No More Churn! Customer Lifetime Value

Webinar

Learn about customer lifetime value (CLV), retention, and reducing churn for healthcare companies. Identify the right level of spend to find and retain patients.

Featuring

Theta

Description

Healthcare marketing often gets its direction from strategic mandates or awareness months for certain illnesses. Patients have complex visit patterns and shifting needs, so these shifts in focus often miss what patients want. They defect, or churn, to other providers.


How do other industries know so keenly what their customers are worth and how much to invest in acquiring and keeping them?


Daniel McCarthy, co-founder of ThetaCLV & marketing professor at Emory University, is a major reason why. His and Peter Fader's work in Customer Lifetime Value guide the methods you see at major organizations such as Shopify and Etsy.


What can healthcare leaders learn from this work?

  • How to build the financial case for patient acquisition and patient retention efforts
  • How to find which patients are most likely to churn and retain those populations
  • A deeper understanding of your health system's financial health

Daniel McCarthy

Co-founder of ThetaCLV,
Marketing Professor at Emory University
ThetaCLV

Theta

Chris Hemphill

VP, Applied AI & Growth
Actium Health

Michael Linnert

Michael Linnert

CEO
Actium Health

1

Transcript




Chris Hemphill:
Loading bar is complete. Hello, healthcare. Hello, LinkedIn. Hello, YouTube. However you're consuming this content, hello. If you're consuming it right now in the live setting or a little bit later, we are happy that you're interested in this subject and joining us.

Chris Hemphill:
What we're going to discuss today is, there's a lot of conversation around investing in the consumer, how to identify how much to invest in acquiring and retaining our consumers and patients. At the same time, there's talk of what can healthcare learn from other industries.

Chris Hemphill:
Customer lifetime value, CLV; set of metrics aimed at identifying value of relationships, identifying likelihood of retention versus turn. These are metrics that have been heavily embraced in so many other industries, but it's really apparent there's been some false starts in the past within healthcare, but, healthcare is really just catching up.

Chris Hemphill:
Hello to the person who just said hello to. Thank you.

Chris Hemphill:
So, to help with this thinking, to help bring a lot of this knowledge into healthcare, we've actually reached out to Daniel McCarthy who is cofounder of data CLV and also a marketing scientist and professor at Emory University. You didn't coin the term customer lifetime value, but a lot of the stuff that you've done, he and Peter Fader, who I encourage you to look up on YouTube and see some of his talks on lifetime value as well, but a lot of the things that you're seeing industry doing at companies like Shopify, Etsy, a lot of big industry is driven by a lot of the research that they put out together.

Chris Hemphill:
So, big history that we're going to get into a little bit later. But, Dan, I just wanted to give you a chance to say hello.

Dan McCarthy:
Yeah, thanks so much for having me. Great to be here. I'm looking forward to talking CLV and healthcare.

Chris Hemphill:
Fantastic. So, Dan works across many other industries including some healthcare background as well. But what we can gain from this conversation and learn here is the perspective of those industries and married in with healthcare.

Chris Hemphill:
To round out that healthcare angle, Mike Linnert, CEO of SymphonyRM, who's been leading and guiding our efforts since 2014 especially with big health systems such as Intermountain and even community health systems like Griffin Health, basically a wide range of healthcare background, to kind of take these broad industry learnings into healthcare related chunks that you might be able to go out and execute on today. But, before we get into it, Mike, I wanted to give you the chance to say hello too.

Michael Linnert:
Hey, good morning. I'm really excited to be a part of the conversation this morning. You know, when we started SymphonyRM the whole point was to help health systems unlock the lifetime value of the customer relationships that they had. A lot of times we're just focused on the next transaction, the next appointment, the next encounter when, really, there's an opportunity to focus on the full lifetime journey that you're going to have with your patients, with your members, with your customers. So, I couldn't be more excited to have Dan here to have the conversation this morning.

Chris Hemphill:
Appreciate that. Appreciate the intro and the [inaudible 00:03:27] shouting us out down in the chat. Keep that energy going. I'm loving seeing an international audience here. Dan and I are in Atlanta, Georgia, but we have people all the way from Qatar, California all joining. Keep the energy flowing. As different things come up, as different topics come, the reason we have Mike and Dan here is so that you can address your questions right away.

Chris Hemphill:
There's extensive research and publications, videos on YouTube and podcasts that you could listen to and watch and all that; but here, if you have questions, you're able to get them answered from the experts live. So, we're really excited about any kinds of questions or stories you might have on customer and patient valuation.

