January 23, 2025 • 44 mins
When you think of combinations who comes to mind?
👉 Jobs and Wozniak?
👉 Proctor and Gamble?
👉 Hewlett and Packard?
When it comes to customer experience and one-to-one marketing, hands down, it's Don Peppers and Martha Rogers. They are the individuals behind the Peppers and Rogers brand.
Don has authored or co-authored eleven different business books, collectively selling more than a million copies in 18 languages.Â
In 2022 Peppers and Rogers released the greatly revised and updated Fourth Edition of their graduate-level textbook and desk reference, Managing Customer Experience & Relationships (Wiley, 2022).
I had the chance to pick Don's brain about the intersection of AI and customer experience management. It was a lesson in how to think about the value customers expect and the value companies desire.
There were so many powerful insights including:
👉 Transforming Customer Interactions with AI:
Don highlighted how AI, especially generative AI, can revolutionize real-time, individualized customer interactions by analyzing emotional sentiment and providing empathetic, immediate responses.
👉 Rethink Success Metrics:
Don emphasized the importance of measuring success through customer-centric metrics like customer lifetime value (CLV) and proposed the innovative concept of 'Return on Customer (ROC)' as a more accurate gauge of business performance over traditional Return on Investment (ROI).
👉 Fostering Trust for Long-term Value:
A significant part of his message was about building trust with customers. Don stressed that maximizing customer value inherently requires businesses to always act in their customers’ best interest, nurturing trust and long-term relationships.
Don's vision and experience provide a roadmap for leveraging AI in creating truly personalized customer experiences. For more pearls of wisdom from Don Peppers, tune into the full episode of the Delighted Customers Podcast!
Meet Don Peppers
During the course of his career, Don has authored or co-authored eleven different business books, collectively selling more than a million copies in 18 languages.Â
His first book, The One to One Future: Building Relationships One Customer at a Time (Doubleday, 1993), coauthored with business partner Martha Rogers, kick-started the Customer Relationship Management discipline (“CRM”), which has evolved over the years into the “customer experience” field.Â
This is near and dear to my heart because I’ve had the blessing to teach customer relationship management at Michigan State in the first CXM Masters Degree program in North America. Â
So you’ll have to understand, this is an extra special episode for me. To have the Tom Brady, the Wayne Gretzky, the Babe Ruth, and the Michael Jordan the GOAT on the show is a big deal.
Finally, In 2013 Don and Martha were inducted into the Data & Marketing Association’s Hall of Fame, along with their business colleague Seth Godin (Don wrote the foreword for Godin’s 1998 breakthrough book Permission Marketing).Â
In 2022 Peppers and Rogers released the greatly revised and updated Fourth Edition of their graduate-level textbook and desk reference, Managing Customer Experience & Relationships (Wiley, 2022). As an Adjunct Professor of Marketing at Menlo College, Don teaches from this very textbook, and when time permits he Harvard Business Review articles:
-
World Class Bull (May 2009), an HBR Case Study commentary, with Martha Rogers
-
Is Your Company Ready for One-to-One Marketing? (Jan-Feb 1999), with Martha Rogers and Bob Dorf
-
Do You Want to Keep Your Customers
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Today's episode is brought to you by Achieve Unite, a global
leader in leadership development, business acceleration and trusted
partnerships. Achieve Unite combines deep expertise, data
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costs, elevate talent and build trust. They're more
than advisors. They deliver results with their proven three part approach,
(00:23):
talent development, ecosystem strategy and profitable growth
programs. Whether you're strengthening alliances, enhancing internal
systems or optimizing your partner ecosystem, Achieve
Unite is the partner you need for success.
Welcome to the Delighted Customers Podcast. I am so
(00:44):
glad you're here. We challenge conventional thinking about
customer experience because I believe that improving experiences isn't
just good for business. It's a powerful way to make a meaningful
difference in people's lives. Each week we we feature thought
provoking conversations with industry thought leaders from
a variety of backgrounds offering unique perspectives and
(01:07):
actionable insights. Get ready to sharpen your
leadership and transform your approach to customer experience.
Let's dive in.
Well, I am incredibly excited today to have a very special
guest on the show, Don Peppers. And let me tell you a little
bit about Don Peppers before we, before we get started. During the course
(01:30):
of his career, Don has authored or Co authored 11
different business books, collectively selling more than a million
copies in 18 languages. And his first
book, the One to One Future Building Relationships One Customer at a
Time from Doubleday, which he co authored with his business partner Martha
Rogers, which you may have heard Power Peppers and Rogers
(01:52):
before kick started the Customer
Relationship management discipline CRM which has
evolved over the years and has really been absorbed by customer experience
in our field. So this is near and dear to my heart because
I've had the blessing to teach customer relationship management at Michigan State
in the first CXM Master's degree program. And so
(02:14):
you'll have to understand this is extra special episode for
me because you know I have the Tom Brady, the Wayne
Gretzky, the Babe Ruth and Michael Jordan the goat
on the show. And so this is a big deal. This is a big
deal. Don and Martha were inducted into the Data and Marketing
Association's hall of Fame along with their business
(02:37):
colleague Seth Godin. And Don wrote the forward to Godin's
1998 breakthrough book Permission Marketing. Seth
was a guest on the show as well.
