Allison Hartsoe: [00:01] This is the Customer Equity Accelerator. If you are a marketing executive who wants to deliver bottom-line impact by identifying and connecting with revenue generating customers, then this is the show for you. I'm your host, Allison Hartsoe, CEO of Ambition Data. Each week I bring you the leaders behind the customer-centric revolution who share their expert advice. Are you ready to accelerate? Then let's go!
Allison Hartsoe: [00:34] Welcome everyone. Today's show is about 2019 predictions and in this case predictions about corporate valuation. Uh, to help me discuss this very interesting topic is Dan McCarthy. Dan is the CO-founder and director of Data Equity Partners, which we also just call Feta, and he's also an assistant professor of marketing at Emory University. Dan, welcome to the show.
Dan McCarthy: [00:59] Hey, it's great to be with you again, Allison.
Allison Hartsoe: [01:01] Now I know you from the connection with a professor, Peter Fader at Wharton, but tell us a little bit about your background and how you got attached to corporate valuation as an interesting idea.
Dan McCarthy: [01:16] It really goes back about 12 years that I was at the Wharton School for my undergraduate part of the M and t program, and back in 2006 we were in the middle of the housing bubble and lots of financial engineering, and so I was lurking to the board and like many of my colleagues, I went off into finance, so I spent about six years working at a fundamentals-based hedge fund before seeing the light and coming back for a Ph.D. formally and Statistics, but also at the Wharton school and it was in the second year program that someone had said, I should really speak with the Fader that we really get along. I'm really glad that I made the trip up to the seventh floor to have that chat because really the rest is history. I kind of made a big pivot into marketing, focusing on predicting what customers will do using statistical models. And it was pretty shortly after that kind of converged on this topic of customer-based corporate valuation, which is really bringing together those predictive models for what customers will do that kind of inserting them within a corporate valuation use case. So in some sense, it was just bringing together all the topics that I've loved the most over the past 12 years.
Allison Hartsoe: [02:22] That concept of being able to understand what customers will do and related all the way back to the bottom line is something that we love in the data space because it's oftentimes very difficult to deal with your new venture at fit equity partners. Are you connecting the sea levels to Wall Street and helping them think about their data and the way they connect to Wall Street in a different way?
Dan McCarthy: [02:45] We've definitely been connecting them much more to their evaluations, and we've been also using the same models on behalf of the investors, primarily private equity firms, but we're also having a lot of discussions with play stage, VC firms, and with hedge funds. And so, certainly to the extent that we've been getting very strong traction both with, you know, the CEOs and the CFOs and the one side and with the investors on the other side, at some point of connection. Oftentimes when we are speaking with CPOs and CFOs, it's because they are in the middle of some sort of capital raise, either it's a around that they're raising or considering some sort of a strategic alternative, but obviously to the extent that this is really, really relevant, relevant enough that the investors that they're speaking to are, are paying for the same analysis is really important and potentially very helpful for them to have in their pitch to x instead try to paint a view of how much more they should be worth in the future.
Allison Hartsoe: [03:47] And I think that is exactly why this is a predictive episode. It’s not only are the models predictive, but you're also trying to shape the way Wall Street thinks about companies and investors. Think about companies. Would that be fair?
Dan McCarthy: [04:02] I think so. You know our goal really hope to just change the conversation on Wall Street and have everyone wake up a lot more than they have up to this point about the health of the customer and how important that is to the overall valuation firm. So what is the proper revenue multiple or multiple that accompanied should get. Well, it should be to a large extent, driven by future expectations of the modernization of active customers, and future acquisition growth, the company's retention curve. And to students of the course that I teach, I've Kinda gone through exercises where I've shown them examples of two hypothetical companies where literally the revenue trajectory is exactly the same, and the only thing that's different between them is the company's retention. And you can have some companies with great retention, others with much worse. Where their historical revenues look the same, but their forward-looking revenue outlook should be dramatically different and specifically it should be worse for the company with the worst retention, all those being equal. So that's sort of exercise, I just, I haven't seen it really be done to this extent before. So I think, you know, both Pete Fader and I were hoping to bring some real rigor and science to it, you know, by kind of doing this with many companies directly, you know, to kind of very directly change that conversation.
