, the podcast that takes you inside the drama, decisions and choices that go with being the head of marketing.

Dan McCarthy

Hosted by five times CMO Mike Linton. Welcome marketers, advertisers and those who love them. The chief marketing officer, Confidential CMO Confidential is a program that takes you inside the drama, the decisions, and the politics that go with being the head of marketing at any company into what is one of the most scrutinized jobs in the executive suite. I'm Mike Linton, the former chief marketing officer of Best Buy, eBay, Farmers Insurance and Ancestry.com, here today with my guest, Doctor Dan McCarthy. Today's topic, the case for customer lifetime value.

Mike Linton

Why is this such a hard concept? Now, Dan is perfect to talk about this. He's an assistant marketing professor at the Gazette Business School at Emory University, where he's been there for a little over seven years. He built a predictive analytics firm called Zodiac, which he sold to Nike in 2018, and he also founded Theta Equity Partners. Now Dan's specialty, and you probably want to write this down, is the application of statistical methodology to contemporary marketing problems.

And he has created what I think is the first customer lifetime value business school class. Welcome, Daniel. It's great to be with you. Really excited to talk all things clv and how it connects with everything else. We are too.

Before we get into that, though, give us a quick overview of what you are seeing in marketing. In the wild with everything going on. AI, big data, the pace of change, recession, not a recession coming off the pandemic. How's the profession trending in your mind? Yeah, it's a good question.

Dan McCarthy

I mean, marketing has taken its knocks, so certainly budgets are tight. If you're a vendor, all those discretionary projects, that would be very interesting to pursue. I think a lot of companies are taking a much sharper eye to those projects, and this actually speaks to what we'll talk about a little bit later. But there's this issue of marketing accountability and how oftentimes the CMO role can be something of a revolving door, and that the marketers can often be blamed and be the first ones to experience layoffs when times get tough. Because historically they've had a tough time being able to justify the value that they create and so, yes, I know it's all going to be, it's well trodden territory for you, but certainly, as we're having these, you know, kind of uneven times, some businesses are doing great, and so, you know, they're not experiencing any of it, but others are having a really tough time.

And, yeah, I think a lot of the first people to get cut, you know, a bunch of them are within the marketing department. So, yeah, so it's kind of a weird. It's just a weird environment. Very polarized. Oh, and we are definitely hearing that.

Mike Linton

We're hearing also from a lot of b two B people about budgets being cut and the rush for acquisition. Suddenly a 180 degree turn to, okay, now it's profitable growth and with a lot less money. And that is putting a huge amount of pressure on a lot of folks. So, particularly if you don't have data or you don't have math. So with that as a little background, though, and I agree with your assessment of, of the marketing universe right now, give us an overview of customer lifetime value and what you really teach in this course, because a lot of people talk about it.

I'm not sure everybody really actually knows about it or the real application. Yeah, we kind of run the gamut. So it's not a pure models course, but it's certainly, it's not a pure course for the poets. We, we touch on both the strategy, the philosophy, and some of the modeling. Get the cliff notes of that, the strategy, the philosophy and the modeling.

So people know the building blocks of the story. Yeah, I think actually this mimics when we think about successfully implementing and making money off of CLV, that's really what companies looking to do. They want to grow shareholder value, and if they can't do that, they're not going to pursue it. And step number one, oftentimes is getting cultural alignment that you have kind of buy in from people higher up in the organization because you can have all the greatest ideas in the world, but if you can't get your boss and your boss's boss to buy into them, yeah, it's going to be pretty tough sledding. You may not have the budget.

Dan McCarthy

You may not have the support you need to actually implement. So we'll talk about customer centricity, as Pete Fader defines it at the very beginning of the course. And that's really to help just lay the groundwork. Why are we even doing all of this? Why do we care about retention modeling?

Well, there's a lot of value that can be made, generated by looking at the world through the customer lens and specifically through the lens of customer valuation and customers, really different in terms of the profit potential that they can generate for a firm. Very different in terms of what they care about. And just leveraging that can create all these new opportunities that wouldn't have been there if you were just looking at the world through the lens of product. Yes, we'll spend a bit of time with that right at the front, just. So everybody knows, to make sure I'm getting this right.

Mike Linton

Dan, this customer lifetime value says it's the value of all your future customer sales. And then how you can actually adjust that by improving loyalty or better customer feed. But it's really using the customer as the building block to your long term financials. Is that a fair Cliff notes journeyman summary of this? Yeah.

