#144 From Data to Dollars: How Customer Value Drives Business Growth

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Well, today on the Delighted Customers podcast, I am
so excited to have a special guest from the world of
academia, Dan McCarthy. Dan is a
associate professor of marketing at one of the best schools in the
entire country, the University of Maryland and the
Robert H. Smith School of Business. I say that jokingly because

(00:21):
that's where I went to school. I first met, heard about
Dan through Dr. Peter Feder from the Wharton
School, who was one of my earlier guests probably two years ago on the
show. And the two of them partnered together
in a business Dan will tell you a little bit about in a minute. That
they sold to Nike and then now work in a business together

(00:43):
called Theta. And the focus of the research and the work
they do is around customer lifetime value and customer
base value corporate valuations. And so we're going to dig into that a
little bit more. I want to tell you a little bit more about Dan who's.
Who's come from Emory after teaching there for about seven
years now. He's at one of the finest schools in the country. I mentioned before,

(01:05):
University of Maryland. Dan, welcome to the show. Yeah, thanks for having me.
Yeah, clearly no bias there, but I would agree.
All right, go Terps. Go Terps. Dan has
been featured in media outlets like the
Harvard Business Review, the Wall Street Journal, Fortune, the Economist,
USA Today, Barron, cbs, cnbc,

(01:28):
and so many more. He's won so many different awards and I'm just honored to
have him on the show. And as I mentioned before,
he's a partner in Theta. So Dan, can you tell us a little bit
about what Theta is and the primary focus of the business?
Yeah, Theta is a best in class customer lifetime value
prediction and insight business. We have two kind of primary

(01:50):
markets that we focus on. One are investors. We help them understand if
they're looking to make a purchase of some direct to consumer business or
really any business that has trackable customers over time, we can help
them understand how good are the unit economics of that business. When
they acquire customers, are they making money or are they losing money? So
they're really interested in kind of better understanding. When we kind of go

(02:12):
beneath the top level financials, what can we see about the
ability of the business to continue to generate operating leverage and that
they become more profitable as they grow? And to understand the
profitability of customers that they acquire is like a key, very key
ingredient to that. So that's kind of market number one. And then market number
two are the corporates, the VP of marketing, everyone

(02:34):
who's in charge of managing those customer relationships over
time. If you had a crystal ball that could tell you this is how many
purchases these customers will make, this is how much revenue we're going to get,
this is all the profit. And oh by the way, this is how much we
spent to acquire each and every one of those customers. Then you can compute
something like a return on investment at the individual customer level, which is a

(02:55):
really powerful thing to have. So yes, we kind of do all that sort of
modeling on behalf of the companies that we work with. And so for the
audience's sake, I know some people listening may be familiar with
customer lifetime value or lifetime value
of a customer. So there's different acronyms around, but I know when I had
Fred Reicheld on the show, he talked about what he

(03:16):
called as the traditional capitalist financial metrics
and boo hoo hiss on those and that we should be using
something like customer lifetime value. Would you agree? And if so, why?
I would agree and disagree. Not to be the two handed academic, you
know, I think the ultimately the value of
a company is the discounted sum of the future free cash

(03:38):
flows. If your business is not generating free cash flow,
it's not going to be a valuable business. And so you know, ultimately, if
that's what you need to know is what are those free cash flows going to
be into the future? I mean, I don't know what else you call that
except top line financials. But what we would argue is that to be able
to understand what those future free cash flows will be, you really need to

(04:00):
understand this critical piece of it. But I would also hesitate to
ignore the importance of like overhead expenses
if we're thinking about customer lifetime value or customer experience or any
of the net promoter score, any of those measures. Oftentimes they
kind of ignore overhead expense. Now they might evaluate
some new opportunity and say, well this is how much we would spend to improve

(04:24):
how customers feel about us. And then you can kind of carry out that exercise.
But ultimately some businesses to get the whole engine running is
more expensive than other businesses. And so you really can't ignore the fixed
costs. You know, when you think about valuation. And so to that extent I
think there is this piece that is often ignored by, you know, us
kind of customer people. And so again, it's not to say that what