And the thing that also connects me directly to Don is he wrote
now in the fourth edition, Peppers and Rogers
released the customer relationship management book
(02:59):
called Managing Customer Experience and Relationships by Wiley. And
if you're watching on video, he's holding up the book
which we'll start using at Michigan State in my class
because it's, that happens to be the class that I teach. So with that long
winded intro. Don, welcome to the
show. Thank you very much. Mark, Delighted to be here. And
(03:22):
let's get started with the meat. Okay. Yeah, let's do
it. So today what I hope we would talk
about is the interplay of AI with
cxm, customer experience management. So if you
would, if we could like level set for the audience,
(03:43):
you know, frame out what we're talking about here in terms of AI and
cxm. Well, the first
kind of computing that prior to AI,
the way a business would
treat different customers differently at scale is
they would use rules, business rules. You know, if
(04:05):
customer does this, you do that, customer does this, you do that.
If this is true, then that and that are true.
But the problem with that is the rules have to be
written somehow. There are software programs and so forth that make
them more accessible, but it's very complicated
and it was never really true one to one
(04:27):
real time marketing. Whereas AI
tools, and particularly generative AI, which gets better and
better and better hold the promise for a company
really being able to treat each customer
individually, even if they have millions of
customers and do it efficiently
(04:50):
with corrections and so forth. So I think
the computing power that's out there now
is going to make the one to one.
Vision that Martha. Rogers and I had back in the 90s
really come true. Pretty much. Pretty much.
(05:11):
And so would you say prior it was more cost
prohibitive and now it's becoming more accessible
because of AI? No, I wouldn't say that that's a problem.
Costs were certainly an issue, but costs went down when we
moved from Oracle and Siebel to cloud
based Salesforce and other cloud based
(05:33):
systems and software. As a service,
data has always been available, but it's been difficult
to validate, verify,
comb through and regularize.
There are all sorts of issues involved that requires manual
(05:53):
intervention. And every time you have an issue of manual intervention,
you reduce the practicality
of treating different customers differently.
AI has its own problems, right? AI
is, it's subject to biases because the
(06:13):
large learning models and other tools databases that
the AI tools are trained on, those databases
themselves are biased. They're biased against particular
races or genders or other things. They're biased
against people of different incomes and depending on how
prevalent your type of person is in the
(06:35):
data that they're looking at and you know, we're dealing with all those kinds of
issues. I think one of the most important issues when thinking about
how to apply general
generative AI to one to one marketing is
protecting the privacy and
being on the customer's side.
(06:58):
Right now a lot of companies out
there, business executives, want to do a better job
of targeting customers. And literally the word target itself
contains the bad idea. Okay? Should never think of
customers as a target. In a truly interactive
world, your customer is a partner in a
(07:19):
relationship that. You want to go on through time. And to be more and more
valuable. But in most companies,
the organization is based on products,
not customers. You know, you could put your hand. On some product that a company's
operating. Or marketing and you can pull the string
and you can find an executive. At that company who's responsible
(07:42):
for that product somewhere. I guarantee you every product company is like that.
But very few companies can. You put your fingers on a
customer and pull a string and find out who at that company has
accountability for that customer's increasing
lifetime value. You see what I'm saying? So it's an organizational
issue as well. I think what we're seeing here is a
(08:04):
form of technology which will demand
different traditions, different
cultures, different sense of mission
on the part of the organizations that are using these technologies if they want
to use them effectively. You need to
constantly look for using these technologies and using
(08:27):
one to one marketing not to build your business bigger,
but to serve your customer better.
Okay? And if you do that, you will build your business bigger. But if
you only concentrate on your business and your costs and immediate
sales guarantee those relationships will never be as strong as they ought to
be. Yeah, and you've been pounding that drumbeat for a long time
(08:49):
about focusing on the customer, right?
But how do you see. Because you use the word like
interact and engage and we used the word
earlier, interplay. How do you see AI helping us
achieve that interplay? I see it in a number of
ways. Number one, I can make an
(09:11):
immediate response from the company in an automated fashion
that is more akin to what an empathetic
human being might do. Number two, and I can
do a better job than, than a simple machine
of interpreting customers
comment or suggestion or
(09:33):
complaint, even to the point of
analyzing their emotional sentiment and comparing it with
the actions that have been taken by other customers with that sentiment
and that type of history. So there's tremendous things that
the AI engine can help you do, but you have to know where you want
to go with it. You have to know what the goal
(09:55):
is. And I repeat, if your goal is simply
to sell more stuff and lower your
costs, you're unlikely to succeed very fast. But
if your goal is to use The AI tool
to deliver better and better service to your customers. You're probably going to sell more
stuff and probably reduce your costs as well. Well, I want to get into
(10:17):
some practical ways that leaders can start to think about doing
that. But before, before we do, I want to double tap
on this, this idea of what's the
big deal. Earlier you mentioned if they treat the customers
right, they will get the business outcomes that they're hoping
for, right? Most likely. Right. And so part of my
(10:39):
question is, are we, are we going to get the business
outcomes through? Because I get asked this question all the time. Am I
going to get this through cost reduction? Am I going to get it through,
you know, referral business? Am I going to get it through revenue
growth? Or is it a combination of all those.
Yes, yes, yes and yes. Okay, you're going to get it through
(11:02):
all these things. The question is, how do you account for them?