Allison Hartsoe: [05:20] And it seems obvious in a way. So I'm going to translate what you said a little bit for folks who don't speak models and don't really understand Wall Street terminology. Basically, the way I see it is companies should be rewarded for the quality of their customer base, and until now it's really been hidden. You know, if I come to Comcast and I don't get great service, and then I move on, um, if, if I have a choice to move on, then I'm just like one number in the game and Wall Street doesn't really acknowledge that. They don't look at the quality of the customer base. But if I stay with a company like our local ski resort, you know, I renew them every year. I don't go to another ski resort. I love this place. I come back again and again and again. Now they're not a public company, but the quality of their customer base is very loyal. There's a high retention rate. And so what we're really talking about here is how kind is a company to their customers and how does that translate to their bottom line, how much their customers love them back? And I think this is such a great concept for empowering or recognizing the power of customers in any business.
Dan McCarthy: [06:31] I think that's a, I couldn't have said it better myself.
Allison Hartsoe: [06:34] Well good.
Dan McCarthy: [06:36] I would say so. It's really interesting you bring up the example of being kind to the customers, and I think whether it's even the kind of valuation friendly to be very kind or less kind of, it's going to be a function of the company and the vertical that they operate in. And there could be some verticals, and actually, maybe Comcast is one of them where they're actually not being incentivized to be that kind of the customers because they know that the retention of customers is going to continue to be really good regardless of how poorly they treat the customers. It's unfortunate for us as customers of them, and I've experienced it firsthand, but I've also experienced it on the flip side, that if they're the only game in town, then I can't switch. Contrast that a certain much more competitive e-commerce verticals where I do have the ability to just very easily take my business elsewhere. You know, they're much more of a case could be made for being kind, especially to the highest value customers.
Allison Hartsoe: [07:33] So in a way, what we're saying is the more competition there is in the market, the more incentive there is for companies to have high-quality customer bases, which probably translate to kindness and the more incentive perhaps there is for Wall Street to look at a different way of valuing those businesses.
Dan McCarthy: [07:53] I think all those being equal, obviously to the extent that companies can personalize that service to different customer segments, but even kind of personalize the level of kindness that they don't know to optimize that around the value the customers. That's the sort of thing I think we should be seeing a lot more of. And I think to the point about customer-based corporate valuation, the next big question is how these firms can communicate that to the shareholders. And I think that's kind of a whole other challenge that we're now starting to develop some science around. But, uh, I think we're still very much in the first sentence there.
Allison Hartsoe: [08:28] Well, let's talk about some of those examples. I know you've done several different companies that you've looked at their public data and you've calculated how well they're retaining their customers. Um, what's a good story that you could share with us?
Dan McCarthy: [08:42] Yeah, I'd say one of the more recent ones was the comparison that I did between Blue Apron and actually a private company called emails. It's operating in a, in a very similar space. Essentially it was to say one, you know, imagine that we have two companies in terms of the service that's being provided to the end customer. They're similar, but the way they went about it was dramatically different. So they have very different business models and with the labor and you know, they were one of the first examples that I think really stood out in the mindset of the everyday public as a result of some of the work that I put together about their customer retention. You know, people could really appreciate the importance of that to the valuation story and what's happened to their stock price since the IPO. So really the story was more about looking at other companies and send the case of emails.
Dan McCarthy: [09:32] Essentially, what we saw was here's the company, they're smaller, but they're acquiring customers just as quickly, but most importantly their retention was dramatically higher. So whereas at Blue apron, their six months retention rate was 30 percent, which basically means the acquire a bunch of customers and roll forward the clock six months in 70 percent of those customers have churned out. At emails, it was dramatically higher. They had a six-month retention rate, I believe it was on the order of 80 percent or so. And so, just a world of difference, and granted, you know, they have a lot of customers that sign up for annual plans and so at the one year point they finally have the opportunity to turn into a bunch of them do, but their, their one year retention was still on the order of 45 percent, which was dramatically higher than the around 24 percent that the waiver and was doing.
Dan McCarthy: [10:27] So no matter how you cut it, it will retain these customers for a very, very, very long period of time. And on the customer acquisition cost side, they were spending dramatically less, less than half what blue apron was spending to acquire and each of their paying customers. So essentially, you know, we're starting to come to this, call it a report card where we take all of these kinds of key customer base KPIs and just put the company's head to head and along virtually all major dimensions, emails that come out ahead and it was kind of no wonder that they've been kind of thriving, you know, whereas we waiver, and I believe it was just yesterday that they're stuck for the first time ever fell below $1 share, which, uh, if it remains below that level, they may need to be less from the exchange that they're currently on.
