Customer Centricity: The Art of Picking Favorites

   

Drew: Hello, Renegade Marketers! If this is your first time listening, welcome, and if you're a regular listener, welcome back. Before I present today's episode, I am beyond thrilled to announce that our second in-person CMO Super Huddle is happening November 6th and 7th, 2025. In Palo Alto last year, we brought together 101 marketing leaders for a day of sharing, caring, and daring each other to greatness, and we're doing it again! Same venue, same energy, same ambition to challenge convention, with an added half-day strategy lab exclusively for marketing leaders. We're also excited to have TrustRadius and Boomerang as founding sponsors for this event. Early Bird tickets are now available at cmohuddles.com. You can even see a video there of what we did last year. Grab yours before they're gone. I promise you we will sell out, and it's going to be flocking awesomer!

You're about to listen to a Career Huddle where our flocking awesome community, CMO Huddles, gets exclusive access to the authors of some of the world's best-selling business books. At this huddle, we're joined by Peter Fader, professor at the Wharton School of the University of Pennsylvania and co-author of The Customer Centricity Playbook. He challenges how companies measure customer value, urging a shift from averages and CPA to customer lifetime value. He explains why not all customers are created equal, how to identify the ones to lean into, and how these insights shape marketing strategy and valuation. If you like what you hear, please subscribe to the podcast and leave a review. You'll be supporting our quest to be the number one B2B marketing podcast. All right, let's dive in.

Narrator: Welcome to Renegade Marketers Unite, possibly the best weekly podcast for CMOs and everyone else looking for innovative ways to transform their brand, drive demand, and just plain cut through, proving that B2B does not mean boring to business. Here's your host and Chief Marketing Renegade, Drew Neisser.

Drew: Hello, huddlers. I'm delighted to welcome Professor Peter Fader to today's Career Huddle. Peter is the Francis and Pei-Yuan Chai—and I'm blowing that pronunciation—Professor of Marketing at the Wharton School of the University of Pennsylvania. He's co-author of The Customer Centricity Playbook and co-founder of Theta Equity Partners. His latest book, The Customer Base Audit, which I just happened to have right here—here, look at this right there, look at that hard copy—got a copy right here. The Customer Base Audit: The First Step on the Journey to Customer Centricity provides a framework for truly understanding your customers' buying behaviors and the health of your overall customer base. So Peter, first of all, welcome. I hope you had a good reunion weekend. It was beautiful in Philly most of the time. I loved it—boy, Penn looks great.

Peter: Yeah, sorry we didn't get a chance to get together. It's just nuts when we—because we have reunion and graduation. So you'd think the school would be smart to space them out. There's only so many hotel rooms, so the whole world converges on—and for me as a professor, it's just glorious. So I had fun, even if I couldn't get a chance to meet you and countless others.

Drew: Oh my gosh, yeah. No, it's really something special. And for those of you who've never been to a Penn reunion, one of the remarkable things that they do is they do a march of the classes, which is like this, where they start with folks that graduated literally 80 years ago—and they had one there—and they work their way back in five-year increments, all the way to present-day graduates. And it's quite a thing to watch, a wondrous thing. So anyway, importantly, Peter, we've got some B2B CMOs here, a lot more in the audience for videos and podcasts. I want to make sure that we convince them that there's a really good reason for them to stay. So let's give them three things right off the top of your head that they may misunderstand or typically misunderstand about their customers. Just give me the bullet points, and then we'll go through them one at a time.

Peter: I love it. Love it. First is one you kind of understand at a visceral level, but you don't really understand it. There's—say all your customers—they're not created equal. They're wildly different from each other, and it's essential for you to understand the nature of those differences, the financial value of them, which ones are worth leaning into and which ones are worth leaving alone. So part of it is just the differences. That leads to thing number two, which is not only our ability, but the necessity—the competitive imperative—for us to measure those differences in dollars and cents. As much as I love Net Promoter Score, it's not enough just to say, "Oh, that's a promoter. That's a detractor." We want to basically say, what's the net present value of all the profits we're going to make from this customer or that? And then thing number three is that too often B2B people kind of silo themselves. And if I ever start giving B2C examples, they go, "Well, that's B2C. That's not our world." Shut up, man. There's just so much that you can learn from seemingly unrelated business models, industries, customer types. I just—you don't want people to be just open-minded and kind of basically say, what can we adopt? All right, there are some idiosyncrasies. We get it, but there's actually more overlap than you might think.

Drew: Okay, great. Those are perfect. Let's go through them one at a time. So I think inherently B2B CMOs understand the notion that all customers are not created equal, but talk a little bit about what in your world, when you do these audits—and if you've done it right—what kinds of differences are you looking at?