How do you judge your company's success
when in fact you, you, your
lifetime value model shows that a customer's lifetime value has gone
up, but you don't carry, unless you're a subscription business, you don't carry customer
lifetime value. It's on your books, right? So you'll have to
(11:24):
reconcile the inadequate accounting standards that most
businesses operate under today. By the way, I'm not the only one saying
those accounting standards are inadequate. The percentage of companies in
the S&P 500, the percentage of
assets of S&P 500 companies that are now intangible
is far, far higher today. It's something like, something like 80
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or 90% of the S&P 500's assets are
intangible compared to, I don't know, 10 or 20%
25 years ago. Because increasingly
the intangible assets, which are normally goodwill and things like that,
come from the value of the customer base of some company that
the, the S&P 500 company acquired. So if I,
(12:10):
if you were to, if you were to value Google, for
instance, okay, it doesn't have $50 billion
or even $2 billion worth of ping pong tables
and computer consoles. Okay, it doesn't have that. The
value of Google is the value that investors expect
its customers to generate over the, over future time
(12:32):
periods, a discounted net present value of the future stream of revenue
investors expect from the company. And the thing is,
increasingly, it is not true
that the, the return that investors expect
is related to the factories and assets and
inventory in the hands of the company. And increasingly
(12:54):
it's related to the attitude that consumers have. The number
of Customers that are reaching. Out and so forth. So
customers don't figure at
all in. Most companies financial statements. And yet
let me give you just an example. Suppose I have a really,
really good. Customer who calls me with a
(13:15):
complaint and we do a bad job handling a complaint. And at the end of
the call, the customer slams the phone down in disgust.
Now wouldn't you have to say that your company
just lost a smidgen of its value because that customer's not going to come
back. He may even tell other customers not to use.
Obviously your value has gone down a little bit,
(13:38):
but you don't have to report it at all. It has no effect on your
balance sheet. If on the other hand, you have an inventory of
products in a warehouse and they burn down, you have to take that as a
loss this quarter, right? You have to write that down.
So customer assets are not physical assets.
A lot of companies will argue that it's impractical to
(14:00):
govern with lifetime values at the helm of your thinking
because it's impossible to know what lifetime value is. Well, that's
true, but that's exactly the way a stock price works, doesn't it?
Okay. It's impossible to know whether a stock price is
accurate or not. It represents the sum total of
investors at expectations of future revenue. That's all it
(14:21):
is. And as those expectations change, the value of the stock
goes up and down in the market. And we could see that in a physical
market, you know, NYSE or somewhere. There is no
such market for lifetime values. Lifetime value is a
real number. Just because you can't know what it is
doesn't mean it's any less real. Consider this. In 20 years,
(14:43):
okay, companies will be able to decide
that. Mark Slayton, his value in
2025 was X dollars. Because
over the last 20 years he's done all this business. We can just add it
up. That's a real lifetime value. It exists today,
but you can't really know it. You have to approximate it.
(15:07):
So increasingly what I'm advising companies to do is if
you don't have a, a sophisticated
lifetime value model, if you're not a subscription business, you have a problem. Come
up with some proxy variables. What's a proxy
variable? Might be simply the
frequency of purchase. Okay. That kind of thing I
(15:29):
sometimes tell a story about. There's a car wash in
Florida, Speedy Car Wash, whose owner told me
that every time a car goes through, the cashier
has to write the license plate number down along with the tape.
Okay? So they charge him the money and they write the license plate number
down. And he said, what we do with that is every
(15:51):
couple of months I print up a list of the top 50
license plates by frequency. And I give
the first employee who can spot one in the day a
$10 cash bonus. So all my employees have memorized these top
50 license plates. Now, are they the 50 most valuable customers
of the car wash? Maybe not, because it doesn't take account of whether it's a
(16:14):
deluxe inside, outside job or just an outside wash, you know,
but it's better than nothing. Okay? It's
workable. So companies have to come up with proxy
variables like that. I know I'm talking a lot, but let me just give you
one more suggestion. Yeah, sure. One of the critical
issues that face businesses trying to deal with
(16:36):
this kind of marketing is
justifying the current
real time, today cost of a better customer experience
in terms of the customer's future behavior.
Okay? Right. In other words, the problem with managing
customer experience, the biggest problem is the costs occur
(16:58):
now and you can measure them precisely. The benefits are later. You
cannot measure them. You can expect them and you can model them, maybe, but
you'll never be sure right until the future.
And nobody can know what the future is for sure. But you can have a
discussion with the CFO in your company and say, you know, I think
customers that have this sort of profile,
(17:21):
I think we should give them a lifetime value for planning purposes of
$500. And the CFO says, no, no, no, it's not that big.
I say, well, what would you say it is? I 200.
Alright, so how about we agree on 300, is
that okay? So you make an arrangement where you actually
have an exchange rate between how
(17:44):
many points of customer satisfaction it takes to create how much dollar
value for the company among this particular set of customers
and this set of customers. You see what I'm saying? We need practical steps like
that and you need to be thinking financially,
okay, but acting in the customer
experience, benefits side of things. Yeah. So
(18:06):
what I hear you saying are a couple things. One is
that customer lifetime value
is something that we can use to get a gauge
of what the return on investment in CX
is, even though it's not a true accounting metric right to
today. But if we, even if we don't have
(18:28):
it perfect because it looks at cost today and predicts out
in the future what the return is going to be, we can use a proxy
and get good data. And we do have reasonable assumptions. An
economist said that he would consider a stock market
to be reasonably good if at Any point in time,
(18:49):
the stocks in that company were no more than 200% of
their actual value and no less than 50%
of their actual value. Now that's a big range, right?