Dan McCarthy

For what CLV is and how it could be leveraged, pretty much. And it actually is a great segue into kind of the second part of the course, which is how do we even define the damn thing? You ask ten people, what is customer lifetime value in terms of numbers? And you might get ten different answers. And so, yeah, so step number two is to say, okay, let's create a formula.

Imagine that we had these customers and we could see their entire lifetime. We could see the profit, we can see the revenue, we could see the acquisition cost. We had all that data. We should then be able to agree on what the customer's lifetime value was, you know, and so. But, yeah, I think because there is that confusion, it really merits.

I devote a whole class just to the definition of CLV and then to kind of other related terms that are very similar and relevant and valuable in other ways. But, you know, maybe are not, not quite the same thing. And so I'll spend a lecture just on those definitions. It's not about revenue, it's about profitability. Specifically, it's about incremental profit or marginal profit.

How do we think about customer acquisition costs? I'll spend a whole lecture just on the definition of customer acquisition cost. And I'll often say I could spend. A whole course, which sounds like it's really easy, but it is never easy, and it's very complicated. You think it should be easier because in theory it already happened, right?

You spent the money to acquire the customers. They came in the door, you're looking backwards. It should just be an accounting exercise. Whereas ClV, we're making this projection into the future. The future is uncertain.

We don't know what's going to happen there. But I think in some ways, predicting the net present value of profit into the future. In some ways it's easier because of all the attribution incrementality questions that inevitably crop up when you start really peeling back the layers of the onion on CAC. So I spent a lecture on that and the time. I wish I had at least a couple.

But I think once the definitions are in place for all these key measures like CAC, contribution margin, CLV, how we think about some of the bookkeeping, then we start moving into the modeling. And I think there were in a position we know what we're shooting for now. How do we start making these predictions that we need? And that's where we'll start going into retention modeling. And then we go into how we think about spend, repeat purchase and non subscription settings, and then rolling it all up into customer lifetime value estimates.

Mike Linton

So that sounds like a superclass. I've done this a couple of times, or at least tried to do it, and one of the biggest arguments are the multipliers you put in for some lifetime value and the assumptions you start making about future changes to the product or the pricing or anything else where one or two model variants can blow up the number one way or the other. Does that happen a lot? And how do you teach around like arguing about those variables and picking them? Yeah, I up mean, I'm a statistician by training.

Dan McCarthy

My PhD is in statistics. It's not even in marketing. And yeah, I treat it as any other prediction problem that we want to. To your point, we want to make sure that the model predicts well. And if you think about the CLV formula right off the bat, you have to be a little worried.

If you are using a formula, you're probably not getting good predictions. But because CLV is a prediction, we can see how well we predict. And if we pretended like we didn't have the last year's worth of data, we could take all the data before that and see. All right, well, how well would my model have done in predicting backwards? Yeah, yeah, I think that's a great litmus test, especially if you had some of the events that you're talking about, pricing changes and things like that.

It allows you to really stress test how good your model is, or maybe it gives good predictions, but there's some inevitable uncertainty or error. What's my 95% confidence interval? So now we can start making sure that this is the model that we can trust instead of plugging some numbers into a formula. Once you have your model in this class, how often are you adjusting the model, is it a constant, organic kind of adjustment, or is it a point in time reference kind of thing, or is it a combination? So we'll, in class, we will do some modeling across cohorts.

And so, yeah, imagine that you're working either the CMO, Best Buy or ancestry.com dot. You have all these customers that are being acquired at different points in time. And in theory, you want to have retention models or retention curves for every single one of those cohorts. As those new customers come in, you want to do something about them.

We call that cross cohort modeling. We'll have a lecture or two just on how we move from taking this one shot cohort to. All right, let's see what statements we can make about the entire customer base where we're thinking about it in a cohort by cohort way. So, yeah, if we were doing this in practice, you probably would want to rerun the model periodically, but as new data comes in, you're going to probably want to take your old model, run the new data through it. And that probably should be happening on a more regular basis because the data.

New data is coming in every day. So, Dan, what prompted you to go down this path, create this course, do this, you know, customer lifetime value thing? I mean, what. What. What drove this whole, I'm going to do this thing?

Psychosis. I had too much coffee. Yeah, it's a good question because I had, when I first came to Emory, I taught a course on plain old marketing research. You know, survey design, non response conjoint factor analysis, some of the usual kind of nuts and bolts of a traditional marketing research course. And it was going great.