Peter: So you all believe in the 80-20 thing, and it's largely true that most of your customers don't bring much value to you, and then there's this relatively small but incredibly profitable portion. And so you have to understand that. You have to understand that that's kind of a law of nature. So the fact that most of your customers are—I mean, I don't want to get all technical with you, but I do have to share this term—most of your customers are transients. They don't stay that long, they don't buy that much from you. And then you go beating yourself up about it, saying, "You know, why don't they love us?" Or sometimes, especially if they're a really big enterprise, and you're saying, "Man, they have incredible capacity. We got to do whatever it takes to win them over." But it could be that for many, many of your customers, it's purely transactional. They give you money. You give them a thing. It's a fair deal. Leave me alone. Most of your customers don't want to have a relationship with you. And in marketing, we love to talk about dating and marriage and all that kind of stuff. But for most of our customers, they don't even think about themselves as our customers. So we just have to kind of grow up and get past a lot of the romantic notions of marketing and just view it in this kind of cold, hard way that some of them are just—they're just always going to be like that, and others, the ones who are going to go through the gates of hell to be with us, we just need to really spend a disproportionate amount of time focusing on them, saying, "What makes them different? How do we acquire more like them?" As opposed to, "How do we turn the meh ones into awesome ones," which is really hard to do.

Drew: Right, we're just not gonna—I mean, if that's who they are, there's not much you can do about it. And it makes sense. And I do want to come back to the other part of this—well, having segmented into, if they're not, they're "hurrahs," we'll find a way to make sure that we talk about what it means to invest in them. But let's go to the second point, which is the analytics. And really you mentioned that they're not created equal, and from a competitive standpoint, you need to understand net present value. Let's dive into that a little bit.

Peter: I sure hope we will. This is what I do for a living. I'm the customer lifetime value guy. I do more to kind of push that concept and to bring it to life than anyone on the planet. So you see all the academic stuff behind me. So, you know, dozens and dozens of articles about, "Here's how you calculate customer lifetime value for this kind of company or that kind of company, for this kind of data structure, for that kind of data structure." And then all these books about, "How do we leverage it?" And it's a real interesting love-hate relationship with B2B firms, because on one hand, again, they get this. They understand that you just know which clients are going to be the good ones. So they say, "We don't really need to quantify that." Or, "Our business is constantly changing. There's the competitive forces, the changes in technology, changes in the macro economy—all that stuff hits us really hard. So as soon as we think we have that value down, it changes. So let's not even bother calculating it." No, no, we got to calculate it. We can account for all that stuff, but we really want to be—and that's why we were both waving around The Customer Base Audit, super boring book, because it's all about an audit, and we want to find out just how much—we want to look at our customer base in a very standardized, regular, routine way to look for changes and to understand where the opportunities and the problems are, and we can do that in a hardcore financial dollars-and-cents way. And in fact—and ironically, it often works better in the B2B world, where you have really good transaction records. You don't have people paying cash. So it's much easier to do a lot of that tagging and tracking of clients, easier to do the calculations. Yet, very often people say, "Oh, that's fine for B2C, but we're a serious business." If you're a serious business, then you should be measuring it in a serious way.

Drew: Interesting. So what are the—what's the gap then? And because we know that this is easier, obviously, with software-as-a-service companies—they sell in a subscription, they know what that—probably they know how long companies are staying, if it's a monthly or an annual, and what their renewal rates are. And they can probably calculate this. What are they missing when you look at these, even in that scenario where they do have all the records, they know how long customers are staying, and they even know what percentage of them add a module or additional thing?

Peter: Yeah, I love it. You've set it up so perfectly. So let's start with the kind of simple enterprise SaaS, straight subscription type of thing, and then branch out from there. That is, no doubt, the easiest place to apply these lifetime value models, because people—they buy on a very regular cadence, they spend pretty much the same amount of money each time. We have observable attrition, so we know when they go away—it's like they tell us, "We're canceling the contract now." So that's the easiest scenario. But even there, it's often going to get messed up, like very often, I'll hear companies trying to boast and say, "Well, you know, what's the lifetime value for our customers?" I say, "Yeah, but they're different from each other." So I want to know the distribution of lifetime value. I want to know, you know, are your customers pretty similar to each other, or are they wildly different? And very important, I want to know how that mix is changing as we acquire each new cohort of customers. So I do all these cohort analyses. That's not segmentation—we'll talk about that too. But I like to look—let's look at the clients we acquired in Q1 2019, versus Q2, versus Q3, and so on. And I want to know how the mix of customers is changing with those newer cohorts. They're the canaries in the coal mine. Are they as good as the older cohorts? Probably not. They're probably getting worse as we start scraping the barrel. But are they getting gradually worse? Are they getting much worse? So there's just, even in the simplest world—enterprise SaaS—there's just a lot of subtlety, nuance, and just important, actionable things that we can layer on top of that. And that's the easy one.