Dan McCarthy:
Yeah. Thanks for popping in [inaudible 00:04:14]. I love all the back and forth on social media. So, yeah, looking forward to having you part of the conversation.

Chris Hemphill:
All right. And thanks, Corinthia and thanks to our own Melayna. We're about to jump into it. So, let's get started here.

Chris Hemphill:
Dan, I love the journey that you've had from finance and statistics into marketing, bringing a lot of those quantitative efforts especially part of your background, even developing the company zodiac which eventually got sold to Nike. I'm just curious about the motivations that you've had migrating from this background into applying all these methods in marketing and some of the things that you're currently working on.

Dan McCarthy:
Yeah. So, a lot of the earlier work that I had done was basically, it stemmed from my background in finance. I graduated from Wharton in the school of engineering, but I was kind of a Wall Street person at heart.

Dan McCarthy:
I spent about six years working at a fundamental-based hedge fund. We were all about projecting our revenues; understanding competitive drivers; obviously, how revenue flows through into profitability and then using that to drive our estimate of how much firms are worth.

Dan McCarthy:
It was interesting, when I made the pivot into ... I went back from my PhD in statistics and pretty quickly ended up connecting with Pete Fader, who you mentioned. We really had kicked it off. One of the things that really drew me to what he focused on was a focus on predicting what customers will do.

Dan McCarthy:
There's this underlying accounting identity that every dollar of revenue that a company generates has to be coming from customers making purchases, at least transactional and subscription businesses. Even if they're not, then all the other revenues, probably ad revenue or something like that that's being driven off of engagement from users, to the extent that we have the ability to predict what users and customers will do that really kind of has to give us what revenues are.

Dan McCarthy:
It was kind of interesting. When you looked at the standard ways that people within marketing would try and motivate customer lifetime value, one of them was by establishing this link to corporate value. The way that they did it was basically by computing lifetime values for customers and then summing it up. It just didn't quite sit right with me because when you go over to the people over in the finance department, first, they've been thinking about valuation for like 50 years. I mean, for a really long amount of time. And they've really hammered out all the theory behind, like what is the fair valuation of a company and how can we think about that?

Dan McCarthy:
And so, rather than try and create this homebrewed marketing CLV-based solution, one of the first things I wanted to do is to basically take all these great models that we have to predict what customers will do, but then insert that back into the finance models. I had co-written two papers that basically did just that; laying out these models for subscription and on subscription firms and then creating this direct link to corporate valuation.

Dan McCarthy:
I can't stress the importance of having a link like that. I think a lot of times people in marketing, they'll kind of say, "Well, we want to improve lifetime value. And having a good LTV to CAC is important." I don't disagree. Yeah, it's certainly really important. But what really matters to a chief financial officer, to a CEO is, well, what does that mean for the value of my firm? There's this missing link there that we really need to establish, which is what we have established through how Pete and I now go about doing customer based corporate valuation. So, that was really kind of step one.

Dan McCarthy:
Now, as the marketer, you can say, well, if I can improve the retention of my future cohorts, or if I can do this initiative and it's going to improve my acquisitions by X and the retention of my users by Y, then this is the ultimate, like overall corporate valuation enhancement that we can see as a result of that. I can then compare that to how much I spent to engage in that activity and actually compute an ROI that a chief financial officer would respect. Yeah, so that was kind of a lot of the early work.

Dan McCarthy:
These days, I've been spending more time thinking about how we can improve the models that we use, be able to use them in settings that we hadn't done before and then move to other data sources.

Dan McCarthy:
A lot of the early work was, assuming that the only data source we had available was either ... Like, all the granular transactional data, assuming that you're working for a firm, or on the other side, that you're this outside investor who's looking at SEC disclosures. But there's a lot of situations where you're somewhere in the middle; either you have some granular transaction data and then some aggregate statistics about the broader population, or it's good but you've got some missing or censoring issues. And so, being able to accommodate these other settings where the data is not quite perfect, it's really important. So, I've been spending a lot of time with that.

Dan McCarthy:
And then the final piece has been just moving from pure prediction to impact. One of the big struggles within the academic marketing community about a lot of the early work has been we can make these forecasts of what customers will do, but there's this implicit assumption that basically the status quo that had been in place will continue.