(04:46):
we're doing is any less important. I think it probably is more important.
But yeah, I wouldn't want to diminish the importance of that when
we're thinking about how much is my business going to be worth. Yeah,
and both are important, but in different ways. And you need to know
that customer lifetime value. I think one of the premises of
customer lifetime value is that we understand that all customers

(05:08):
aren't actually the same and they shouldn't be treated the
same. Can you say more about that and how CLV
plays into that? Yeah, whenever you look at every customer,
often will have a different value. Some people buy a lot, some people buy a
little. And so inevitably you're going to expect some sort of a spread.
But I think the mental image that some people have of what the

(05:30):
resulting distribution of customer values is, is something like a bell
curve, you know, that a lot of people are in the middle, yet some were
a bit worse, some who are a bit better, you know, but you actually,
what that distribution actually looks like is more like this.
You have this humongous slug. It could be anywhere from 40 to
80% of all your customers that are worth very little.

(05:52):
Potentially nothing, potentially negative actually. When you factor in CAC
customer acquisition cost and then you have this really small slug of
customers, typically it's like 5% of the cohort that's generating
like all the value of the cohort. And so it's this
barbell. And as soon as you start, you know, kind of embracing the
fact that you don't have a normal distribution, instead you have

(06:14):
this crazy barbell thing, then it kind of begs these questions
like, well, why do I have all these terrible customers? You know, how are they
different from the best ones? And, and then even if we were to assume that
we can't really do a whole lot to change the customers, hopefully we can. But
even if we couldn't, there's probably ways that we can acquire more of our
better customers and maybe de emphasize the acquisition

(06:35):
channels or the things that are bringing in the lower quality customers.
So yes, I think when you talk about embracing differences in your customers
and this thing, embracing heterogeneity, embracing the variation,
I think that oftentimes is what's being referred to. So if you
have the knowledge of what those best customers, so to speak,
the ones that bring you the most value, then let me just throw out a

(06:58):
couple of the advantages and see if you know, so you
see if I'm on on point or you would add or delete, but you
have knowledge in which to resource allocate.
You have knowledge into how to optimize your channels.
You have knowledge on how to personalize and customize the experience
and knowledge on how to develop retention strategies

(07:21):
where your primary focus is going to start with
those customers that are contributing the most to your value.
Did I hit that right or would you add or change any of that? Yeah,
that's right. And so I think oftentimes when people, there's this area
of voice of the customer, we want to know what do they care
about? Do they care about convenience, do they care about price, do they

(07:43):
like the colors that we're using? And it's to say that that's not important.
But oftentimes it is. Like the customer, you know, we just
kind of take this survey, we do it on a whole bunch of people
and then whatever results that we get for all those people, we just kind of
take this simple average of them and we say, well that's what the customers want.
And, and what we would argue is maybe we want to have a

(08:06):
segmented version of that, you know, where, let's look at the results of
that but just among the top 5% customers
and then let's look at the results for the bottom 80 and maybe what you'd
find is that the people who are on the top, they have actually pretty different
things that they care about than the people at the bottom. It's not that we
want to ignore the people who have lower values, it's just that we may

(08:28):
want to have a different approach for them because the things that they care about
are different. If it's going to be equally expensive
to do something for the low value people versus the high value
people, well, if I know that I'm going to get more of a bump in
my revenue from the high value people, I probably want to prioritize the
initiatives that kind of focus on the high value people. Before we talk

(08:49):
about some applications of this and some immediately come to, I want
to talk about when I first posted about the interview
I did with Dr. Peter Feder from Wharton, your partner,
I think it was called don't treat all customers the same as what we titled
the episode. And I got a lot of negative pushback from
people in particular in the CX space saying no, you should treat

(09:11):
all customers the same as if they're number one. And they thought it was
sort of a non democratic way to view your
customers when you don't treat them all the same. Have you ever heard
anything like that? And is it, you know, does it make sense if you explain
the, the financial reasons why it shouldn't be that? But have you ever heard that
before? Well, I think there's a few sources of that feeling. One is