Drew: Before you go on to that, because there are some nuances there that I began to understand reading the book. So it's funny, when I look at the cohort analysis, you can't quite see this, but all the curves look like that. And so there's a group of people, right, that are high lifetime value, that are distinguished by something, right? And then there's a group that is low lifetime or however you look at these cohorts.

Peter: All right, Drew, show me the curve again. I'm gonna grade you on it. That's really important. See, that's not what it looks like. I mean, that's the basic shape, which is to say this is really important: that we acquire a bunch of clients, and then we're just going to watch them over time. We're going to watch them die off over time. That's brutal, but we're going to watch them turn away. But the way the curve really looks is it's downward sloping—duh—but what happens is it drops pretty quickly and then levels off surprisingly high. So the curve you drew was just kind of falling gradually, gradually, gradually to zero. But it's kind of a much more dramatic, quick drop, level off type thing. And the reason I want to emphasize this is because it reflects the point that you just raised: that we have some customers who are kind of flighty. They try it once, and it's not for them. They drop pretty quickly. Then you have those amazing customers who are going to stay with you forever, and they're going to turn very, very, very slowly. Understanding that mix is reflected directly in the nature of that curve, and I want to see how that curve is varying across the different cohorts. Is it starting to drop more seriously and so on? There are just tremendous insights from that, both in terms of how we manage the business, as well as how we financially value the business.

Drew: So my most important takeaway is the notion that you have a lifetime value customer average. Our average customer stays with us 4.4 years, and the value per customer, therefore, is annual times 4.4, and that's your lifetime value of the customer. And while that is a nice average to have, that's missing the opportunity, which is dividing it up and finding the eight-year people and the one-year people. And what are the commonalities of the eight-year people that you can exploit and take advantage of, and those people that are the one-year or the six-month or the one-month people, and not spending time necessarily if you can't identify their behavior.

Peter: I think this interview is over. Drew, you got it. We're done.

Drew: Well, we have more to cover, because that was just SaaS and those were the easy ones. So you were going to move into other industries and why this gets more complicated.

Peter: All right, so then we move to the next gradation, which would be if we have a portfolio of different kinds of services that we can sell to our customers. So, for instance, we just finished up a nice project with a Vietnamese business services company where they're selling accounting and HR and IT. And so there's a variety of different services. So each one of them is following the kind of straight curve you just showed. But it's much more interesting because we're watching them add and drop services to the portfolio. So we're asking basically four questions. Question one: how long will it be until you make any changes to your portfolio to add or drop something to your existing mix? Question two: when you do that, which services are you likely to add or drop? We just want to know what you're poised to do next. Number three: given the portfolio, the bundle you have at any one point in time, how much money are we making off of you at that time? And then number four, the ultimate question, the L in CLV or LTV: how long will it be until you drop everything? How long until, for whatever reason, you just say, "I'm done here"? So we're going to look at this kind of multi-service firm. And like I said, it could be a business services provider. It could be a financial services provider where you're opening up different kinds of accounts and loans. It could be your telecommunications firm where they're doing IT, and maybe they might even be providing security services and just other stuff, and you're just adding and dropping, and it's just much more complicated. But that's reality. There are many more businesses—many of the people on this session who are selling a portfolio and not just a single thing. So we have to understand all those dynamics there.

Drew: And is there a point where you can identify that there's a particular product within the portfolio that they are most loyal to—that is the sticky glue for the thing—and as long as they keep that, they keep the others? Is that part of this exercise?

Peter: That's such a huge part of the exercise. In fact, I'm so glad you raised it. I want to flip the whole conversation around that, because too often we look at the things that we sell—again, they could be services, they could be products, whatever they are—and we kind of line them up from the things that we sell the most of to the things that we sell the least of, and we say we really better look at the ones on top, because that's our bread and butter. Well, it turns out, in many cases—this is going to sound really ironic and paradoxical—the things that we sell the most of, we're going to sell disproportionately to a lot of those customers, a lot of the one-and-dones. But way down the list of the products and services that we sell, buried in the middle there or towards the bottom, will be that sticky glue, the things that really distinguish those high-value customers from the less valuable ones. So if we look at all the things we sell through the lens of what's the profitability of customers who buy that thing, we're going to find some services that pop and say, "Whoa, we never knew that this was the bait that lets us catch some of those best customers, or the glue that keeps them around." And so we need to be looking at the things we sell, not through the lens of how much we sell of those things, but the profitability of the customers who buy that thing. It's an easy thing to do, but it doesn't come naturally, and we just tend to be more volumetric-oriented than we are value-oriented.

Drew: Yeah, I don't know how many of the folks in our community actually have this data. I know they probably have certain customer satisfaction data. They have certain—they know the value per customer on aggregate, because they know how many customers they have, and they know how much revenue they have, so they can just divide that number, boom. But they're looking, and that's, I think, the most interesting part of all of this, which is, if you can divide this into, like, as I think you did, 10 different cohorts based simply on various axes, right?