And the course evaluations were really good. I won a couple of teaching awards for it. But my research, it's all about CLV. And all this, the work that I'm doing in industry, it's also all about CLV. So again, I like those concepts, the marketing research concepts.

But I jump out of bed to talk about the CLv stuff, and so it's just fun. Yeah. So I thought, you know, first there is this real gap in the MBA curriculum where we just. We don't have this. The closest thing that we'll often have is like a CRM course.

Mike Linton

Right. And this is very much not. And you can hear from this description of the class, it's just very much not that. Well, CRM, it just sits on top of stuff like this and optimizes it. Or at least that would be my take.

But it doesn't actually do it like this. Yeah, so you create this class and let's just move on. I want to talk about how come business schools are not like absorbing classes like this and big data and other stuff at speed, because that is what's happening in the marketplace is all this stuff is crashing into the cmo space and cmos are looking around for how do I get a handle on this fast? And you can look back at not all the schools, but surely some of the schools and say they're not evolving at the same speed as the marketplace at all. And your class is kind of an example of how come it takes you to do this class.

How come there's not millions of classes like this being developed around all the new data and technology all over the place? Yeah, there should be. I really, I think that there should be a course like this that is being taught at many, many more universities than just Emory University and soon to be University of Maryland when I moved there. Um, so yes, I think it's uh, it's been slow to change. And I do think that there is an element that, uh, you know, business school's, you know, course curriculum, it's, it's been slow to, it is, it tends to be slow to evolve.

Dan McCarthy

You know, there's a lot of material that we teach that it's very over indexed towards CPG. And um, and it's not that CPG isn't very important, it's tremendously important. But other things have become important too. And so if we want to cater to all of these other new kind of growth vectors of our economy, we need to have courses that teach concepts that are more relevant to those jobs. Look, we just did a show about believers and non believers with McKenzie and the ANA.

Mike Linton

And what they said is one of the biggest problems here is business schools are not keeping up on the marketing front. And why? I mean, I agree with what you're saying because having hired some folks out of obedience schools and looking at it also, my producer and I have been talking to, trying to talk to some of the colleges here just to help. And the reception on new stuff doesn't appear to be that great. Why?

Dan McCarthy

Yeah, it's a slow moving machine. I'd say that creating a. And now I know this firsthand. Creating a course, it takes a lot of time and effort and pain, and it's a real labor of love. And especially for a junior faculty, our incentive is especially us on the research track.

The first priority is to publish top quality research. Yeah, that's kind of the first priority. So you want to be reasonably good in the classroom, but it's certainly lower on the priority list when it comes to what is it that's going to get me tenure. And so people respond to incentives, and if you're a rookie professor, then you say, well, you have only got 24 hours in the day. Am I going to spend all that extra time on the teaching or am I going to spend it on, you know, on my research?

Mike Linton

Right. And you get credit when you like, when you create this new class, I would assume all kinds of other B schools are like, how can I get this class for me or my school? And like, we want to make classes like this. Is that happening or not? Yeah, I've had a number of.

Dan McCarthy

First, I've got guest lecturing and multiple other guest lecturing from multiple other universities. And you have this CLV case study on blue apron that it's been used all over the place. So it's this case that was co written with Eric Schwartz, typically to make a wholesale pivot towards ClV. My course is now going to be on CLV. That typically.

Again, that's a pretty heavy lift. Yeah, it's super heavy. But what I've seen a lot of people do is a lot of professors have asked me for CLV slides. And so they'll want, you know, that one or two lectures that are. Here's like this quick hit on CLV, you know, just give me the crash course in a couple lectures.

And so it's kind of like a condensed version of some of a subject. But making some traction into there, and hopefully a lot more things will make traction. Hey, Dan, can we talk about whether it's blue apron or anything else, an example of CLV in practice, like a case study, if you can share it, and also particularly where the case study showed a different outcome than the pure financials. You were just looking at the income of the balance sheet. Whatever you want to say.

Yeah. So blue apron and Wayfair are probably the two examples that I'm the most famous or infamous for. I'm going to go with famous, Dan. Famous, yeah. But, yeah, I'd say the most recent fun one was Warby Parker.

So I don't know if you'd have a preference for one or you tell. Me what you think is the most fun, interesting one and we'll go with that. I'll go with Warby Parker just because it's newer and, you know, again, wait. Let me put on my glasses for the warby Parker thing. I've got my warby Parker glasses at home.

So first off, just wanted to say I love the company, obviously Wharton grown, but they're an example of a direct to consumer, digitally native vertical brand. And in some sense they were kind of one of the progenitors of that category. And I'm a big fan. But we had run the numbers on them before they went public. And to their credit, they put a lot of really good disclosures in their prospectus.