Dan McCarthy:
And wat we want to know as marketers is, well, I want to change the status quo. I want to do this thing and have it create value in a way that we haven't seen before. And so, to do that, you need to understand the causal impact of those actions. And it's a very different toolkit that's often used to be able to establish that.

Dan McCarthy:
I have three papers that are currently in varying stages of the academic publication process that are essentially using these tools from the, they call the observational causal inference toolkit to establish the impact of things on your customer purchase behavior.

Chris Hemphill:
That's exciting to hear. It's exciting to hear, like if I could put into two broad domains valuation, which would be identifying the value of a firm or some group of consumers or patients and being able to help. A lot of the gap in marketing, a lot of the reason why it's hard for marketing teams to grow or budgets to expand is because there's a lack of that communication and shared language with finance. It sounds like a lot of this work helps link CLV, customer lifetime value, to things that are going to matter to a financier, which is going to be a huge part of this conversation. I'm really happy to have you talk about breaking down that barrier.

Chris Hemphill:
And then the impact questions around, okay, so what are the actions that we should be taking? Based on some of these metrics, how should we be directing our spend and focus as marketers? So, that's a really exciting branch that you've laid out there.

Chris Hemphill:
Mike, it looked like you were about to say something?

Michael Linnert:
Oh, I'm always about to say something. Hey, Dan, can you talk maybe for a second about some of the work you've done and maybe if you can share just by industry or by ... what are examples of customer lifetime values and what do people do different based on knowing them? What actions fall out of knowing a customer lifetime value?

Dan McCarthy:
Broadly speaking, they can fall in a few different buckets. If you're working for a company itself, so this is kind of putting on my Theta hat. Theta, as Chris had mentioned, is the latest company that I co-founded with Pete. If we're working on behalf of a company, one of the first things that often will fall out of our analysis is basically how they should rejigger their customer acquisition budget.

Dan McCarthy:
I think one of the first keys that we like to establish is there's no one CLV. Every customer will have a different CLV. And so, we really want to, instead of ignoring those differences, we want to really celebrate them.

Dan McCarthy:
Different customers have different values, and they're coming in through different acquisition channels and they're being serviced in different ways by different people. And so, we want to take all those things that we can segment the customer base through and basically use them to our advantage and understand, like, well, how does customer value vary as a function of those things?

Dan McCarthy:
One of the things we'll often find when we first run an analysis like this is the customers that you're acquiring through all these different acquisition channels will have potentially significantly different values. And so, the quality of the long-term quality of those customers will be very different depending on where you got them from.

Dan McCarthy:
We've got many examples of this. One of them was there was an engagement not too long ago where we actually identified a couple of acquisition channels. One of which was Facebook, where the CAC was actually higher than our estimate of the value of the customers.

Dan McCarthy:
There are all sorts of issues associated with incrementality that you need to think through when you've got channels that look really, really profitable and the CLV to CAC is extremely good. But when you have channels for which CAC is higher than how much customers are worth after they've been acquired, you really don't have to think too hard about what you should do next, which is basically save that budget. Don't spend it on that channel. Either keep it for yourself or redirect it back into some of those other channels.

Dan McCarthy:
That's usually kind of playbook. Step number one is let's take all those other, whether it's acquisition channel or whether they came in through physical store or whether they made an online purchase, digital or not, let's look at the first product that they bought. Whatever it is, take all those things that we know and basically look at CLV by those things across acquisition cohorts and use that to decide how I should reallocate my budget. Should I be emphasizing stores more than online? Et cetera, et cetera.

Dan McCarthy:
The second broad category is customer retention. So, to the extent that you're sending out mailers and catalogs and things like that, that you have expense associated with them. The question becomes, where do I send the catalogs to? Under constraints, who should I not? Basically, one way you can think about that is, all right, the standard way is some sort of response model where you say, what is the probability that this type of customer is going to make a purchase after I send in the catalog?

Dan McCarthy:
Basically, going back to what you said at the very beginning of the session, it's a very now way of thinking about the world. And the question is, what's actually creating enduring value? And so, usually, you may be prone to getting an order from someone if you send them a catalog, but oftentimes you'll get a post promotional dip because you just pulled forward some of their demands. The question becomes, where did I actually get long-term value?

Dan McCarthy:
And so, usually we'll run some sort of an experiment that's not dissimilar from what you would do with a properly implemented response model, but we'll wait until the dust settles. We'll compute the CLV of the customer before we send out the catalogs and then compute it again after the dust is settled after we sent out the catalogs and compare the two, and then just look and see where are we getting lift in CLV?