Huge. You can make the same argument for lifetime values. I don't have to know
to the dollar what your lifetime value is to know that you're worth more than
my senile uncle Gerald. Right. Or than my
(19:12):
kid or than somebody, you
know who's not in the right income bracket.
Right. You know, I don't have to know that. I just
need an approximate level so that we can
agree among ourselves inside the company, what
the economics are of some kind of program that I'm going to run. So thanks
(19:34):
for sharing that. I think that's really important. And you're right, it is a tough
nut to crack for CX leaders who are getting beat up all the
time for not doing a better job of it. And I think
you're right in framing it out that way. That's
really helpful, I think.
Now, now the question I have for you is, as you start to think about
(19:56):
AI or generative AI and its applications
in the world to improve or lift SEACs, what are some
strategies that come to mind for you that business leaders should be thinking about?
Well, the biggest problem that most companies have in implementing
AI or any technology, but
specifically this kind of technology is coming to grips with the cultural
(20:19):
and organizational obstacles to the
success of that kind of strategy. In the same way that most
companies are product managed companies and not customer managed companies,
one of the problems that that creates is that the entire company's
structure is aligned with product sales and
product profitability. And as I said, you can find the people who
(20:41):
are accountable for that. So
if I were in business today and had the gen AI
tools to do better and better with the data,
I would want to set up a structure where I could hold
some executives accountable.
And when I say that, I mean reward them for
(21:04):
increases and you
know, manage them across the quantitative side
of things. I like to hold some accountability, some customers, some
managers accountable for how much value particular
types of customers create for the business.
The product centric market, product centric competition is all about
(21:26):
trying to maximize the profitability of every product,
okay, across all the customers. Now my product meets a certain need. I want to
try to find as many customers as I can who want to have that need
met and sell as many products as I can. I'm managing the
maximizing, trying to maximize. The profitability of each product. The
customer centric organization needs to maximize the Profitability of each
(21:48):
customer. Okay. How can you maximize the value
created by a particular customer? Now, that
value is created by in two things. Okay? It's created when the customer
buys things right now, or if the customer is destroyed when customers cost
you more to serve or whatever. Right? But it also
value is created if I have a really good experience
(22:11):
with you. And so as a result, my likelihood of buying
in the future goes up, so my lifetime value is increased. Right?
So when you think about maximizing the value that customers create, you need to
think about both the customer's lifetime value and increasing that lifetime
value as you think about the
actual revenue generated by the customer in the future.
(22:34):
Problem that most companies have is that
this comes into conflict with return on
investment. Companies think that
the most important measure of success is return on
investment. How much money can I get for the money I have to
spend? But Martha and I wrote a book. Hang on.
(22:56):
We wrote this book,
Return on Customer. We proposed a metric. Think about it this
way. I'm an investor. I buy a stock for
$100, and at the end of the year, the stock has increased in
value to $210. And I also got a $5 dividend. What was my
ROI on that $100 investment in percent. Right.
(23:20):
We argue that you should use the same kind of metric when
trying to measure the efficiency with which you're creating value in your
company through customers. I have a customer's got a lifetime value of
$100 today. And during the year, I get a $5
profit from that customer. And my model says that by the end of the year,
the lifetime value has increased from $100 to $110. Then
(23:41):
my return on customer, my ROC is
15%. Now, here's the thing. Return on
customer, if you look at it at the enterprise level, it's
equal to total shareholder return. Because
at the enterprise level, okay, you're going to look at all
the customer equity you have across all your current and future customers now,
(24:04):
and you want to generate revenue from that, and you want to increase that
customer equity, okay? And the revenue generated, the profit
generated during the period, and the increase in the customer equity,
that's what you put. Over the denominator, the initial customer equity. And that is
equal to total shareholder revenue, total shareholder return.
So return on customer is a much more
(24:27):
exact approximation of
your total corporate. Benefit generated with customer oriented
activities than is return on investment. And so
assuming what I heard is, the first thing is you really need to
reframe the yardstick you're using to measure
Success. And think about it in terms starting
(24:48):
with the baseline of the customer. What are some
strategies that AI affords us that we
should be thinking about to drive those numbers in a positive direction?
Well, I think one of the tools is that it can take
data in the wild and make more sense of it. It's
more likely to make more sense. AI tools can actually compose
(25:10):
their own algorithms to show the relationships.
One of the biggest problems with the statistical quantification
of numbers in the customer area
or in any area really, is it really does
take a statistician to
drill down and try to figure out what's really important, whether
(25:33):
the. Whether you're dealing with a normal curve or a
log normal or some other sort of curve of
statistical relevance. And so the
AI tool can eliminate all that. You can ask it
the question and they'll tell you the answer if it's a good
tool. But it also requires good data.
(25:56):
Now, a lot of companies don't really
have good data. There's still companies out there that can't agree on what the
definition of a customer is. Okay. Like, is the
customer the consumer who's buying my product or the grocery store
I distribute to product through? Right. Because the grocery
store who's paying is paying me, but the consumer is paying the.
(26:18):
So where is the customer relationship? So a lot of companies need to make those
kinds of decisions, like how to. How
to handle fuzzy
definitions and so forth. But
it's not beyond the realm of possibility. It's just
not something that's been a high priority for a lot of businesses. Because
(26:40):
what do I care what customers are worth? I'm just trying to sell this product.