So we ate it all up. But there's just a whole slew of interesting things that kind of came out of that, like lessons learned. And I think generalizable things that are more broadly applicable than just warby Parker, for one. That was an example where we did find a pretty significant discrepancy between the valuation that we thought was fair and where they ended up trading. So we ran this model again.

The unit economics were good. We were inferring very healthy LTV to CAC, better than the average company within the set of companies that we've run analysis on at Theta. So better than average. But that doesn't mean that any price is fair. NCAC is customer acquisition costs for everybody.

Yes, sorry. No worries. LTV is lifetime value just for those. So, yeah. So for one, having good unit economics does not mean having a good valuation.

Valuation is a function of price. And at some price, even a company with astoundingly good unit economics will be overvalued. And you're talking stock price here now, right. What you're saying is even though this was a killer company and it looked like it was doing great, you could not get to the stock price valuation no matter what you did to the model based on all the data you had. Right.

We reached as far as we could. Yeah. I mean, the bottom line on the customers, you buy that first pair of glasses, the average amount that you spend on, it's about $180. And what they showed in their filings is that after that, if you take 1000 people that buy that first pair of glasses, about one four of them will buy within the next year, a fourth will buy the year after, a Fourth will buy the year after, and a fourth will buy the year after. And so there's this question then, well, I'm sensing a trend here.

It's going to go out some more years than that. But the question is, well, how many years? And we said, you know what, screw it. We're going to go out infinite Years. We'll just say these people are going to.

One Fourth of the cohort is just going to keep on going until the World. Yeah, until we're all gone and let's see what valuation that suggests. And we still couldn't get to the Market Valuation. So, yeah, so it's one of those circumstances where we like the company, we're rooting for them. Good unit economics.

We really played that up. But we said, you're not buying the stock. We're not getting there by like a factor of two. So it's not like, well, 50 versus 40. It's like 50 versus 20.

Mike Linton

Wait, so now this Model, you cant even apply it to something like Reddit, can you? Because Reddit just came out and it hasnt made any money for 19 Years and its stock price goes boom on day one. How does this model apply to something like that? Or can it even, well, in theory. You could actually, I was just talking about this yesterday in a guest lecture, ironically, as part of a class where they wanted the CLV stuff, you have one model for engagement, and then the question is how much monetization you get per unit of engagement.

Dan McCarthy

And that's, I think that's the difficult factor. Yeah, I'd say the other difficult factor is a lot of people talk about upside to the valuation because of the data that's created being fed into llms who can be buyers of that data. And that's large language model, I think. Yeah, sorry, I'm just going with all that's right. I'm here to help without explanation.

And so what price do you put on that? So you've got the advertisers, you've got large language model companies like OpenAI. So, yeah, I think traditionally, and this is kind of consistent with their disclosures, they'll often provide measures like monthly active users, daily active users to help you get a sense of how much audience engagement there is. But there's that big question mark of how much money is the company going to get. And I think sometimes there can be more uncertainty in the ability in that modernization model.

That's probably how I'd go about it, but I just think that I'd have a much wider prediction interval for the stock price, be quite as confident in that modernization. So. Well put, Dan. Hey, so given all this empirical data, because if you look at CLV, you look at some of the other data that are available around marketing, where you can pretty much say a well run marketing company or with marketing in its center is in general going to be better than a company that doesn't have marketing in a like, business. How come there are still so many non believers about all this stuff out there where they still want to just put marketing as a cost line versus a growth item.

Yeah, I think it's in part language issues that I think marketing often tends to speak in one language, how they think about success and value creation. And I think oftentimes the finance department or the CFO, they're used to different language. They think in terms of net present value in project finance. And so when they see engagement measures and things like that, I think being able to go from that to this was the amount of value that was created or just some sort of a proxy for that, I think that they need some help kind of getting there. And so, you know, we'll often, I'm not sure that there's any like magic bullet to solve that communication issue.

But yeah, I'd say that a step in the right direction can be this customer lifetime value type of concept, because at least for one, first, all the historical measures they can directly tie to revenue and profit, and that's a good thing. The second thing is, you know, you're talking investments again, except the investment here is the customer, and you have the marginal costs of the customer to bring them in, and then you have the marginal benefit that you get in net present value terms after acquisition. So suddenly the CFO kind of hears all that. It's like, yeah, that's language I'm familiar with now, it's not language that I think some marketers are terribly comfortable with. But they should get comfortable with it, because we have a number of shows on why marketers should not use marketing jargon or try and convince everybody that they should become really great at brand awareness and consideration.