(09:33):
fairness, like we need to, we need to be fair. You
know, we talk about equality and here we're not Being equal?
Yes, I think that is one of the sources of it. I think there's another
that feels like there's a lot of harm that can be done, you
know, and so we might want to prioritize. Some people, I think sometimes they

(09:53):
think that we, we want to kick those other customers to the curb
or fire them. And certainly I'm not sure that
we would advocate for that in almost any setting. So, you
know, actions have consequences. And if we were to really like
completely ignore or even fire some customers, that will
create negative word of mouth. So, yes, I think, you

(10:16):
know, that can be legitimate depending on how far you take it. But
we would not probably advocate for taking it as far as some people might be
assuming. But yeah, I think, you know, I come from a background in finance.
I went to Wharton for undergrad and then again for the PhD in
undergrad. I was kind of a straight up Wall street person. So I went to
a hedge fund for six years after graduating there.

(10:37):
And ultimately companies have a fiduciary responsibility
to their shareholders. And if you're the CEO of a firm
and you are taking actions that are not kind of mindful
of shareholder value maximization, you can get fired. And so
it really matters, the board is in place to kind of uphold
that too. And so when you think about all that we're advocating for, it's

(11:00):
really just advocating for being
mindful of return on investment. And I might make some investments
that pay off well and others that pay off very poorly. And
so here we now have the ability to be a lot more granular
at the customer level in how we make those investments. But
ultimately that's all we're trying to do, is we're trying to avoid spending money and

(11:22):
not getting anything for it. So in terms of the way
leaders approach clv,
let's say they've done some analysis, either using
your firm or another of their own internal resources, and
they say, okay, we think we know who our best customers are. What are
some mistakes or missteps that they make in their approach to it?

(11:45):
So kind of mistakes. And they have the philosophy, but the
question is the execution. There's a whole bunch, one of the
ones that gets very little love, but it's so important
is how we actually do the cost accounting. It sounds so
dull, but you can get such a different view
of how valuable your customers are if you allocate the

(12:07):
cost the wrong way versus the right way. So, you know, for example,
like, it would be very bad to allocate a whole bunch of
truly overhead expenses to the customer contribution margin.
You know, so all of the lawyers and the accountants and the
CEO's salary and the, you know, the headquarters and all that,
those we would want to leave out because when you're acquiring your next

(12:30):
thousand customers, you're not going to have to buy a new headquarters.
Those costs are gonna stay the same. So if you kind of encumber
the contribution margin with those expenses, you're gonna end up with this pretty dim
view of how much your customers are worth. And it makes a real difference
because what that would then imply is that your return on investment is pretty
poor. So how much should we spend on customer acquisition?

(12:52):
Well, I'm gonna be real gun shy because I'm seeing these ROIs that are
like super duper small. And in fact maybe I
should have made those investments. And so that could lead you to under
invest in the customers. But it's very easy to come up
with the converse that you over invest because you have
this overly optimistic view of the value of your customers.

(13:15):
So it could be that you're focusing on revenue and you're not taking into account
cost at all. If you look on Google and you say, what is the definition
of customer lifetime value? I guarantee you you'll find a whole bunch of definitions
that are purely revenue based and don't take into account cost
at all. So again, it's not every single one of the references, but
it's surprisingly common. So accounting for those costs is

(13:36):
tricky. And again, there's kind of the issue of how do we
calculate customer acquisition cost? How much did we spend to acquire a
customer? That's like a surprisingly, like a deceptively difficult question to
answer. You could spend a whole semester teaching a
course just on that. And then the slightly easier but still kind of tricky
one is, you know, what is my variable margin? You know, I get this revenue

(13:58):
from that next marginally acquired customer. What are all of the
expenses that I'm going to have to pay to be able to bring that revenue
in? So cost of goods sold, labor, payment processing,
probably some amount of customer support, expected returns,
fulfillment expenses. But you know, there are some expenses that will also
kind of scale over longer horizons of time. And so again, it's