So get clear. Get a clear definition of what is a customer,
and you can get a better vision into how to treat
that customer through the use of AI tools that now exist. Yeah. And by
the way, I think you should think of a prospective
(27:01):
customer as a customer with whom
your current share of customer is zero. Okay.
And your goal is to increase your share of that customer's business. I think
anybody who could buy from you should be considered a
customer or prospective customer. Okay.
And I would argue that when you look at your customer
(27:23):
equity, customer equity is defined as the lifetime values of all your customers. I
think it includes the lifetime values of all your prospective customers as well.
Okay. What's the lifetime value of a prospective customer? Well,
it's their lifetime value if they were to become a customer
times the likelihood that they're going to become a customer. And so
therefore, you can manage that kind
(27:45):
of issue in two different ways. You can
increase the likelihood that they're going to become a customer by increasing
your marketing acquisition, or you
could increase their lifetime values by targeting your acquisition
to a higher lifetime value prospects. You see what I'm
saying? But I think that the definition of customer
(28:07):
equity is not what the lifetime values of all your
active customers are, but what the lifetime value of all your
current and potential customers is.
And that might be. It's easy to think about, it's a little harder to measure,
but it's not impossible. And conceptually it makes a lot of sense.
Yeah, it does. So, all right, so I'm hearing two things. One is,
(28:30):
is think about, number one, reframe it in terms of
customer metrics, in terms of what we're measuring. And two,
understand what the market potential is out there by including
your current customer base or the total customer
equity, but current and the prospective as well. Right, right, right,
right. And there's one more thing I really need to get in here.
(28:53):
Yeah. It's a very important issue, and that
is if my goal as
a business is to maximize the value that each
customer creates for my business. Okay. Then that
inherently means that I should be
working hard to earn the trust of all my customers,
(29:15):
each and every one of them. Because think of it this way, A customer is
likely to create the most value for you when they think you're
creating the most value for them, all the things being equal.
And when is that? When does that happen? It happens when the customer can trust
you always to act in their interest when they don't think that
you're simply telling them something to sell another product. Okay.
(29:36):
When they think that you're giving them advice that's inherently good for
them, they're going to want more of that advice. They're going to want to deal
with you more. So maximizing the value of
customers is exactly in sync with. It's simply the flip
side of trying to treat customers the way you'd like to be treated
if you were the customer. That's all it is. That's all it is.
(29:57):
It's the principle of reciprocity.
But Quantified. Yeah. No, 100%. I think
Charlie Green, who wrote the Trusted Advisor, talks about
first you have to trust in order to be trusted. That's a
huge factor. I couldn't agree more. And Charlie Green had it
exactly right. Yep.
(30:19):
Dawn, I have a follow up question that is
in my mind comes up the idea of influencers. Right. Influencers who
may not. May not actually purchase a lot from you, but can
ultimately help you generate a ton of business. How do
they factor into the equation? How should we pay attention to them?
Well, an interesting study was done of customers
(30:42):
buy the value at a telecom company. They looked at
a consulting firm, looked at the value of customers through
their purchases and customers through their referrals. And what they found
was the highest referring customers are not the highest
value referrers are not necessarily the highest
value buyers. And if you think
(31:04):
about it, it makes sense because if you're thinking about buying from
company A, but you don't know whether you're shrewd or not,
who's, whose advice will you seek? Will you seek somebody who buys
a lot of stuff from company A or would you seek somebody who
you think knows a lot about the category and the problem that you're trying to
solve? Right. So what that says to me is
(31:27):
that if you want to influence the influencers,
you need to focus on generating the
most knowledgeable customer proposition that you can. You want to
focus on improving influencers expertise
and as a result influencing the influencers. You know, you
give them acknowledgement, you acknowledge they're an
(31:49):
influencer, you reference them, you give them information, maybe
even you give them access to your engineers, their thing of
what would your opinion be? The more you can do that, the more you increase
their expertise and the more valuable they're going to be to you,
in my opinion. Assuming you've kept your
product up to snuff. Yeah. And
(32:12):
I guess the baseline for that is you got to know who they are. Yeah,
right, right. That's not hard today. That's really not hard.
So give me one more strategy on how to
differentiate how AI is going to help businesses
differentiate on the experience. The problem that most companies
have, as I said, was cultural or
(32:35):
organizational issues. Right, right.
And if you want AI to
power through those kinds of issues, you have to start
small with pilot projects,
put a few customers in a laboratory, in a sense, do AB
tests. And this side of the business we're doing AI
(32:56):
generated things. And I think over time what will happen is
that the successes on the AI side of
things will generally pay
off. But realize also that even as
you're doing this, customer expectations are going up. The
reason customers don't feel a lot more satisfied today than
(33:18):
they did 20 years ago. And that's true statistically, the average
level of customer satisfaction, despite the fact that 20 years ago, I mean, our
products have dramatically improved in 20 years, we really
have improved. You know, I mean. Right. Could
you imagine when you were 10, taking out some object in
your phone and saying, tell me who the author was. You know, come on.
(33:41):
It's ridiculous. Right. So customer experience has dramatically
improved, but people's expectations are
competitive. Okay. My expectation of you is based on
what my experience was with A, B or C. Right.
And so therefore the more customer expectations
improve, the more customers expect them to. Right. And it's a competitive
(34:03):
battle. What you need AI to do is to
help you be first in
raising the customer's expectation above the static level it is
today. Right. You want to be first and then when it reaches it,
you want to be again and then again and then again. So you
can't rest on your laurels with an AI tool and say,
(34:25):
okay, we're there now. It's not going to happen. It's a
journey. You're never going to reach the destination. It's a direction in which
you're pointing your business. Right. That's the issue.