Dan McCarthy:
Yes, I know that's a pretty specific example, but broadly speaking, acquisition and retention are the two big ones. Obviously, I'd be remiss if I didn't mention the other form of acquisition, which is company acquisition. At Theta that's what we're all about, is we'll help post acquisition as well, but we actually help PE firms think through whether they should acquire whole companies.

Dan McCarthy:
You can apply the same way of thinking about the world, but you're taking it one level up to the level of overall companies as opposed to how you can manage the customers within them.

Chris Hemphill:
Thank you. I got a question from the audience, from Steve Wood, that I think will help lay out the unifying principles or the basics on where you come from a CLV perspective. So, just in general, factors that are important in establishing customer lifetime value, what are the considerations that you would take there?

Dan McCarthy:
Biggest one of watch what they do, not what they say. We're all about actually looking at their monetary, basically looking at their actual purchase behavior and having that be one of the big things that we'll look to glean from.

Dan McCarthy:
A lot of people, they'll focus on demographics and psychographics and things like that. It's not to diminish the importance of those things, but you have a lot of people that they fall within the same persona bucket but have dramatically different values.

Dan McCarthy:
And so, really, the thing that we want to emphasize is when you actually look at how people spend, or in this case, engaged with the healthcare system or whatever service it is that we're talking about, how is that varying across the customers? And if you have the ability to observe those customers for a long enough period of time across a large enough group of customers, you'll do a very good job at being able to predict what they'll do in the future. You'll probably get 90% of the way there just by squeezing all the juice that you can out of that behavioral data.

Dan McCarthy:
If you want to layer in the other data as well, that's great, but oftentimes it's somewhat secondary in importance and is a bit duplicative when you have the behavioral data as well.

Dan McCarthy:
Where the demographic data can become more valuable is when you move to customers that you have very little transactional data for. Because it's as if someone just showed up in the system and you said, "All right, here I am." You might have seen one purchase, but that's it. And so there, it becomes trickier. We'll spend a lot of time basically thinking about how we can best marry the demographic or whatever information we have about the young customers with the trends that we can see across the customers, leveraging what we know about the older ones. It's probably more than you wanted to know, but that's generally how we think about it.

Chris Hemphill:
Actually, it's a really powerful answer because if you look at the bunch of different competing thoughts out there, some will say plug a bunch of demographic or variable factors into a machine learning model and see what that comes up with. But your point is, is that by looking at these behaviors such as frequency of purchase and transactions and things like that, values of transactions, you can get a big portion of the way there without having to make a ton of those ... You start squeezing more juice out of the lemon when you add some of those other factors, but you're 90% of the way there based on the behavioral approach.

Dan McCarthy:
Yeah, we're not averse to [ML 00:20:34]. Certainly, I'm very familiar with those methods. We'll tend to use them after the fact. Explaining the variation and CLV is the function of this very large feature set, and it speaks to this philosophical question of, when is machine learning really, really useful? It's most useful when you have label data, you have your outcome of interest and it's clearly labeled and you have this really, really large set of X variables, all the different features that you have for each person.

Dan McCarthy:
For one, there's the issue that oftentimes you'll have a lot of missing data. And so, it just becomes a mess to be able to incorporate that full forest of Xs in your model. But even if you had a pretty clean set of Xs, when we're thinking about lifetime value, you don't actually have your Y variable. Unless the person has physically passed away, oftentimes you don't know whether that person is going to make another purchase in the future. The fact that we don't have a Y variable makes it more difficult to use those models at least straight out of the box.

Dan McCarthy:
Our methods, we explicitly account for and are perfectly fine with the fact that the data is what we call right censored. We haven't necessarily observed the full lifetime of customers, but we can still give you our estimate from them.

Chris Hemphill:
I think we probably have varying levels of mathematical background on the call, but basically when we say right censored, what we're really saying is that customer lifetime value, we don't know when that, especially in retail and without contracts. Within healthcare, most of the time we're not contractually obligated to go to the health system. So, we don't know when that term, when that relationship, when that retention ends, so it makes the calculations that much more difficult.