Peter: Actually, I'm going to interrupt you for a second. I like the 10 thing, so we'll break them into deciles. Remember, we want to save the C word—this is important—for the time of acquisition. Save cohort for that. But we're going to look at segments. It's strata of the customer base based on your top 10% of profitability. Next, next, next—not cohorts. I mean, that's separate.

Drew: Deciles, right? So, but that way you can easily see in this curve, if this group of people are the most profitable, that would be, for example, a group. And so you're simply looking at that. And I wonder how many of the folks could actually get that data.

Peter: You all could have it. You have great data. You have really good transaction logs. There are so many firms out there that would just die to have the kind of data clarity that you do. Now, maybe you don't manage it well, maybe you don't have a proper CRM system or something like that. That's your fault. But you have the capabilities to have good data that a lot of the companies that we associate with being more data-oriented—either CPG firms or a quick service restaurant—you know, they got people paying cash. You got people where you can't identify who they are. You can do that, and there's just no excuse not to.

Drew: Okay, so we can wrap up these first three things that they might not be thinking about learning. Your third point was learning from B2C. And I'm curious in particular if there's a lesson or two that you've seen recently that you think B2B CMOs could really benefit from understanding.

Peter: Oh, sure thing. So you've talked about some of the startups that I've had. So the first one was a company called Zodiac, where we brought lifetime value to life. And we were completely agnostic, working with B2B and B2C, and products and services and big companies and small companies and US and international. And we sold that company to Nike in 2018, which was, of course, a wonderful exit. And you look at some of the things that Nike has done recently, and Nike hasn't been doing so well recently. And why is that? Well, my fault? Because what happened is—we did, I'm the guy to blame. Well, yeah, I mean, yes and no. I haven't had really anything to do with them since my non-compete expired a couple years ago. But they took these models and they ran with them, and they said, "Let's find out which channels of distribution tend to bring the least valuable customers, and let's not sell through those channels anymore." So for a while there, Nike stopped selling through Amazon. Yeah, they used our models, and they said Amazon customers tend to be less profitable. Why should we do that at all? So they kind of cut off Amazon, and that's what cost the last CEO, John Donahoe. That's what cost him his job. I mean, not that alone.

Drew: I mean, there was—it may be in the decision, but it felt like, and I've read a lot about that particular case where, you know, Nike was built athlete to athlete. They really built a great brand around athletes being athletes, and they had people embedded in various communities. They got rid of all that and said, "We're going to sell through the Nike.com website." They didn't take care of the retailers who were really their customers. And boy, did they open up the door for a couple of other brands that just ran right into it. "Hey, we care about you as individuals." So this is a little bit of an apocryphal story about, yeah, you can analyze all you want, but if you lose track of why your customers really care about you, you're screwed.

Peter: That's right. You get into this analysis paralysis thing. I get, you know, I hand you this CLV magic wand, but go with me, and then you're tempted to let that drive the business. So it's no longer "sell these kinds of products," "let's no longer sell through those kinds of channels." You make some of these black and white decisions, and again, you kind of lose sight of what brought you to the dance in the first place. I think BDRs can learn a lot from some of those kinds of stories. That as nice as it would be to see exactly where the different sources of value are, you have to be careful about overacting on that and cutting off your nose to spite your face, type thing. And it's a cautionary tale. It's playing out as we speak, and I want to make sure that people use these metrics and models but don't abuse them.

Drew: I think the number was they lost about $40 billion in business value - pretty big number. And I know they're trying to rebuild everything that they got them there in the last 18 months. And I don't know how that's paying off for them yet, because there is a lot of brand equity, so to speak, that they had some in the bank. We'll see if they are able to...

Peter: That's right. And by the way, if you think about it, and this goes back to Nike, sort of lets me expand from there. Nike is technically a B2B business. You know, Nike rarely sells direct, right? This is one of the things that we're trying to do. They're selling boxes of shoes to Foot Locker and Walmart, who are then selling, so they're a B2B2C business, just like a lot of other people here. So to their credit, they were trying to understand the C part so they could better manage the B2B part. So if I may, let me tell you now the opposite story, right? Another B2B2C that's been doing amazing things, another company that many of you are familiar with, and I've had the pleasure of working with, although people might not admit their relationship with this company. I'm talking about Allergan Aesthetics, the company...

Drew: As in the maker of Botox?

Peter: Exactly. Botox, Juvederm, CoolSculpting - so they're a B2B2C business that they're selling these things to the med spa, who then sell it to the patients. And sort of like the Nike story, they wanted to, through the patient relationship, help themselves better manage the B2B relationship with the med spa. And we did just an amazing, amazing project with them. It was really great, and this is one where, in fact, we have a whole white paper on it, and there's videos and things I can share. And it's just really great to see the way that they better align themselves with their B2B customers by understanding the mix of customers for each med spa. So does this med spa have a very heterogeneous mix, you know, mostly MEH, but a few awesome? Or are they kind of similar to each other, and therefore it should be a different way that they interact with those med spas? It's really interesting. Too often, some of the best B2B insights will be if we can get some visibility into who the second B is selling to and then helping us manage that B2B relationship more effectively, more accountably, and just more appropriately.