(14:21):
just, it's not quite as trivial as it might seem. So that's one
thing that can dramatically swing like the return
profile that you think that you're getting relative to reality
now Theta. So we'll obviously we'll spend a good amount
of time on that with our clients to make sure that we're all thinking about
costs the right way. The other thing that we'll often see is that if you

(14:42):
have a not very good model of what customers will do in the
future, you say, well, I found this thing online somewhere, you know,
off the shelf. This will probably do fine, right?
Well, you'd be surprised at how bad those can be depending on the business.
So there's a lot of things that matter a lot to get the
right prediction of what those customers will do. And it's especially

(15:05):
hard for the customers that you acquired relatively recently, because
most of these models, they'll kind of look at customers you
acquired a bunch of years ago and say, well, now we kind of observed
their lifetime value, you know, because they've been around for a while, maybe most of
the customers have churned, you kind of know what they were worth. But the
customers you acquired four years ago could have a very different payoff

(15:28):
profile than the customers that you're acquiring today. And so we want
to account for all sorts of sources of variation. And so
having the right model becomes incredibly important. And it can lead to differences
of a factor of like two or three in terms of what you're going to
get over the next five years from them. So when I think
about differentiating experiences for your best

(15:50):
customers, what comes to mind as we, we talked before about don't treat all
customers the same is I think of Disney
has an express pass, and I'm going to get the name of it wrong.
You've got your corporate suite at the ball game, you've got
your Premier Lounge at LaGuardia from
Delta. You know, you just go on and on.

(16:12):
Am I thinking about that in the right terms? Those are certainly good ways
of making your customers sticky. I've written some research about
the impact of signing up for some of those subscriptions. And obviously
with Delta, it's not a subscription. It's really having kind of a tiered loyalty
program that encourages people to deepen their relationship
with you so you can kind of get access to certain benefits.

(16:36):
Some people, they like the status of being able to say, I'm
platinum, I'm gold medallion. So whatever it might be, these
programs can help encourage that sort of behavior from them. And so again,
I'm a ROI guy. And so the question would be the
launch loyalty program. I'm going to provide these goodies, whatever they might
be. Maybe it's free delivery on the purchases, maybe I'm going to charge them a

(16:59):
subscription fee. But let's kind of take into account all
that. Let's take into account how it Changes, customer retention,
how many times they buy, bring all that together, and that tells us
how much money did we make from the program. And again, if you're going to
present something like this to the chief financial officer, that's going to probably be
the argument that will convince them that this is worth doing.

(17:21):
You know, I think that if you, if you purely focus on, well,
it's going to make people happier. You know, we're going to get a more engaged
customer. Well, engagement in what way? You know, are they going to go to the
website more? They might talk about us on social media and
maybe we'll get some social media hit. But is that going to lead
to more purchases, more revenue? Yes, I think, you know,

(17:43):
to be able to kind of translate things like that to
net profitability, I think that it's incredibly important. Yeah, as you're
talking, I'm thinking about going back to that. I don't know if it's an upside
down hockey stick, but whatever shape, I think the, the curve, the dumbbell
curve is of those simplest. He called it the 8020 rule.
I think about the bank where I worked, and we had retail, we had commercial,

(18:06):
we had mortgage, wealth management. The majority of
deposit accounts, checking accounts were not profitable
at all. Anyone who just has a checking account with a bank and
doesn't fund it with lots of money, which you shouldn't probably do,
should probably put enough in there to make it an operating account and invest
the rest. But if you just have a low balance and you're keeping a checking

(18:27):
account, you're actually costing the bank money. There is a hope
that at some point you'll take out a loan of some kind and, or
get engaged in more profit, start a business, engage in more profitable
businesses. And some of the, some of the customers do. But
it's a great illustration of how you might not think about
it from the outside, but you as a customer, you may actually be

(18:50):
costing the organization money. Have you found that to be true? Yeah, I
think in a lot of businesses, most of the customers will be unprofitable
for some reason or the other. Now I say the other aspect though, of
lifetime value is that we do want to account for our best
expectation of how customers will evolve over their life cycle.
And so it could be that the checking account is kind of the gateway

(19:12):
drug into the broader portfolio of services. Some people,
they just kind of leave it at that and they say, don't worry, it's going
to be fine. You know, these are kids, they're going to have families,
they're Going to get that car, whatever. But yeah, I would say let's quantify that.
You know, that's an empirical question. Like let's take all the people
they first signed up with a checking account, now let's just track them

(19:35):
over time and see what proportion of them migrated
into other services, how many people stayed. Checking account only. And
that's again what gets us the value of the cohort is to be able to
do that. And so analogy to that would be in the mobile
gaming sector you have a lot of free to play games and so
inevitably you'll have a lot of people that stay with the free stuff.