Dan McCarthy:
Yeah. Sorry. Thanks for keeping me on earth. Actually, the ironic or the nice thing is a lot of the models that we use, actually they have their origins in the actuarial sciences to predict physical mortality. These are the sort of models that may be more popular within the health sciences because of the prominent role of mortality there. Again, that's the same analog, someone hasn't died yet, and what you want to know is what is the likelihood that they'll pass away at different ages? We don't get to observe that, but we need to infer it.

Chris Hemphill:
When I started the conversation, I said, hey, healthcare is behind, healthcare needs to learn from other industries, but-

Dan McCarthy:
[crosstalk 00:23:19].

Chris Hemphill:
Yeah, a lot of these models are coming from healthcare, so it's kind of coming full circle so we need to catch up on [crosstalk 00:23:27].

Dan McCarthy:
Or at least insurance. But, yeah. Yeah.

Chris Hemphill:
A question that we had was there are organizations that are good at this and bad at this, there's organizations that had well performing methods that have led to great decisions and other approaches that that haven't worked out so well. Could you talk about the differences between those types of organizations or, more broadly, if you're going to CLV, the kinds of pitfalls that you should be aware of and avoid?

Dan McCarthy:
Yeah, it's not like you could just snap your finger and then just magically it all happens.

Dan McCarthy:
First, you need to be instrumented properly and you need to have the right culture in place. You need to be setup from an organizational standpoint to really be able to do this whole thing. It's one thing to say that we care about customer lifetime value, it's quite another to actually be able to measure it reliably. And you can't measure it unless you're you've got a well-functioning CRM system, you've got customers tagged reasonably well. Thankfully in the healthcare system, hopefully we should have reasonable customer identifiers. But even there, you might have some issues because of HIPAA compliance and privacy issues.

Dan McCarthy:
So, first, can we actually calculate customer lifetime value? Do we have the data to be able to do it? If you don't, then you have to invest in CRM systems, which can be quite expensive. That's just an investment that you need to make. Even if you have that in place, again one of the big things is ... you can estimate it, but how do you act on it?

Dan McCarthy:
And so, if you want to act on it intelligently, one of the things you need is some way to be able to run experiments. And experiments aren't, again, something that you can just snap your finger and say, "All right, we can do an experiment now." It's really tough especially if you want to have randomization to be able to, again, look at the data and be able to infer causal effects. Oftentimes, you need a separate experimentation platform which again entails expense. Now, there's companies that are making it easier and easier to be able to run experiments, but you'd really want to speak with those companies to be able to take that step.

Dan McCarthy:
If your company is organized along product lines as opposed to around key customer accounts and segments, it's just going to be a bit harder because those product managers are going to be territorial. They're going to care about, number one, they want to make sure that their specific product line is doing as well as they can even if that means cannibalizing other products within the same company's portfolio.

Dan McCarthy:
Again, when we move to thinking about it from the customer perspective, we care about the products but we only care about them to the extent that that portfolio of products can most enhance the overall value of customers to the firm. And so, yes, the products are kind of an ends to a mean and not a means unto itself.

Dan McCarthy:
So, yeah, again, that's something, either you're set up that way or you're not. If you're not, you might need to think about how you can restructure the organization to be able to do it.

Dan McCarthy:
You might be a marketing manager who really loves these ideas. If you don't have support from the top, then it's also going to be difficult. Having executives at the firm who have bought into this, that can be really important.

Dan McCarthy:
Those are a few of the issues that that we've seen as we've been doing this where you'll have people who like it, but for a number of very reasonable reasons, they're just not really able to see it through and actually be able to create value as a result of it.

Michael Linnert:
But, Dan, I might add that lifetime value done right drives engagement from the executive level. I'll give you an example of a lot of companies I've worked with in the past. For instance, if you come to the conclusion that a customer could potentially be worth $2000, well that fundamentally changes what you're willing to spend to acquire that customer. Once you have the customer, if you thought the customer could be worth $2000, you want to make sure you're doing the things to unlock that value.

Michael Linnert:
A lot of times, what I see, when the marketing group is able to lay out numbers and then go to the CFO, go to the CEO, and say, "Look, here are the hard dollars in terms of opportunity that we're leaving on the table by not engaging. Can we have the money to go engage?" It forces or creates opportunities for decision. But maybe even more powerfully, it forces and creates discussion around, is that the right calculation?

Michael Linnert:
I'll give an example. In healthcare, if someone is a fee-for-service patient, the things that drive value for the patient and the health system are making sure they're getting the services that they need, right? If someone is high risk for cancer, and by the way, last year, cancer diagnosis in the US was down by 50%. There are a lot of people right now walking around with advanced cancer that needs to be addressed, right? It is huge value for the health system to be proactively reaching out to the high-risks people and it's huge value for those people as well.