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Drew: We know that there are dangers in going - reading the data the wrong way. We know that there's also opportunity. If you can figure out what group of people are going to stay with you longer and why, then that's an obvious thing where there's an opportunity. But specifically, as you've worked with various companies, this analytics process that you go through, identifying lifetime value, segmenting customers into sort of various deciles, if you will - let's talk about the actions, or the things that you can do once you have this data.

Peter: Love it, love it, love it, love it. Yeah, because keep in mind, I'm just a nerdy academic. I just glorify the models. "Oh, it fits well, look at those forecasts." Well, that doesn't put money in the bank, and that's why I've started writing the books. In fact, the one that you mentioned, the first one that you mentioned, "The Customer Centricity Playbook" - and I'm not trying to push books, I'm just answering your question - and this is how to implement a winning strategy driven by customer lifetime value. So how do we do the kinds of things that we do naturally, but better? Acquisition, retention, development. So every company out there is acquiring new customers - duh. Every company out there is thinking carefully about, "Who should we give that discount to, to keep them around, and who should we say, 'take it or leave it'?" And every company is out there doing different kinds of cross-selling and upselling and getting those existing customers to try to buy more and to engage more deeply. So how do we do those kinds of things, but through the lens of lifetime value? And I could talk for days about it. So for instance, when it comes to acquisition, instead of just trying to acquire more customers more cheaply, let's instead of obsessing over the efficiency of customer acquisition, let's focus on the effectiveness of it. Let's be willing to dole out a few more shekels. Let's be willing to spend more money to acquire customers if we know we're acquiring those good ones. So let's view marketing as a value maximization function instead of a cost minimization function, which is all too often how we view it, and using lifetime value as the way to do that. And then likewise for these other tools as well. So I could give you 50 fun things to do with lifetime value. I haven't even gotten warmed up yet.

Drew: Well, I just want to sort of - could we just write a joint memo to every VC and PE firm out there that says to their CEOs and CMOs, "There are two metrics that I care about: CPA, cost per acquisition or cost per customer, right, and lifetime value"? Now that - but CPA is number one. Currently, your cost per acquisition is $1,232. I want you to reduce that by 10%. These are literally words that come out of the mouths of PE firms and things as they try to squeeze and get EBITDA down, because if they can decrease the cost per acquisition, they can increase their EBITDA, which is their third metric that matters.

Peter: And what I'm trying to do is to try to make lifetime value as visible, visceral, tangible as CPA. And if we can just have a more balanced way we approach things, where we're maximizing value while being cost conscious... Right now, it's just complete opposite. It's all just cost, cost, cost. The value is invisible to us, so let's not even think about it.

Drew: But help me understand this, because I can see this struggle with this. So CPA is a number that you can just - how many, how much we spent on marketing and sales last year. This is how much revenue we generated last year. We divide one by two, and now we have a cost per acquisition for sales and marketing, or we could just divide it by marketing, and then we have a different number for cost per acquisition. That seems like... And you can look back six months or nine months or 12 months, and you can get that number easily. Lifetime value is always a projection, and it's again, often it's just - there's one number. What you're saying is, no, there are multiple numbers. And there are numbers - there's a lifetime value within a cohort that's a lot higher, and if you know what those characteristics of that cohort are, then you can say, "Okay, this person that we just acquired is worth this lifetime value." So now you have a different cost per acquisition.

Peter: You're willing to spend a lot more for that one. Yeah, that's exactly right. I'm trying to - so again, for years and years, I've been developing the tools, and I go to people and say, "Hey, read these articles," or "Hey, here's a technical load," or a spreadsheet. Like, so what I've been trying to do now, in this weirdly meta way, is taking these models and SaaSify them so that we can put these models in the hands of executives so they can be calculating the lifetime values, acting on the lifetime values as easily, incredibly as they could act on the cost per acquisition. Let's just put equal weight on these things. So I'm spending a lot of time as an entrepreneur to just make the models as instantly accessible, so that you don't have to face this kind of trade-off.

Drew: And I just think, for the folks that are listening right now, when you think about your customers, can you imagine that there are clearly identifiable characteristics or behavior of customers that indicates that you can tell almost from day one, that indicates that this is going to be one that's going to fit in that cohort, that decile that has that really high value? And I just wonder, because this is not analysis that we talk about very much in CMO Huddles, and I wonder how hard it is to get at that information and really figure out what those segments are.