Allison Hartsoe: [11:16] Which is just the reflection of what you've seen already. But now just finally playing out in Wall Street. So here was a great opportunity for wall street to perhaps you use different metrics or better metrics that looked at the quality of the customer base and really paid attention to, should this company have gone public in the first place. And when it does go public, what's the proper valuation for it? Would you have sent this company out through the IPO?
Dan McCarthy: [11:43] I would not have any. Even if I would have, I believe that they had very aggressively acquired customers in the six months leading up to the IPO and I believed that they were doing it to be able to say that they had over a million active customers as of their pre IPO filing. I think they were basically burning dollars to be able to hit that, what I call it, trophy metric. So I think there were certain things, even if they were to IPO, that I would have gone about it completely differently. Contrast that to a company like Stitch fix, you know, they've done a good job of maintaining the value to customers, and they showed very little evidence of gunning the metrics in a period of receiving their IPO.
Allison Hartsoe: [12:24] Talk a little bit more about gunning the metrics. Is this, is this something that's really driven by the venture capitalists or private equity firms or whoever is behind the company and they're trying to get to an exit by pushing the company through IPO?
Dan McCarthy: [12:40] I think that the venture capitalists are a part of it for sure. I think that oftentimes what their objective is with investments is to return the fund on one of them and they know kind of going into investments in 20 companies that most of those companies will probably flame out, and so what they're hoping for is to be able to get that one that is so successful that it makes up for the other 19 companies that will inevitably go down. And you know, so one of the big things that they'll focus on is kind of growth growth growth. How can we just grow as quickly as possible and if we do and the street-wear to reward that, they'd see a very high level of revenues and they'd see a very strong year on your revenue growth percentage and say, well typically, holding everything else equal, I should pay a higher revenue multiple for that company.
Dan McCarthy: [13:32] And so it basically creates this incentive to just grow the revenues as quickly as possible when some of these other considerations like customer retention, which obviously in we're showing are extremely important. I think they would acknowledge that those metrics are important, but they don't surface themselves quite as quickly. And so oftentimes they can kind of take a little bit of a backseat. And so I've heard firsthand some VC say things like customer retention it's important, we're going to solve some of those problems later. And uh, I'm not sure that's a problem that you can just solve later. I think that's a problem that should be top of the mind from the very beginning.
Allison Hartsoe: [14:09] Let's touch on that for a second because there's a key concept around customer lifetime value that the first customers you acquire are often the best customers you acquire. Is that, does that mean that you really can't solve this problem later? You've really , and you burned through any good customers already.
Dan McCarthy: [14:27] I've definitely seen that happen a lot. That I wouldn't claim to make that as a universal law, but I would say from the many analyses that I had done through my previous company, Zodiac, which I'd also co-founded with Pete Fader and through Seda, just over the life cycle of these firms. The value of these customers after you acquire them, does tend to go down as you move into a company's maturity, and oftentimes to the amount that you spent to acquire those customers tends to move up and typically that's the result I think of moving from cheaper marketing channels to more traditional marketing channels like paid advertising. So in general, I would definitely agree that later customers, they tend to be worthless. The thing that accompanies is ultimately trying to maximize is the total amount of customer value that they require every period and so there could be some circumstances where I'd be very happy to accept a lower CLV if it meant that I'm acquiring many, many, many more customers at that lower CLV as long as that CLV is very adequate. So I think oftentimes there's a dynamic like that that's a play that there's a bit more volume coming in the door, even if it's at a lower quality level, but kind of holding that aside, it does reinforce that point that the unit economics is something that is very important to get and it really shouldn't be left to later.
Allison Hartsoe: [15:47] And can you just give a quick definition of unit economics for folks who don't have any con background?