(19:57):
They never spend any money in the game, but they might be playing a lot.
But for every 100 people you'll have one person who does
graduate and they might spend like crazy on the game.
So it could be a very valuable customer acquisition vehicle. But again,
you want to be pretty numbers minded about.
Doesn't mean that because they could, they will. Even if they

(20:20):
do, there's the question of well, what proportion of them do and is
there, are there ways that we can be able to kind of nudge more of
those people and kind of hit that sweet spot where we're bringing in a lot
of people but then we're getting enough of them to migrate that
this pays the bills. So yes, again it's
not, it's not an insurmountable problem, but it does speak to the importance of

(20:40):
that lifetime view. What advice would you give to
C suite leaders who maybe haven't done
a CLV analysis of their organization? Get started with
something easy. You know, I think jumping straight into the modeling
is probably running before you can walk. I advocate for kind of
understanding the philosophy behind this of not even looking at any

(21:03):
data yet. You just understand what is the opportunity here.
And then I think the second step is something like what Pete
advocates for with the customer base audit where there's no models. It's still purely
backwards looking, but it really helps you understand how your business
sits. This is what the business looks like from the customer
perspective, how much spread there is across the customers, how things are different

(21:25):
by business unit, how things have been changing across the
cohorts. All very valuable. And the nice thing about those views is
that they don't require a prediction. There's just a lot of work that can go
into having good predictions. And if you're going to present something to
your boss or to the CEO of the company and you have this heroic
eight year forecasting horizon or something like that, inevitably the

(21:48):
questions become well, do I trust that? But here it's like
auditable. Well, these are the numbers. And so
as long as there's no quirk in your data set, you
can take those as ground truth. And I think that can be a lot more
compelling. You can get, kind of get a lot of the other people in the
company on board. You know, I remember when I worked at the bank in the

(22:09):
mid Atlantic, I know that there were a number of initiatives from
studying whether or not to create a digital new account
opening platform to buying a new interface
for the many different software applications that drove the
bank. And in the big hurdle that I think came
up quite often was, well, we got to get our hands around

(22:31):
our own data before we can go get help. Have you heard that one before?
And what would you say to that? Yeah, if your data house is not in
order, that can be a real issue. I would say our models,
the data requirements are not so high. So I think some people
use that as an excuse to never even look because they just have other
things that are higher up on the pile and they say, I just need some

(22:51):
plausible reason to not do this. Now, most of our models, they only
require at the base level like a good transaction log.
And you think how many companies have that? Well, most of them should.
If their transaction log is really that bad, they might have like
finance issues. Like how can they do their, you know, their accounting. I think usually
when you start running into issues is like with everything else, you know,

(23:13):
the metadata about the customers, it could be so different
that it's great to have all the rest of it. But at least if you
want to understand, like this is how healthy my business is, this is the
spread across the customers, usually you can kind of go to the transaction log
and it should be pretty good. Yeah. When you think
about the payoff, pardon the pun here, of doing

(23:36):
the work to get to things like CLV and getting your
arms around it. My gosh. I mean, you just described, and we just talked
about how you could be missing something really important, really big in
focusing on treating everybody the same when you know you're
losing money on a good chunk of your customer base and you're making a ton
of money on 5% or 10% and you're really not focusing on them. Dan, I

(23:58):
want to, I want to ask you if you could share a success story.
When you think about when you looked under the COVID when you've opened the
hood and you think about something that you
discovered with a client of yours that was sort
of like what you would consider a success story from your standpoint.
I think one interesting one was Warby Parker. Yeah. This was a