Good stuff. Good stuff. You know,
so many great gems in here. I pulled a few out already. Some
come to mind. Before I ask you my last question here. Here
(34:48):
you talked about the yardstick. You know, start thinking about measuring
from the customer backward rather than use traditional.
And what's customer equity in your organization? Start thinking
about that. Start identifying your best customers. Right.
And figure out who is worth the extra value
and then give them that value and they'll reciprocate
(35:11):
back. But you've got to do it through trust. Yes, that's
true. And also
it's not just the value by which you're differentiating
customers. Customers are different in two ways. They're different in terms
of their value to you and they're different in terms of what they
need you for. Okay. That's both sides of the value proposition.
(35:33):
What you need from the customer is money. What they need from you is solving
their problem. Right. Each of those things can be
different and different customers. And so needs based
differentiation of customers allows you to
to look at particular types of customers or particular profiles of
customers and understand that I've got five customers
(35:54):
of this profile. They all need this. This other customer looks like this. He's probably
needs this. Right. The same thing. And I think
needs differentiation is also a critical issue that AI can help
in. And also double click on this one for me and make sure I'm thinking
about this. Right. But way back when you and Martha wrote the one to One
future book and you wrote on that, now
(36:17):
we've come full circle with AI and you mentioned early on, near the top
that we're getting closer to that. How close
Are we? We're close, but not there yet.
Martha and I, in chapter nine of the One to One Future was make
money protecting privacy, not violating it.
And guess what? All those big companies out there,
(36:39):
Meta, you know, Google, they all make money by violating
your privacy. They don't make money by protecting your privacy. Now, Martha and I,
when we imagined the world that was interactive, we
thought that probably interactivity would have to be hosted by some
large enterprise. All right, like,
you'd have to go to, let's say, either Google
(37:02):
or Facebook for your thing. But the truth is,
when HTML came into play and the first web
browser came out, the fact that nobody with a website
has to agree for you to be able to see it, Right.
You know, I can go look at it
without your permission. Right. And
(37:26):
if, on the other hand, you. You had to give permission, okay,
then you'd have a. You'd have a moderated interaction.
So all the print newspapers would now be
online newspapers and just as profitable as before because they'd have
subscriptions. The subscriptions might be in pennies instead of dollars,
okay. But it would still be an economic model. Instead,
(37:47):
what's happened is the currency of interactivity is
advertising. And clicks and click throughs. Right? If I can
show that your ad got more clicks, and guess what, guess what incentivizes
clicks better than anything else? Outrage. So is it any
surprise that we have the chaotic system we have
right now? And
(38:10):
so Meta and Google, they make a lot of money
by simply running over your privacy
and not representing your good interest. And I think
that. I think that will eventually change somehow. I'm not exactly
sure how, but when Martha and I wrote that book, we thought we were writing
about a future, an interactive future that was still a decade or two away. When
(38:31):
we wrote the book, we thought that the key barrier
to introducing interactivity was that they'd have to dig
cables to people's homes to put into fiber optic lines. We
didn't think about being able to do all this stuff simply by phone
connection, which turned out to be perfectly fine,
you know, there you are. Well, it was incredibly,
(38:53):
incredibly visionary to think the way you were thinking back then and to
think about the idea that we could have these mass
customization and personalized experiences
that give consumers a better experience at scale.
Yeah. I'll tell you one story. When Martha and I
were working on the book, we were thinking about writing a book about
(39:16):
technology and how it's going to change. And
the editor at Doubleday, who hadn't given us
an advance yet, came back and said, look, I like your concept, sort
of, but I want you to tell us what technology will do to business.
What will business have to do differently because of technology? Okay, so we're thinking
about this. And I, at the time I was president of direct
(39:38):
marketing at Chiat Day, the advertising agency. I was in charge of the direct marketing
and our client for direct marketing, that is for the direct mail,
okay, was the gold Amex card. We
sent letters, we managed all the mail for the gold American
Express card. Ogilvy and
Mather managed all the mail for the green card.
(40:01):
In those days they had the green and the gold. That was it. Right.
But here's the problem with that. And I was talking with
my, my
colleagues, we were trying to solve the problem, how we adjudicate all
this stuff and what the issue was when you
give up your green card and get a gold card. Back in those
(40:24):
days, back in the 1980s, 1990s, you got two
letters from Amex, one from the Gold card people, us saying, wow,
this is great that you've joined us and look at all these benefits. It's great.
And another one from the green card people. Oh, what can we do? How do
we support screw up? What can we do to get you back? It's like
nonsensical to the customer, right? So my
(40:44):
executives and I were around a roundtable and I think, well, you know, what Amex
needs to do is they need to manage their customers, not their cards.
What if we were in charge of certain elite customers and Ogilvy had other
customers? Then wait a minute, manage customers.
And what's the measure of success? Share of customer, not share
of market, share of customer.
(41:08):
And we take products to customers. We don't take customers to the products in the
store. We collaborate with
customers. We don't. And those are the, those became the
chapter titles to our book, the One to One Future in 1993. Things
like, if I read the chapter titles here, manage your customers,
not your products. Share of customer, not share of market. Differentiate
(41:31):
customers, not just products. Engage customers in dialogue.