Peter: Yeah, I'm telling you, it's there. The raw data for it is there. It's just sitting there in the transaction logs. You have it. It's just a matter of squeezing the juice out of it. It's not that hard. Now, I'm not saying you should be running the lifetime value models yourself. That's my job, but I'm going to make them as accessible as possible, so that it really is no more difficult than calculating the CPA. The data is there, and too often what companies will do to try to distinguish the awesome from the MEH is they'll look at firm characteristics. You know, just how large is this firm? I don't want to do that in the same way in the B2C world, I don't want to look at demographics. I mean, I'm not against it, but there's usually much less signal than noise. When it comes to customer characteristics, we said before, what are some of the characteristics that really help you identify the MEH from the awesome? What are the first products that they're buying from you? What channels are you acquiring them through? What kinds of acquisition campaigns did you get them through? So very often, it's different kinds of acquisition characteristics that might be largely independent of the size or nature of the firm that's going to be indicative of who are the good lifetime value ones versus not. Once you get used to this, once it becomes more of a rinse and repeat thing, you realize it's pretty easy to do. It's just that they're muscles you've never exercised before, and that's my job, is to make you aware of those and to give you the training devices to let you build them up.

Drew: It's interesting, and I'm wondering - so a lot of folks have multi-modal attribution models, and they're trying to figure out what part of - was it the event? Was it the customer reviews? You know, what was - was it the first point, the last click, any of those things? But I do think in some ways, what you are talking about is that the method of acquisition, like, if I read about - this is consumer language, but if I go and read a Consumer Reports article on, I don't know, lawnmowers, and I decide to buy a lawnmower at that place, because I bought it, I got it from there, I come in with a high degree of confidence, and I'm going to project that confidence into my lawnmower versus I saw the ad on, you know, Golf Channel, right? And so I don't have any degree of confidence in that. So I could see from a marketing standpoint, obviously they would love to know the customers that came in this door or went through this process are the ones that had the highest value, right? Kind of attribution model, because now we're just - we're not, because the attribution model was basically trying to figure out, just how do I get more people in the funnel?

Peter: That's it. That's right, most of whom are there. Yeah, we want to attribute quality instead of quantity. I mean, it's that simple. It's not that big a leap. It's just people just haven't thought that way.

Drew: Another refinement layer of attribution. It's not just did we acquire them, it's did they ultimately match with our highest value customers, or our highest profit customers, or our highest whatever customer? And I mean, there is one factor in all of this, which I wonder, like domino customers. It could be a low value in terms of revenue. They could even be low value in terms of profit, but they bring in 10 because they're willing to do recommendations.

Peter: Let's talk about that, because that's a big part of the B2B space. So a lot of the things that we'll do beyond just, you know, buying and selling things, but the other relationship-enhancing things that we do, whether it's referrals, whether it's participation in trade shows, whether it's just other things that, let's say the sales reps would know about you that we don't necessarily tie to the transaction data, to the CLVs, and we can bring all that stuff together. Oh, it's just wonderful, and it's not that hard. It's just that companies just don't think of doing so.

Drew: Help me reconcile some of this, because I'm thinking about there's so much focus today on intent data and a scoring system. So if they look at the pricing page, that's an indication of intent. If they go to review sites, that's an indication of intent. If they register for a demo, that's a high indication of intent. What it isn't any indication of necessarily, is that they're going to be a high value customer.

Peter: You've said it, that's it. I want everyone just to complete that thought, which is, let's collect all of that upfront, pre-acquisition data. Let's not just tie it to conversions. Let's tie it to long run value.

Drew: I'm going to ask, how do you do that?

Peter: Well, we're going to do the intent type attribution model. It's just that the thing that we're going to attribute will be lifetime value instead of, you know, did we acquire you or not? Again, I'm going to give you the lifetime values. I'm going to look at all of our existing customers and say, what was their CLV, then we're going to work backwards, because we capture the data to know, you know, how did we acquire them? And we're going to fairly easily see what were the acquisition motions and characteristics that just tended to be associated with the higher value customers. The analytical demands on it are no different than the kinds of attribution you're doing now. It's just that we're attributing value instead of just mere conversion.

Drew: Well, you're trying to find correlations you may or may not have, right? And this is the part I think that makes this so hard, which is you talked earlier about that you didn't think demographics were necessarily a good thing, but you could discover, for example, in your analysis, that when the general manager comes in first, they have a higher lifetime value because now you have air cover or the purchasing manager comes in first, you have a higher lifetime value, right? You could discover that because in you probably don't know why. You have to figure out why. But this is really tricky stuff, because you could create a lot of correlations that may not be causations, right?