Dan McCarthy: [15:53] Yeah, I'd say it breaks down to the following five factors. Customer acquisitions, yes the first, how much am I spending to bring each new customer in the door? And then, uh, what is the volume of future customers that I expect to acquire in the future? And then the heart of it is customer retention. So how long do I expect to retain customers after I've acquired them? Then it's the order rate. So how many orders do I expect to get? Well, customers are lights, the basket size, which is how much spend is going to be associated with each of the orders. And then finally, the contribution margin, which is how much variable profitability can I expect from each of those incremental revenue dollars. So you bring all that together, and that's what creates the Internet health firm. And those factors, they can really play off against each other.
Dan McCarthy: [16:42] So oftentimes, for example, if you're willing to pay a higher CAC, your volume of future acquisitions will be higher as well. And at the same would hold true if you have pretty strict requirements about the sort of contribution margin that you would want to make on choir customers. Well if you hold it really strict, there's only going to be so many customers that are profitable and so, you typically that will also be inversely related to the volume of future acquisitions. So, you know, one thing that I've heard many people talk about is, you know, what is the good level of retention? And uh, yeah, typically it's at that point I said, all right, let's just kind of take a step back and let's look at these five factors and just analyze the net effect on those five factors as a whole. And that's, I think, what can kind of lead companies to the right answer.
Allison Hartsoe: [17:26] Got It. So there isn't a rule of thumb that says, Hey, if you have 60 percent retention or 30 percent at retention, that that is good. Obviously, if you had a 99 percent churn and one percent retention, that's probably universally bad, but there's a heavy gradiation in between.
Dan McCarthy: [17:46] You know, just kinda to play devil's advocate with myself. If you had a business that you're spending a dollar or a penny to acquire the customer and you're getting back thousands and thousands of contribution margin dollars on that first purchase, and then they never come back. Well, I'd run that business. That business, it'll have a very different risk profile. So it's going to be much more driven by its ability to continue to acquire customers like that. But again, you know, that's why it's really hard to have a hard and fast rule because there are five different factors and that means there are many different combinations that can be good or bad.
Allison Hartsoe: [18:22] Got it. Let's go back to some of your other examples. When we talked about Blue Apron, we touched on hello fresh for just a second. And then we also touched on stitch fix. Is there anything more you want to elaborate on those models or do you want to queue up another one?
Dan McCarthy: [18:35] Yeah, maybe just another point about stitch fix. As I had mentioned, they didn't seem to be gunning the numbers which I really respect them for and even though I wasn't able to run a full-blown model on them, I think it is fair to say that they do turn a profit on their customers. So there are more positive, and I think they were a great example of the company that made a decision to move into other categories, specifically men and plus size clothing. And when they did that, the CLVs of those customers weren't quite as high, and so they saw kind of a move down in their profitability, and there was a lot of angst about that. And the part of me felt like, you know, it is true, all those feed will you want higher CLVs. But I think that was a perfect example going back to this kind of five-point framework where I'd be happy to accept lower CLVs if the volume of future acquisitions was large enough as a result of that.
Dan McCarthy: [19:31] And the CLVs of the new people that I'm bringing in are still very positive, and you know, here again, if they didn't make that move into men and plus size clothing, those are whole sectors of the apparel market that would not have been adoptable. So essentially, they made the decision to, to address those markets and there will be some time where they don't have CLVs that are assigned. Hopefully, they can bring that up as they learn more about those customers and unleash their data science teams to analyze their data. But, uh, you know, again, I think CLV, it's the most important measure if I had to pick one, but you can't ignore the volume.
Allison Hartsoe: [20:10] Do you think, Dan, that companies like stitch fix are more successful because they're so close to not just to the data, but to what the connection is between the marketing data and the business data so that they really understand the engine of their business and therefore they're not swayed by what might be bad guidance from other key board members or other folks that influence a company?
Dan McCarthy: [20:39] I do, yeah. I think it's a really great point that especially with a company like Stitch fix, they have such visibility into the needs and preferences of their customers that other very well-intentioned companies that even may have very good data science departments. If they're very, very heavy on brick and mortar and they just don't have quite as much trackability of what their customers were doing. You know, those, those ladder companies just wouldn't be able to do what stitch fix is done. So yeah, I think the big thing that the stitch fix model provides to them is just the ability to personalize to the degree that hadn't been possible before. Part of it is because they have SME subscription offering, which means they're able to see everything about their customers and they're shipping to them directly, so they know their shipping address and because clothes that aren't liked are probably returned back to them and because they know in excruciating amount of detail about the clothes that are being shipped and returned into the features of the clothing, they can understand a lot more what those returns mean for the preferences of those customers, which allows them to ship out boxes that are more likely to be kept.