Mike Linton

Everything else, it's because none of the investors actually eat any of those measures. They eat the financial measures. And I do think marketers are partially responsible for being misunderstood because they're talking a language that requires huge translation instead of translating on the front end. I want to talk about, how do you get marketers better at this? I mean, we already talked about business school's responsibility here to maybe step up their game and evolve a lot on helping marketers think and approach things differently.

But how about when marketers are setting their objectives or their plans or communicating to their companies other than learning to speak finance, what advice would you give them?

Dan McCarthy

Start disclosing relevant measures to it, and disclose them to stakeholders where they'll care about the numbers. And I think what that can inevitably create is accountability. That suddenly you're like, whoa, if those numbers are kind of moving in the wrong direction now, you need to explain what might be going on. And I'd argue that's a step in the right direction. It's just creating that accountability mechanism for yourself to other adjacent organizations within the company that allow that dialogue to start taking place.

And it allows you to start speaking the language and thinking through what is the relationship between the stuff that I'm doing in terms of brain awareness and how that's manifesting in these outcome measures that everyone cares more about?

I'd start with the backward looking measures first. Just the no predictive model. Just give me all of the active customers, acquired retention measures, modernization measures, the sort of ingredients that you put them together and you project them and that gets you to measures of lifetime value. But because they're purely historic in nature, there's no second guessing the marketer about the model that was used. It's like these are just auditable facts.

Mike Linton

And the sales and profits that stick with them, depending on what you want to move around for CAC or anything else, those are auditable facts as well. So yeah, starting with that's helpful because no one's gonna be like, ah, that's B's. You know, I'm sure this is just based on some crazy model. Yeah, no, this is just the actual raw data. I think once everyone starts getting comfortable with that, that also helps build the proficiency to be able to start thinking about the forward looking.

Dan McCarthy

Yes, it really kind of motivates those measures, but it allows you to take a more gradual approach and kind of work the company into it as opposed to, you know, trying to sprint from day one. Can I flip this over to comp a little bit? Compensation, because a lot of marketing departments, they will pay for like actual marketing measures like brand awareness or acquisition, CAC, acquisition cost, you know, other stuff like that. And some of these things, they probably have some impact on, or pay for traffic, they probably have some impact on CLTV, but looked at individually, they may or may not work. Can you just tell us a little bit about how you might compensate a marketing department given all the different functions that could sit in there?

Yeah, it's hard, I think executive compensation having that being based in part on measures of customer value. I think you're on very solid ground when you move to the market department. I think it still merits a place on the compensation sheet, that it's one component of what triggers payment. Because again, that's typically, while I'll say this elevates the role of marketing is because it's the marketers who traditionally are managing the customer relationships and they're traditionally the owners of CLV. Well, if you're the owner of CLV, then you're accountable for ClV.

Yeah. And CLV is translating to sales and profit kind of immediately. Yeah. So it needs to be there. But I'm also the first to say, imagine that you're the performance marketer and you're only focused.

You're in the customer acquisition department. Well, the repeat purchases, a year later, you end up with these situations where you're like, well, that's not my. I wasn't involved with that, you know. Right. And it's yes or no.

Oftentimes you want to be bringing in the right quality customers, and so that definitely is important. So, again, it deserves a place, but they'll say, you know, I passed my ball off to the retention person, and now it's their responsibility. So if they drop the ball, are you saying that I'm going to not get paid? And so then they start getting upset. So, yeah, so, yeah, I'd say that there are certain measures that I think might be more aligned with the specific role of the people in question.

Like if you're a customer acquisition person. Yeah, I think that the weightings of the different decomposed customer behaviors might be different from you if you're the retention marketer. But, yeah, certainly CLV deserves a place on all of their compensation sheets. And, yeah, it's just kind of how you kind of determine the weights for some of the other, some of the other parts of it. I agree with this, and I.

Mike Linton

But I think one of the things to me is the company has to win the game. And if you had a great game, you can't just blame the defense or the offense for not doing their job. You have to collectively win the game. And the real game is. Is in the financials.

Dan McCarthy

That's why. Yeah. I mean, you hire a sales manager, and they get paid in part based on restricted stock units. And that's for public companies. That's a function of the stock price.

So you're very out of control of that. But no one disagrees with that. We all win together. We all lose together. So I think the same idea should apply to CLV, and in fact, it should apply at least that's even closer to what they do than arguably the rsus might be.