Peter: Yeah, yeah. And that's what—let's say take—oh so good Drew. That's why I want to take you back to doing the cohort level analysis. I want to do this cohort by cohort, and what we might find is that some characteristics pop for a given cohort, but then go away when we look at the next cohort of customers, suggesting to us that it was just some kind of, you know, random noise thing. So by looking at each tranche of customers that we've acquired and finding out what are the characteristics that consistently pop across them? Those are the ones that we really want to focus on. So demographics will come and go, but acquisition characteristics, as I've mentioned on many times, which product did you buy first? You know, what was the kind of campaign and so on, those things tend to be more enduring. That's why I really emphasize them. They're not as sexy. They might even be a little bit less actionable than, you know, other kinds of firm characteristics, but if they're the ones that are consistently moving the needle, you got to roll up your sleeves and figure out how to act on them.

Drew: Interesting. And going back to something you said earlier, which is so many purchases, and I think it's true in B2B are transactional. It is the rare—or that finding the ones who don't see this as transactional is an interesting part of this conversation. But I think the biggest takeaway for me in all of this is that we marketers do ourselves a disservice by simply accepting a cost per acquisition and a lifetime value average as gospel. And therefore every customer that comes in, this was the cost per acquisition. This is the lifetime projected value, end of story.

Peter: That's right, but even then, you know what, I'll still take that as step one by step zero is, if we're just obsessing over cost per acquisition, trying to minimize that, that's inexcusable, but that's most companies. So even if you give me that single LTV, that's a step in the right direction. And we could even talk about what would be, you know, interesting proxies for that. Okay, you know, point five, before we even calculate the LTV, maybe it's Net Promoter Score, maybe it's credit score. Maybe there might be just other things that we kind of have that we can tag and track that tend to be, you know, lightly correlated with LTV. So let's just kind of plug that in as a proxy, just to try to get used to moving in that direction. So while we get the better data and do some of the better analytics, so we can eventually plug in the proper CLV metrics, we can at least start to get used to doing this kind of value instead of cost type thing. Walk before you run. I'm fine with that.

Drew: How does win-loss analysis fit into this process, because that's a qualitative often that tries to be quantitative, but you know, it's post-acquisition interviews. What were the key rational reasons? Why did you end up going with this company over that company? Why'd you even consider them in the first place? Do you get in those kinds of win-loss analysis, do you get data points that can help in flesh out the LTV segmentation?

Peter: Totally. Oh, it's such a great point, Drew. Yes. So a lot of those factors that would go into the win-loss analysis are the same factors that we should then be using to slice and dice the CLVs once we get them. Likewise, if you think about a win-loss analysis, instead of saying, you know, we won this one, we lost that one, if we could just replace the ones with the values, how much value did we win here? How much potential value did we lose there? So we could use lifetime values just to do a slightly more refined win-loss analysis. So it's, you know, we're making it just much more financially oriented. Instead of, you know, you win some, you lose some. Let's quantify that.

Drew: So, all right, I'm thinking about another scenario. You're B2B, you're working with a multinational. You've got a proof of concept in place in the US, and one of the divisions, the value of that customer is $100,000 for the POC and so forth. If they take it on, the value might go to $500,000 and then if they expand it globally, it goes to, you know, $5 million or whatever. When you're trying to do cost per acquisition in those scenarios, I guess you're going back to and say this person who did the POC that is a multinational that you probably have other cases where you can sort of look at it and say, we're looking at this wrong. Is that the idea?

Peter: Exactly, yeah, you know. So whether you're doing it in a somewhat informal way, maybe even in Excel, or if you bring in some machine learning to help you sort that stuff out again. That's it. It's just good to see folks thinking along those lines. If we could just make what you just said kind of more rule than exception, life would be good. So it's just nudging folks in that direction.

Drew: All of this, from a marketer's standpoint, is we're talking about, are we targeting the right people? Are we using the right channels, and are we ultimately being measured against the right things? And this is the problem. Most of the marketers start from what they're being measured on, which is going to be cost per acquisition. And, you know, revenue pipeline, it's not even often there. It's net new revenue. It's not even existing revenue in B2B, you could—it's and so you end up just, it's just about pipeline.

Peter: Yeah, and I want to change it to lifetime value. And yeah, coming up with those metrics both internal—like, how are we going to evaluate and reward the salespeople—as well as externally. You know, let's say we're doing the lifetime value thing. We're in it for the long run. We're willing to spend more money to acquire more valuable customers. Then we've got to get the people in FP&A to buy into that. "Wait a minute, your costs are going way up. Prove to me that it's worth it." So using these—a lot of these metrics—for external purposes as well, to kind of justify some of these investments that we're making. That's a really big piece of it. Like, it opens the door to a topic we really haven't touched on, but I've been spending a lot of time on recently: PDF customer-based corporate valuation. So spending a lot of time these days working with private equity firms and investment banks saying, "You want to value that company? Let's do it from the bottom up. Let's do it from the customer level up," as opposed to just coming up with these make-believe multiples just because 12x. Yeah. So let's take your EBITDA, and let's decompose it into acquisition, retention, repeat purchase, and spend, because, you know, every dollar you make is coming from a customer. And so let's understand: where's the bottleneck? Is it that we're not acquiring as many as we used to? That they're staying as long? Not spending as much? So let's take a lot of the traditional financial metrics and then view them through this marketing lens, and we'll just do a better job of doing the finance things, not to mention the fact that we'll just build better alignment between marketing and finance. And I'm spending just a lot of time doing that sort of thing.