Take customers. Take products to customers, not customers to products. And chapter
nine, make money protecting privacy and not threatening it. There you go, There you
go. There it was. What a great conversation. Don,
I've got one last question for you. What advice would you give to your 20
year old self? Business advice. I would say
(41:53):
any advice. Any advice?
I would say always assume
that somebody you have a disagreement with has good
intentions, but you just don't understand
why. Maybe, you know, always assume good intentions in
others. I think if I had to give, I've given this advice to
(42:16):
my, my own kids. Assume good intentions in
others and whenever you're about to have a big argument or a big fight,
stop, step back. Assume their intentions are good. What should you
do? You know, how would you deal with that? How could you understand
their intentions? That I haven't heard that one in almost 120
episodes, but it's a true gem and it could probably
(42:37):
save people a lot of heartache, headache and counseling fees. It's
particularly good in today's political environment where intention, where, you know,
sentiments are so diabolically different.
You know, so when I meet somebody who doesn't agree with me politically, I assume
good intentions and, and I try to get at it. We don't always
resolve them, but we have reasonable questions
(43:01):
at least frequently. Excellent. Don Peppers, thank you so
much. It's been such a privilege to have you on the Delighted Customers Podcast.
Thank you. Mark Slayton, thank you very much. I hope you enjoyed
this episode of the Delighted Customers Podcast. It would mean so
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Spotify, Amazon Music, or wherever you listen to podcasts.
(43:23):
Click on the plus sign or follow button and that will ensure that you don't
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forward to seeing you back here next Thursday.
Today's episode is brought to you by Achieve Unite, a global
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Unite is the partner you need for success.
Welcome to the Delighted Customers Podcast. I am so
(00:44):
glad you're here. We challenge conventional thinking about
customer experience because I believe that improving experiences isn't
just good for business. It's a powerful way to make a meaningful
difference in people's lives. Each week we we feature thought
provoking conversations with industry thought leaders from
a variety of backgrounds offering unique perspectives and
(01:07):
actionable insights. Get ready to sharpen your
leadership and transform your approach to customer experience.
Let's dive in.
Well, I am incredibly excited today to have a very special
guest on the show, Don Peppers. And let me tell you a little
bit about Don Peppers before we, before we get started. During the course
(01:30):
of his career, Don has authored or Co authored 11
different business books, collectively selling more than a million
copies in 18 languages. And his first
book, the One to One Future Building Relationships One Customer at a
Time from Doubleday, which he co authored with his business partner Martha
Rogers, which you may have heard Power Peppers and Rogers
(01:52):
before kick started the Customer
Relationship management discipline CRM which has
evolved over the years and has really been absorbed by customer experience
in our field. So this is near and dear to my heart because
I've had the blessing to teach customer relationship management at Michigan State
in the first CXM Master's degree program. And so
(02:14):
you'll have to understand this is extra special episode for
me because you know I have the Tom Brady, the Wayne
Gretzky, the Babe Ruth and Michael Jordan the goat
on the show. And so this is a big deal. This is a big
deal. Don and Martha were inducted into the Data and Marketing
Association's hall of Fame along with their business
(02:37):
colleague Seth Godin. And Don wrote the forward to Godin's
1998 breakthrough book Permission Marketing. Seth
was a guest on the show as well.
And the thing that also connects me directly to Don is he wrote
now in the fourth edition, Peppers and Rogers
released the customer relationship management book
(02:59):
called Managing Customer Experience and Relationships by Wiley. And
if you're watching on video, he's holding up the book
which we'll start using at Michigan State in my class
because it's, that happens to be the class that I teach. So with that long
winded intro. Don, welcome to the
show. Thank you very much. Mark, Delighted to be here. And
(03:22):
let's get started with the meat. Okay. Yeah, let's do
it. So today what I hope we would talk
about is the interplay of AI with
cxm, customer experience management. So if you
would, if we could like level set for the audience,
(03:43):
you know, frame out what we're talking about here in terms of AI and
cxm. Well, the first
kind of computing that prior to AI,
the way a business would
treat different customers differently at scale is
they would use rules, business rules. You know, if
(04:05):
customer does this, you do that, customer does this, you do that.
If this is true, then that and that are true.
But the problem with that is the rules have to be
written somehow. There are software programs and so forth that make
them more accessible, but it's very complicated
and it was never really true one to one
(04:27):
real time marketing. Whereas AI
tools, and particularly generative AI, which gets better and
better and better hold the promise for a company
really being able to treat each customer
individually, even if they have millions of
customers and do it efficiently
(04:50):
with corrections and so forth. So I think
the computing power that's out there now
is going to make the one to one.
Vision that Martha. Rogers and I had back in the 90s
really come true. Pretty much. Pretty much.
(05:11):
And so would you say prior it was more cost
prohibitive and now it's becoming more accessible
because of AI? No, I wouldn't say that that's a problem.
Costs were certainly an issue, but costs went down when we
moved from Oracle and Siebel to cloud
based Salesforce and other cloud based
(05:33):
systems and software. As a service,
data has always been available, but it's been difficult
to validate, verify,
comb through and regularize.
There are all sorts of issues involved that requires manual
(05:53):
intervention. And every time you have an issue of manual intervention,
you reduce the practicality
of treating different customers differently.
AI has its own problems, right? AI
is, it's subject to biases because the
(06:13):
large learning models and other tools databases that
the AI tools are trained on, those databases
themselves are biased. They're biased against particular
races or genders or other things. They're biased
against people of different incomes and depending on how
prevalent your type of person is in the
(06:35):
data that they're looking at and you know, we're dealing with all those kinds of
issues. I think one of the most important issues when thinking about
how to apply general
generative AI to one to one marketing is
protecting the privacy and
being on the customer's side.