Dan McCarthy: [21:48] So that is an example of a business that can really be made extremely customer-centric.
Allison Hartsoe: [21:54] Yeah. They basically got their fingers on all the right metrics in order to make that happen. I get that. Alright, well let's talk about another example. Who else have you seen doing interesting calculations and connecting to Wall Street in the right way?
Dan McCarthy: [22:09] Another interesting example I'd say it might be just to kind of pick one farfetch. I know if you follow their IPO, but the IPO relatively recently and they're an online luxury marketplace. So you can think of them as kind of an eBay, but for very high-end goods. And I'll be the first to say I know nothing about fashion. So if there's a fashion that I like, if you were to ask my wife, it probably means that people should go short that immediately. But, just going purely by the customer metrics, I'd say, the thing that struck me the most when I was going through their pre IPO filing was this one chart that they put in there, which I've now come to lovingly coin the triple C chart, the c three chart for customer cohort chart. And it's basically cohort by cohort, what is the total amount of revenues that those customers had generated, and so you can see things like the 2015 cohort.
Dan McCarthy: [23:08] All the customers they acquired them to generate 100 million in revenues. How much revenues did that cohort generate in 2016, in 2017 and in 2018, and there's a lot of really good information there about that company's ability to retain their customers as you can kind of almost see from that flow of data. And so basically myself, Aval Restedwith and Pete Fader, we had run the numbers on far fetch and basically the model it's suggested, they have great repeat-ability. But the customers, they acquire a batch of customers and essentially what we saw was you'll see an initial drop-off in revenues and then it stabilizes that is still reasonably high level and then just goes totally flat and basically at that lower level those customers become something of an annuity which speaks to something that the company is doing right. There's a core segment of people in their customer base that really loves what they do, and they'll come back for multiple years, like five-plus years, which I’ve said a lot.
Dan McCarthy: [24:08] So there were some questions about the company's margin profile and you know right now they're unprofitable. But again, the idea behind having a business that has very strong retention is it's going to be much easier to generate what's called in finance operating Leverage, which is basically the ability to improve your margins as your revenue grows. Because essentially, once we kind of roll forwards the clock five years, most of this company's revenue will be coming from loyal customers who've been around for a while. And it may not require as much investment on far fetch as part to keep them around that they just kind of keep doing their thing and so those customers almost kind of become pure profit to the business. So I'd say, wow, there are some questions about their margin profile. I've admitted to feeling quite strongly about that, that they've really hit on something very good when it comes to revenue repeat-ability. And so our analysis, they concluded when we did our full-blown valuation of them, it was basically, that even though they're selling for a relatively expensive valuation, that one could justify that valuation on the basis of the health of their business. So again, it's not even necessarily saying that they're undervalued, but essentially that we could reach that valuation and it was primarily driven by the goodness of the customers they're bringing in the door.
Allison Hartsoe: [25:31] So good customers are more profitable because they're happier, they're not pulling on heavy returns or all these extra support things that the business has to provide like a call center or email questions because of they kind of know how it works. Is that fair to say?
Dan McCarthy: [25:49] That's right, yeah, it’s a, the other key element is you don't have to keep spending those customer acquisition dollars to bring them in the door, so even if their profitability remained exactly the same as the day they came in, well, you know, now you don't have to spend any of those marketing dollars and so, in theory, the idea would be at some point the company could kind of turn off their ad spend budget and they've got this book of business, it’s really strong and solid. It's going to be there for many years and all those dollars that they had been spending on ads before, suddenly it's gone, and so yeah, it just makes it that much easier to become a profitable company.
Allison Hartsoe: [26:25] Okay. I'm not going to recommend that to anyone listening to the show. I think it's pretty clear. You always need some advertising, some branding to get in the game, but I see what you mean about the book of the business and, and I thought it was really interesting when you said they became a totally flat annuity that basically, you know, they, they were so stable, they were just like the company could just count on that group of people who love them to come back again and again, and I think that's what every company is really trying to get to, is a large group of people that really loves them. But, but what was interesting in what you said was that that group was stable but not necessarily targeted for growth. It wasn't like they were saying, um, you're coming back again and again, and now we want you to buy more and more and more instead they seem to be satisfied with that. Is that right?