Michael Linnert:
On the flip side, in the value-based care model where we want people to stay healthy, we make money by keeping people healthy, there's lots of people with chronic conditions who've been putting off appointments. We need to get them in. If you don't take a lifetime value of things, well then, what you have is a list of people with chronic conditions. If you're able to take a lifetime value approach, you might say, "This list is worth $11 million to us because we need to get these things done."

Michael Linnert:
I'll stop there, but maybe, can you talk about how you see people use the numbers to actually change what they do and reallocate budgets?

Dan McCarthy:
Yes. Again, I think ... First, I fully agree. I think the key then is being able to ... This is oftentimes what we'll try and do first. We're working with a consulting firm that, we're doing a similar thing with two companies, but it's basically to do a pilot where it's small scale and limited risk than for the firm so you don't necessarily need to roll out the full thing. You can just do an on-trial basis, and that can allow you to get the data that you need to be able to bring it to the executives of the firm and say, "Look, this is really, really promising. We should invest more in this." So, pilots are really useful in that way as a trial step.

Dan McCarthy:
I think, again, the nice thing about putting a monetary value on customers and being able to think about the world in ways that the finance department understands, is it makes a lot of the other steps a little bit easier.

Dan McCarthy:
I think oftentimes, at least within the companies that we've worked with, they have a more difficult time getting budget approval when their argument is something more like, this is how much engagement that we got. If you're the CFO, you're wondering, like, "Okay, more engagement is probably better than less engagement, but how much is it worth to me?" If you're able to say, "These customers, they used to be worth 100 bucks. If we do this budget reallocation, we can expand the value of these customers to 150 on average. We're creating an extra incremental $50 per customer that we're acquiring," you can compute return on investment in a way that's credible.

Dan McCarthy:
I think, to the extent that you can then be able to go back to the CFO and say, "We have these initiatives. They're going to cost us X amount of dollars, but we're going to be able to get back Y," where Y is much is greater than X. You know, now we're talking.

Michael Linnert:
Yeah. I'm not sure how familiar you are with it, but I'll flag it. One of the huge trends in healthcare right now that is going to reshape healthcare is changing in how we calculate customer lifetime value and who the value accrues to.

Michael Linnert:
Historically, in the fee-for-service model in healthcare, the value accrued to the people who provided complex care, complex surgeries, really specialty care, as we move the value based care and we reward providers who can keep people healthy, more and more of the bonuses and economics will begin to accrue to primary care. That's a big challenge for the industry because that enables competitors to come in in a new way. Suddenly, Walmart, Amazon CVS, One Medical, Village Oaks, suddenly people who just specialize in primary care have a really compelling business model that starts to pull rents forward in the value chain.

Michael Linnert:
I think people who, if we fall behind on acknowledging that, we risk waking up one day and finding people stole all of our customers, all of our patients while we were looking the wrong way, or calculating the wrong lifetime value.

Dan McCarthy:
That's interesting. I got to admit, that's a world that I know a lot less than you about, so.

Dan McCarthy:
But I was going to say too, one thing, yeah I guess this might also go back to Chris' question about the pitfalls is customer lifetime value can mean five things to six people. There's all these different definitions of what is lifetime value. There are some that I think are just flat out wrong.

Dan McCarthy:
I've got a pretty ... At least I've convinced myself that I've got the definition that is the right one to be using, but it goes back a little bit to this question of what should it mean for an executive and how can we reach consensus about that? Because I think sometimes people, they hear lifetime value but it's unfortunate that, because they might have either a different definition or they've been thinking about it the wrong way, they don't care about it, but it's because they're not using the right definition.

Dan McCarthy:
So, yeah, I think having something that ties as directly as possible to corporate valuation is really important. So, happy to go over that, but yeah.

Michael Linnert:
Let me push a little bit on that because in healthcare, a lot of health systems are not for profits. And so, the thought of corporate valuation is a little bit of anathema. But, that doesn't mean that they can afford to look the other way because a lot of health systems are finding kind of no money, no mission. I think you're going to see over the next 3 to 5 10 years a lot of consolidation in the healthcare industry, and I think that consolidation will be led by the people who can drive value for customers and for themselves.