Drew: We do have a question from the audience. This says marketers in transition and looking at customer marketing roles at B2B tech companies. So the question is—it's a nuanced question of who is going to respond favorably to the kind of analyses that you're recommending, because you could come across, you could be talking to somebody, and they go, "Why are you talking about this level of analytics?" And they don't want to scare them off, but they know that there's some real value here. Real value here, particularly if we're talking about customer marketing.

Peter: Yeah, it comes right back to the point I was saying, because, yes, some of the stuff I'm saying can be scary to marketers. It is a bit more technical, it's more data-driven, it might be much more comfortable to the people in finance, right? So in many cases, I actually will start the conversation with finance. "I'm going to show you a way that we can forecast revenue with cash flow, you know, over long horizons, you know, more accurately with better diagnostic understanding." And then after I've convinced you of that, we can then take some of these same tools and help the kids in marketing figure out, you know, which emails to send to which prospect. So sometimes starting with finance is a way to show greater impact, greater credibility, and ultimately to then get more support as you try to use the same tools for marketing purposes.

Drew: And it feels like you don't—you're not in an interview. You're not going in with answers, but it's questions like, "Have you segmented your customers into, you know, into cohorts as you define it? Have you segmented this way, this way, and this way?" So let's put two—if we were writing the questions that the CMO could ask the CFO, what would the question be? Have you done what in terms of analytics?

Peter: Well, it's going to start with: which metrics should we be judged by? Again, if we want to create alignment within the organization, and if we want to create a narrative for our external stakeholders, what are the metrics that we should all be looking at? And as much as I'd love to glorify lifetime value, in many cases, it's the metrics one level below that: again, the churn rate, repeat purchasing rate, the cross-sell rate. So all of these things are interesting by themselves. They come together to give us lifetime value. But we need to figure out which of these behavioral, financially oriented metrics are the ones that we want to be judged by that we'd like our CEO and CFO to pay attention to. Again, I'm not going to criticize net promoter score, but that is just a, you know, "Would you recommend us?" as opposed to, you know, "Are you actually coaching?" So let's come up with some, you know, behavioral metrics that just can cast the right light on what we're doing, internally and externally.

Drew: I love it. All right. Well, we're running out of time here, but let's—and first, I want to thank you for your insights today. But before we wrap up, let's give them one more practical first step for B2B CMOs that they could take tomorrow to begin moving towards a more customer-centric approach to analyzing their business.

Peter: Sounds like a broken record. It starts with the data. It starts with the tagging and tracking the not only who bought what, but just a lot of the other stuff, like I said before, that, you know, the salespeople might naturally be looking at, but then, you know, the people in finance just—you know, they wouldn't care which campaign this person came in on. But they should. So it's just—I don't want to say I'm being a data hoarder in a way, and in fact, in some ways, I want to almost minimize the amount of data, but I want it to be the right kinds of metrics. Metrics that are going to be either drivers of customer lifetime value or explainers of customer lifetime value, and really spend our time, whether it's through formal analytical approaches or even just instinctively, trying to understand what those metrics are, whose responsibility they should be, and what actions we would take depending on how they reveal themselves.

Drew: Okay, so thank you for that. And how could people, if they wanted to read more or follow you somehow, where would they do that?

Peter: Sure hope they would. Well, first of all, I don't hide very well, so you can just Google my name. But also, I mentioned a couple of times this company that's helping bring lifetime value to life—company called Theta, theta-clv.com. So a lot of the work that we've done there—interesting mix of being more financially oriented with some just, you know, straight-up marketing-type stuff, some really nice case studies, some really nice best practices, and a few things that kind of dabble in this semi-technical—so it's well worth checking that out.

Drew: I love it. All right. Well, we appreciate you and the time that you spent with us. Thank you so much for being here.

Peter: My pleasure. Glad to huddle up with you.

 

Drew: If you're a B2B CMO and you want to hear more conversations like this one, find out if you qualify to join our community of sharing, caring, and daring CMOs at cmohuddles.com.

Show Credits

Renegade Marketers Unite is written and directed by Drew Neisser. Hey, that's me! This show is produced by Melissa Caffrey, Laura Parkyn, and Ishar Cuevas. The music is by the amazing Burns Twins and the intro Voice Over is Linda Cornelius. To find the transcripts of all episodes, suggest future guests, or learn more about B2B branding, CMO Huddles, or my CMO coaching service, check out renegade.com. I'm your host, Drew Neisser. And until next time, keep those Renegade thinking caps on and strong!