Dan McCarthy: [27:17] It is, yeah. So this was one of the other interesting things about the disclosures that Farfetch put in their pre IPO filing. You've given some information about the amount that they were spending on bringing customers in the door versus the amount that we're spending on what's called demand generation, which is essentially ad spend for repeat orders from customers that were already part of the customer base and an indication that would be potentially more troubling would be that they are spending lots and lots of money to keep genning up orders from their existing customers, but that's not what we saw. Yeah. I think that they had said something like 30 percent of their ad spend was earmarked for a demand gen from existing customers and to me that's a good sign because as you're saying, it basically means those customers are on autopilot, they're just buying on the platform, they like it, and they don't need to be constantly prodded to make that next purchase.
Allison Hartsoe: [28:12] Got It. That makes perfect sense. Well, Dan, these are fantastic examples and thank you for sharing links with me before the show. I'm going to put those in the show notes. We probably have about six different story links that people can dig into if they'd like to see a little bit more about these case studies and I want to go into one particular avenue here. We've been talking a lot about public companies. Are we pretty much saying that the same operations apply when companies are not yet public and is there more you can find out when they're not public because you know they're not so constrained with all the public going public rules or was there less?
Dan McCarthy: [28:56] It's a good question, and I say it alludes to one of the limitations of our work with public companies and that's primarily that if they're public, they're kind of straight jacket and the only analysis that we can do is on the disclosures that they decided to put it in their filings. So we're kind of beholden to these firms. It's a problem with private companies in contrast or maybe even with public companies, but where we're under a strict nondisclosure agreement, which we have done in the past, there certainly were able to get a richer set of data again. So the goldmine, the ideal source of data would just be just a raw transaction log, just who bought when and for how much and ideally also what was the contribution profitability of those dollars. If you had that and you've got a whole bunch of CRM data than we can paint a much, much richer picture of the health of the firm from the customer perspective and we can start talking about CLV by the category of first purchase and how that's evolved over time. It's just a level of depth that you would never see in public filings. So that's definitely the sort of analysis that we've done for private equity clients, and you know, it's just, it's something that if there is anyone who's interested in having this analysis to be done, it's good to know that those other sorts of analyses are possible. It's really just a question of the data that we have to be able to feel that analysis.
Allison Hartsoe: [30:24] How can people reach you if they want to get in touch and let's say they want to do an analysis with data equity partners. They’re so like, hey, tell me about the health of my business or thinking about going public. Um, What, what, how should they get in touch?
Dan McCarthy: [30:38] Uh, there are a few ways. One would be by email, email@example.com, but definitely also please connect by LinkedIn and Twitter. My twitter handle is a d underscore, MCC, ar, and on LinkedIn, if you were to just look up Daniel McCarthy, Emory, that should pull me up. So in addition to being able to reach me for good or for bad, I post a lot of content there. This is basically the topic I spend all of my time thinking about. So you know, to the extent that it's interesting to you and you might want to participate in the conversation, I'd love to be able to go back and forth with you over there.
Allison Hartsoe: [31:18] I can vouch for that because there are some really great topics in your feed. And what I love is that every time I post a comment, it's like you never sleep, you know, there's always some comment coming back from you like within 24 hours. So, um, Dan is definitely the guy to engage with if you're interested in this topic and you like these ideas and the models, so thank you for being so responsive.
Dan McCarthy: [31:44] If I'm up at odd hours, it's typically because I've got a 14-month-old baby at home. So in between, uh, putting her to sleep less of these days.
Allison Hartsoe: [31:56] Very nice. Very nice. Well, I want to summarize with a couple of predictions that I think came out of our conversation and, and you know, feel free to weigh in here or shape what I'm saying, but here's what I heard. The customer goodness is really quantifiable, and it's profitable, and businesses that are not paying attention to customer goodness in 2019 are setting themselves up for future troubles. Would you agree with that?
Dan McCarthy: [32:25] Yeah, that if you're not paying attention to these numbers, you're flying blind and that can be dangerous. And maybe you just happened to be doing everything right, but in all likelihood, there could be a lot of money that's being left on the table. You have no north star to be moving in the direction.