Michael Linnert:
Can you talk about how you would think about lifetime value? The nonprofit, if it's any different. I have some thoughts, by the way, if you want me to start, but [crosstalk 00:35:05].

Dan McCarthy:
Yeah, I've got some thoughts. Actually, it kind of speaks to ... I've got this whole lecture in my class called the taxonomy of CLV. Really, the thing that it highlights is that all these other variances, CLV, and they're actually really important and very helpful to know, and I probably look at a lot of them. There are a couple where I say, and these are just garbage; you really don't want to be thinking about this at all. But, for everything else, they have their place on the dashboard.

Dan McCarthy:
I think the key to avoid confusion is basically to have clear definitions as to what each of them are. Is this a sales CLV? Is this a finite horizon CLV? Is this a gross profit-based CLV or a contribution profit-based CLV?

Dan McCarthy:
In the healthcare setting, I think, just to avoid the potential for significant confusion, it'd be helpful to leave CLV the way that it should, in my opinion, should be defined, and I think there's growing consensus about this. But that if there's another variant of it that's more relevant and useful, by all means, let's actually have that be the Northstar that we focus on. But let's just name it appropriately. If it is some measure of total activity, it sounds like it could be a sales type of CLV, which is completely fine.

Dan McCarthy:
To the extent that we have the data available, again, we'll compute multiple of those including sales CLV because it definitely has its place. Part of it might seem like tomato tomahto especially if you're working within the company, you're like, "What does it really matter?" We know that this is most important to us especially when you start thinking across companies in different settings.

Dan McCarthy:
We're speaking with the regulators as well like FASB and the SEC. It becomes extremely important for them because they need something that's going to ... Again, we want standardization of these measures and terms. And so, if you had one definition for one industry, another definition for another, it becomes a mess and, potentially, there's no way they could even recommend it. So, yeah, we take this stuff seriously but ... Yeah, it's definitely, I think we're very much in the same page. But yeah, let's hear your thoughts.

Chris Hemphill:
I was curious. Sadly, we don't have a lot of time left, but one thing that you were mentioning frequently was the ideal definition of CLV. I think it's reflected in some of the papers that you've written that refute some different approaches. I'm wondering if there's a simple high-level view of, hey, this is the ideal way to look at CLV, and maybe an example of the wrong way.

Dan McCarthy:
Yeah, the net present value of all the variable costs and profits associated with a customer. And so, yeah, I think the key then is imagine that you have your firm and now you're spending this incremental amount of money to acquire this incremental customer. All of the fixed costs you incur, those were already spent. So, it's really comparing the marginal profits and trading those off against the marginal expenses and saying this is the incremental profitability that we can expect.

Dan McCarthy:
Imagine that we're thinking about some sort of Fintech or somebody who could potentially consider lending against that customer, or if you were to sell that customer to the Fintech, how much of that Fintech pay to acquire that customer? That's the number. That's really ... yeah?

Michael Linnert:
And I think, Dan, not just to acquire them, but also to retain them. And that's where I think we fall down in healthcare. We're pretty good about thinking about customer acquisition, but we don't think a lot about retention. I would just lay it out. I think, if you look and say what percent of customers in your EMR, your electronic medical record, haven't been in in the last 24 to 36 months, it's probably a staggeringly high number. Now, maybe you can say half of them are five plus years old and may have moved away or may have ... but there's still a lot of people that we're not seeing, right? And the longer between times we see them, the higher the likelihood somebody else saw them and they've jumped into some other health network besides us.

Michael Linnert:
So, the value of retention is important too. The marketing teams, with all their digital tools, have an enormous role to play in that. It's every bit as big, if not bigger, as the role they play in acquisition.

Dan McCarthy:
Oh, yeah. Maybe just to clarify, when I say that the Fintech is buying the customer, they're buying the whole customer contract. So, it includes all of the payments that make over the rest of the customer's lifetime. They would be directly incentivized, obviously, to manage that customer relationship over all future periods as best they can.

Chris Hemphill:
We've got some analysis going, Mike, to your point on the estimated amount of customers that you'd retain over a five-year period. What we're seeing is that over that five-year period, you're expected to lose almost half of, well, without additional retention efforts going on and with a handful of health systems that we're looking at, but the numbers are hovering around 40%.

Michael Linnert:
And it's staggering when we can debate the numbers, but my back of the envelope is lifetime value of the customer to a health system, and the fee-for-service model is 50 to $100,000.