Mike Linton

They may argue that we're closing in on time, and if you have another case study you want to share, that'd be great. If not, I will go to the last question. I'm trying to think the best. Well, maybe if you wanted to hear the aftermath of the Warby Parker story. I would love to hear the aftermath of the war.

Dan McCarthy

And there's kind of interesting, this is interesting other question that I think deserves a place in the conversation, which is that of information disclosures, maybe a little on the one, a little on the other. We came out saying fair value is something like $22 a share. They started trading at 53. We're getting all these calls of, you're an idiot, you didn't value the growth options through the contact lenses and all that. But then promptly, within a few months, they just plummeted back down to earth and then fell to our price.

And fell below our price, actually. So we went back in and revisited the analysis, and we found that the fundamentals were relatively consistent with what we had inferred previously. So now we're relatively constructive on the valuation. So whereas before we were slightly bearish on the stock price, now I'd say we're slightly bullish, but it's within the fairway. I'd say just the other aspect.

This goes back to one of the issues that you inevitably start running into with CLV is conflict of interest problems. And the big conflict of interest problem when you're a public company is you don't want to make your. No one wants their baby to look bad. And for companies, they want their CLV to look as good as possible and they want their tax to be as low as possible. And so you have all these issues of, and I think this has held back the credibility of CLV to a large extent, is these companies, they start removing all of these costs, taking out the discount rate, they'll look to CAC and they define it in these very weird ways in the smallest possible way.

And Warby Parker, I would say there was a, some issues with sloppiness in their disclosures that we called out, and they actually had to restate their prospectus because of the issues that we pointed out. But they also were pretty aggressive on some of the definitions. And again, because there's no generally accepted accounting principles for how any of these measures should be defined, it's not like they're wrong in the sense that they could be sued. I'd say that none of these measures have any industry standard definition. So I think we need to work towards that because I think it's going to help build the credibility of these measures for the next.

Warby Parker. There you go. Here's a new class for you, Dan.

Mike Linton

So last question. It's two parter. You can take both parts, but you have to take at least one practical advice for our audience. We haven't discussed yet and or funniest story you can share on the air. Pick one or both.

Dan McCarthy

Funniest story in what category? Anything you want. Anything I want. Well, I'd say going back to the Wayfair example, that was truly surreal. But, yeah, we put out this analysis on Wayfair.

Bearish. And in that case, imagine you're this pipsqueak third year PhD student. You're there just trying to get a marketing publication to make this pivot to marketing. We posted the paper, and the very next day, this famous short seller started to tweet about it, saying it was the best, smartest piece of work they'd ever seen on Wayfair. And the stock price fell 10% in a single day.

I think it was like the biggest stock price decline in over a year and a half, and it just continued to tumble. And then it was featured on Jim Cramer's mad money, and we started getting all these angry, angry phone calls from sell side equity researchers. But, yeah, I just, I still remember this surreal. I mean, in retrospect, it was hilarious just having to go through that as a student, just trying to get an a. But you did probably get an a on this paper.

That may be a. Yeah, the funny thing was, we wrote this first version of it, and it used this dataset from this company that wanted to remain private. And we did this thought experiment, and the reviewers came back and they said, look, you're telling me this is like a method for corporate valuation for public companies. Give me public company data. We, Hampton hawed, went back, found Wayfair.

It was one of the first companies that we found that disclosed the right data, did up the analysis, and then that's what created Wayfair. But if the reviewers had said that first version was fine, Wayfair wouldn't have any Wayfair. I'm sure Wayfair is not sending you free products.

Mike Linton

Anything else you want to share with our listeners before we sign off? I would say, as you can tell, I get fired up about all this stuff. I love it. To the extent that you're on your own clv journey, please don't be a stranger. Very happy to help share resources, slides, other materials, and just help you along the way.

Dan McCarthy

Well, Dan, take my course. Yeah, it'll be.

Mike Linton

We'Ll put up some links for you on CMO confidential page if you want. Thank you, Dan, very much, and thanks to everyone for listening to CMO Confidential. If you are enjoying our show, hit the like button, share and subscribe and look for all of our shows on Spotify, Apple, the I hear everything network and YouTube, which include marketing, the battle between believers and non believers, the Budweiser case, how not to manage a socio political issue, what private equity really thinks about marketing and is the CMO position the hardest job in business? Hey all you marketers, stay safe out there. This is Mike Linton signing off for CMO confidential.