Allison Hartsoe: [32:40] That's a good way to call it. It really is a north star, and then I want to build on that too because we talked a lot about acquisition and so I want to say that companies in 2019 that are repeatedly spending heavily on acquisition over and over without regard to the existing customer base could also be a red flag because retention is really where it's at.
Dan McCarthy: [33:04] Yes, and especially if you see a company that the revenues are growing, but it's entirely due to customer acquisition. Maybe ongoing profitability of those customers after the acquisition is for a, that is a very big way.
Allison Hartsoe: [33:19] And that's, that's kind of where we get into, how much does your customer base love you. If they love you a lot your retention should be good and how well do you treat them. And you know that's, it’s actually not fair to say to put it all on just the customer. There can be a lot of factors that go into whether a company is able to hold on to its customer base or not. So we can't make it so one-sided. But in, in general, if you're treating people well and your operationally effective and you've, you know, your supply chain in your responses and everything else is firing well, that should be the right market or look at.
Dan McCarthy: [33:59] Yes. I say with the caveat that there is some variation across product categories. Categories just lend themselves more to repeat business than others do.
Allison Hartsoe: [34:08] The mattress example, right? I mean, what's my retention on, on buying a mattress? It might be 10 years long.
Dan McCarthy: [34:15] Exactly. Yeah. So that point, you know, the owners could be unaccompanied and find ways to supplement the revenue stream. So there could be additional Biomed demands that could be uniquely satisfied by the mattress company. But uh, you know, ultimately, it may not be the fault of the company itself, but it's just not going to lend itself to well, to do a whole lot of repeat orders relative say selling books.
Allison Hartsoe: [34:37] I love it how, you know, it's, it's just classic data. It always just, it depends.
Dan McCarthy: [34:43] Yeah. But the key is to be concrete with when it depends, not just the, throw up the arms like the economists oftentimes do.
Allison Hartsoe: [34:52] And I want to pull out one more thing in our predictions summary, and this is what you were saying around stitch fix this concept that the, when the data science team really has a lock on the important metrics, they know the business, they know the customer, and they can execute smart marketing behind it. That companies that imitate that kind of data science-driven strategy, uh, where the tip of the spear is really about a customer lifetime value unit economic metrics. Those are the companies that stand to succeed the most in 2019. Would you agree?
Dan McCarthy: [35:32] I’d say that they would stand to succeed in 2019. Yes.
Allison Hartsoe: [35:33] Good. Good. Dan, thank you so much for being on the show today. It's always a pleasure to have you on and to, to pick your brain and all the amazing concepts that you put forward about modeling and Wall Street. It's such an interesting space. Thank you for being here.
Dan McCarthy: [35:49] I really appreciate your having me and cheers to have a wonderful 2019 for everyone who's listening to the show.
Allison Hartsoe: [35:54] Yes, cheers. Remember everyone, when you use your data effectively, you can build customer equity. That's the customer goodness. This is not magic. It's just a very specific journey that you can follow to get resolved.
Allison Hartsoe: [36:10] Thank you for joining today's show. This is your host, Allison Hartsoe, and I have two gifts for you. First, I've written a guide for the customer centric CMO, which contains some of the best ideas from this podcast, and you can receive it right now. Simply text, ambitiondata, one word to, three, one, nine, nine, six, (31996) and after you get that white paper, you'll have the option for the second gift, which is to receive The Signal. Once a month. I put together a list of three to five things I've seen that represent customer equity signal not noise, and believe me, there's a lot of noise out there. Things I include could be smart tools. I've run across, articles I've shared cool statistics, or people and companies I think are making amazing progress as they build customer equity. I hope you enjoy the CMO guide and The Signal. See you next week on the Customer Equity Accelerator.
Key Concepts: Customer Lifetime Value, Marketing, Digital Data, Customer Centricity, Long-Term Customer Value, Marketing Leaders, Analytics, Creativity, Product Development, Audience Research
Who Should Listen: CAOs, CCOs, CSOs, CDOs, Digital Marketers, Business Analysts, C-suite professionals, Entrepreneurs, eCommerce, Data Scientists, Analysts, CMOs, Customer Insights Leaders, CX Analysts, Data Services Leaders, Data Insights Leaders, SVPs or VPs of Marketing or Digital Marketing, SVPs or VPs of Customer Success, Customer Advocates, Product Managers, Product Developers