Michael Linnert:
You know, when I was working in the wireless industry, it was less than 10% of that. In financial services, it was about half that. And yet, if you think what they do, to go engage and drive acquisition and retention and loyalty and delight, it's a multiple of what we do in healthcare despite the fact that we have much more value to go reinvest.

Chris Hemphill:
We are unfortunately close to the end here. But, Dan, in my conversations with you about this subject and about the courses that you're teaching on right now and everything like that, I was just wondering if you have any final thoughts. I know that there's a reason that you hopped on with us, and it wasn't necessarily under duress or anything like that. So, just curious what you'd like for people to come away with from this conversation?

Dan McCarthy:
I think there's probably a few things. For one, when you're using this, one of the earliest wins is understanding how the value of customers varies is a function of the things that you know about them at the time that you bring them in. So, that's a really good use case.

Dan McCarthy:
Two, it really helps to get the CEO and the CFO on board, if you're going to engage, if you really want this to work. To Mike's point, starting off with a pilot could be a great way to get that started. Always think about, when I'm doing something, what's the impact on customer acquisition, retention, ordering, spend, and profit. Oftentimes, when you're thinking about initiative, you're not breaking it down and thinking about it from the bottoms up. It can be very instructive to think about it from the bottoms up.

Dan McCarthy:
And then, I guess, finally, let's define CLV properly. I'm going to keep waving the flag about this. It's very important to me and I think it'll really help us all be able to get the most from the concept collectively if we start just defining it in a standardized way.

Chris Hemphill:
And, Mike, this is a subject, I know, that was at the basis of even founding this company. Curious, final thoughts that you'd like for the audience to have as well.

Michael Linnert:
I think this is a critical conversation. I think, too often in healthcare, we focus on one of two things, just acquiring a customer or just getting the next transaction out of them. I'm sure Dan, with more time, can share more examples. But I promise you, Amazon doesn't think that way, CVS doesn't think that way, and these are people that we're competing with, right?

Michael Linnert:
So, one is, we have to start thinking different; and two, is it's okay to start with imperfect incomplete calculations. The goal is to start. Even if you're off by 50 to 100%, well, maybe not 100%, 50 to 60%, it starts to impact the decisions you make. The more people who see you making decisions, they'll come in and ask why and then they'll refine your calculation as you talk. But this really is a journey and you can't let perfect be the enemy of progress. There's a lot of low hanging fruit.

Michael Linnert:
Maybe most of us aren't ready for Dan today, but we should be starting to talk to Dan and be ready for him within the next couple of months.

Chris Hemphill:
Absolutely. I think both of these answers fuel my reason for being here, which is really, that this kinds of thinking, I just see it and hope that it's becoming more and more a part of our DNA as marketers to think in those terms and think about how, what we're doing shifts customer lifetime value. And even, as we notice, different economies such as lower CLV versus higher CLV. Rather than ignoring the lower CLV components, start to find ways to optimize the offerings and use this thinking as a way to drive and improve access within healthcare.

Dan McCarthy:
[inaudible 00:45:33] is Crawl, Walk, Run. I'm definitely a big fan of that philosophy, so.

Chris Hemphill:
Well, hey folks, I've loved this conversation. This has been exciting. Audience, folks, you guys were super engaged. It was awesome to see all the input and feedback here. If you want more of that, we're going to be on in a couple of weeks with healthcare behavioral economist, Dr. Matt Cybulsky. That'll be fun.

Chris Hemphill:
If you want this kind of experience on the road, we've actually recently started a podcast. The podcast is called Hello Healthcare. You can reach it at hellohealthcare.com. Each week, we dive deep into a bunch of different subjects. We started with healthcare inequity. This week, we focused on a really strange question, Mike you're going to like this one, are marketers part of the healthcare delivery process? That's the question that we're focused on.

Chris Hemphill:
To get down to the answer to that question, we've talked to several people who are in marketing leadership roles within health systems, in more data driven roles. You get to really see a bunch of different perspectives and answer that kind of odd question. I've never seen a marketer wearing a stethoscope; but, are marketers part of the healthcare delivery process?

Chris Hemphill:
Keep an eye out for us. If you liked the video, give us a like, subscribe on YouTube, and we'll keep putting this out there. Thank you.

Michael Linnert:
Thanks, Chris. Thanks, Dan.

Dan McCarthy:
Yeah, thanks for having me. This has been great. Looking-
 

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