(24:21):
public company and we did this analysis using just the public
data. And so those are kind of nice because you can say the name.
Yeah, right. And if they're public, you have all of
the income statement, the balance sheet, you know, so there's a lot of data
that is available now. You don't have the really granular data. So
oftentimes you can't go to the segment level and sometimes you can't go to the

(24:43):
cohort level either. You can really just kind of get the. The overall view
of economics. But, Dan, can I just interrupt for just
a. So for those listening who. When you're saying cohort, I just. I think I
know what you mean. I want to make sure that everybody's following along. So it's
really a group of customers that you're looking at, and it's the same
group you're going to look at over time. It's the same specific group of customers.

(25:04):
Is that right? That's right. It's a good point. So usually when I talk about
a cohort, it's usually an acquisition cohort. So there's all sorts of different.
Like typically a cohort would be some sort of customer segment. And we
define those segments by when were you acquired? Where the
definition of a customer acquisition is that they made their first purchase, they
finally took the jump. So,

(25:25):
yes, we'll often do our analysis in this cohort by cohort way. So we'll
say, what's the value of the customers that were acquired in Q1,
2017, Q2, 2017, so on and so forth. Let's kind of look
at them over time. So Warby Parker. Yeah, so Warby Parker.
Unprofitable. At that time, they weren't even growing very quickly because this was
post Covid, and they were growing quickly before COVID but they had like

(25:48):
two thirds of their revenue coming from stores and all those stores got shut down.
So, yeah, so they were, you know, it wasn't their fault, but.
But, you know, that was a headwind at the time that they were filing to
go public. And they put a lot of great data in their filing and they
kind of had the usual canonical issue of
actually there. They didn't even have a whole lot of revenue growth. Not profitable.

(26:10):
How do we value this company? Will they be. Will they be a
valuable business? Can they grow their way out of
unprofitability? And again, that's the big thing that a clb analysis
can help you uncover. And we kind of looked at
the numbers very carefully. We found a few,
actually a few errors in their filing that they had to

(26:32):
restate along the way. Kind of that notwithstanding, we found that they
actually were turning a pretty good profit on the customers that they were acquiring.
And so that was certainly. It was heartening. We weren't able to get all the
way up to the valuation that they were trading at right
after they went public. No matter how we kind of dialed up the
assumptions, we were getting like less than half of their valuation

(26:54):
at that time. So. So we were kind of torn because we thought we would
give them a clean bill of health from a customer perspective, but that doesn't justify
any valuation. And the valuation they were trading at was, was just a bit
too high from our perspective. So, you know, lo and behold, what ends up happening?
They ended up trading down to our valuation. They actually traded down to half of
our valuation. And then we said, whoa, all right. You know, now

(27:16):
it's kind of the pendulum swung too far in the other direction. So we
went back in, took a look again, because, no, no valuation that you make is
going to be permanent into the future. You know, we say, well, right now,
based on what we see, the valuation is going to be 20. That doesn't mean
that they should always trade at 20 for the rest of eternity. So, yes, we
kind of went in when they were at like 10, and we said, well, actually,

(27:39):
still getting around 20. So we put out the second piece that said
they're trading at 10, we think they're worth 20, and they actually end up trading
back not only to 20, but above 20. Actually, I haven't checked where they are
today, but it's kind of this nice story from that
perspective that we weren't just like a perma bear. We
started bearish and then we actually moved to bullish, and now we're kind of

(28:01):
somewhere in the middle. But the other nice thing about that story, which is a
kind of a validation of this way of looking at the world, is they've continued
to grow. If their CLV is positive and they continue to acquire
enough customers, that means that they should become profitable. And
in recent quarters, they become profitable. So, you know, we feel like,
well, you know, that's also something of a validation that

(28:22):
we were able to kind of uncover they were able to grow their way into
profitability. You know, whereas for some other companies that we've done analysis on,
that has not been the case. You know, just the CLB to CAC is very
Marginal at best. And if it is, then you can grow a whole lot. You
acquire a whole bunch of new customers, but you're no close to actually
being profitable. So you help Warby Parker see more

(28:43):
clearly. It's a bit of a corny joke. Yeah. In
the eyeglass world, customer value lenses. Right.
Yeah. This is really was their investors, I think that. I don't
know what the. It's funny that their founders came out of Wharton too.
So I'm from Wharton. Pete Fader, Wharton marketing
Professor, they were in his office. So we had,

(29:07):
you know, pretty close indirect ties with, you know, with the management
there, but we had never spoken with them. And so I have no idea and
how they ever felt about it. But. But I will say, you market
investors have a way of always thinking that the
current price is the right price. And so I. I
still remember all of the flack that we got, you know, when we were coming

(29:28):
in so low and, you know, you're being so stupid. You're not
accounting for this, that or the other thing. I was like, well, you know, time
will tell. Yeah. Dan, I. I appreciate you keeping.
It's simple enough for even me to understand.
Thank you for what's behind the curtain, I'm sure are
complex algorithms and lots of data and AI

(29:51):
and all that good stuff. And thanks to you guys, we don't need to know
all that. Well, I say I wish I was smarter, but this is kind
of how I'm able to process everything.
I think there are some things that are truly complex.
Most things are not as complex as they seem. Like,
if you get to know. If you get to really understand it, it actually is

(30:14):
kind of simple. But I think oftentimes it can be kind of hard to get
to the point that you've kind of reached the appropriate level of simplicity
and you haven't gone too far. But yeah, I think the customer lifetime value in
some sense, it's like so simple. I mean, you acquire
customers, there's a price that you pay. There's what you get on the other side.
And you kind of compare the two and am I making money or losing money?

(30:35):
And I want to make more money. Right. So, you
know, so, yeah, the models can get a little more complicated than that, but
philosophically, it's really a pretty straightforward exercise.
It is. It is. What a wonderful discussion. I so
appreciate having you on the show, but I want to ask you one last question.
And that is, what delights you as a customer? What delights

(30:57):
me as a customer? Well, I'll give kind of One example of this from yesterday,
you know, I was just saying I took this trip to Boston and all the
flights were delayed in the airport on the way back because of the storm that
came up the East Coast. And so my flight, it was scheduled
to leave at 5:45. Now it's 9 o', clock, now
it's 10 o', clock, now it's 11 o'. Clock. You know, still waiting. But the

(31:19):
Delta Sky Lounge, again, going back to the Delta example, you know, I'm one of
those platinum medallion people. And to be able to just
chill out in the lounge for hours, that was such
a plus. And there's one thing to kind of get
value like on an everyday basis, but there's another thing
when crazy things happen that they, you could be in a real

(31:41):
pickle, you could be much more uncomfortable, but they're able to kind of come through
with services at that moment at those times. And I feel
like, you know, here I place a lot of value on Delta for
that. That obviously the flights tend to leave more on
time. You know, you're not going to have the issues of getting punched in the
face or anything like that. You know, if you kind of end

(32:01):
up in a pickle like this to be able to have those services that
are kind of readily available to you, they really come in handy. So, yes,
I'm a very happy Delta customer, even though I no longer live
near the Delta hub anymore. Right. You know,
they'll make it much more okay than it could have otherwise been. And so I
think that that can be underappreciated because those events kind of by construction don't

(32:24):
happen very frequently. Right, right. Well, Dan, I thank you
so much for being on the show. If somebody wanted to get a hold of
you, want to engage with Theta to do some, some work with
you guys, what would be the best way? Connect. Connect with me, I'd say
LinkedIn is my main platform. I'm talking about this sort
of stuff a lot over social media. So yeah, Daniel McCarthy, University

(32:45):
of Maryland. You probably need the qualifier because all the other Dan
McCarthy's out there. And yeah, we love to speak with you and I think our
goal is to make CLV and CBCV boring. It's
just, it's what everyone does, you know, like, how can you not do it? So,
yeah, I think we're well on our way, but we still have a lot of
work to do. Excellent. Dan McCarthy, thanks so much for

(33:07):
being a guest on the Delighted Customers podcast. Thank you.

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