(06:58):
Right now a lot of companies out
there, business executives, want to do a better job
of targeting customers. And literally the word target itself
contains the bad idea. Okay? Should never think of
customers as a target. In a truly interactive
world, your customer is a partner in a
(07:19):
relationship that. You want to go on through time. And to be more and more
valuable. But in most companies,
the organization is based on products,
not customers. You know, you could put your hand. On some product that a company's
operating. Or marketing and you can pull the string
and you can find an executive. At that company who's responsible
(07:42):
for that product somewhere. I guarantee you every product company is like that.
But very few companies can. You put your fingers on a
customer and pull a string and find out who at that company has
accountability for that customer's increasing
lifetime value. You see what I'm saying? So it's an organizational
issue as well. I think what we're seeing here is a
(08:04):
form of technology which will demand
different traditions, different
cultures, different sense of mission
on the part of the organizations that are using these technologies if they want
to use them effectively. You need to
constantly look for using these technologies and using
(08:27):
one to one marketing not to build your business bigger,
but to serve your customer better.
Okay? And if you do that, you will build your business bigger. But if
you only concentrate on your business and your costs and immediate
sales guarantee those relationships will never be as strong as they ought to
be. Yeah, and you've been pounding that drumbeat for a long time
(08:49):
about focusing on the customer, right?
But how do you see. Because you use the word like
interact and engage and we used the word
earlier, interplay. How do you see AI helping us
achieve that interplay? I see it in a number of
ways. Number one, I can make an
(09:11):
immediate response from the company in an automated fashion
that is more akin to what an empathetic
human being might do. Number two, and I can
do a better job than, than a simple machine
of interpreting customers
comment or suggestion or
(09:33):
complaint, even to the point of
analyzing their emotional sentiment and comparing it with
the actions that have been taken by other customers with that sentiment
and that type of history. So there's tremendous things that
the AI engine can help you do, but you have to know where you want
to go with it. You have to know what the goal
(09:55):
is. And I repeat, if your goal is simply
to sell more stuff and lower your
costs, you're unlikely to succeed very fast. But
if your goal is to use The AI tool
to deliver better and better service to your customers. You're probably going to sell more
stuff and probably reduce your costs as well. Well, I want to get into
(10:17):
some practical ways that leaders can start to think about doing
that. But before, before we do, I want to double tap
on this, this idea of what's the
big deal. Earlier you mentioned if they treat the customers
right, they will get the business outcomes that they're hoping
for, right? Most likely. Right. And so part of my
(10:39):
question is, are we, are we going to get the business
outcomes through? Because I get asked this question all the time. Am I
going to get this through cost reduction? Am I going to get it through,
you know, referral business? Am I going to get it through revenue
growth? Or is it a combination of all those.
Yes, yes, yes and yes. Okay, you're going to get it through
(11:02):
all these things. The question is, how do you account for them?
How do you judge your company's success
when in fact you, you, your
lifetime value model shows that a customer's lifetime value has gone
up, but you don't carry, unless you're a subscription business, you don't carry customer
lifetime value. It's on your books, right? So you'll have to
(11:24):
reconcile the inadequate accounting standards that most
businesses operate under today. By the way, I'm not the only one saying
those accounting standards are inadequate. The percentage of companies in
the S&P 500, the percentage of
assets of S&P 500 companies that are now intangible
is far, far higher today. It's something like, something like 80
(11:46):
or 90% of the S&P 500's assets are
intangible compared to, I don't know, 10 or 20%
25 years ago. Because increasingly
the intangible assets, which are normally goodwill and things like that,
come from the value of the customer base of some company that
the, the S&P 500 company acquired. So if I,
(12:10):
if you were to, if you were to value Google, for
instance, okay, it doesn't have $50 billion
or even $2 billion worth of ping pong tables
and computer consoles. Okay, it doesn't have that. The
value of Google is the value that investors expect
its customers to generate over the, over future time
(12:32):
periods, a discounted net present value of the future stream of revenue
investors expect from the company. And the thing is,
increasingly, it is not true
that the, the return that investors expect
is related to the factories and assets and
inventory in the hands of the company. And increasingly
(12:54):
it's related to the attitude that consumers have. The number
of Customers that are reaching. Out and so forth. So
customers don't figure at
all in. Most companies financial statements. And yet
let me give you just an example. Suppose I have a really,
really good. Customer who calls me with a
(13:15):
complaint and we do a bad job handling a complaint. And at the end of
the call, the customer slams the phone down in disgust.
Now wouldn't you have to say that your company
just lost a smidgen of its value because that customer's not going to come
back. He may even tell other customers not to use.
Obviously your value has gone down a little bit,
(13:38):
but you don't have to report it at all. It has no effect on your
balance sheet. If on the other hand, you have an inventory of
products in a warehouse and they burn down, you have to take that as a
loss this quarter, right? You have to write that down.
So customer assets are not physical assets.
A lot of companies will argue that it's impractical to
(14:00):
govern with lifetime values at the helm of your thinking
because it's impossible to know what lifetime value is. Well, that's
true, but that's exactly the way a stock price works, doesn't it?
Okay. It's impossible to know whether a stock price is
accurate or not. It represents the sum total of
investors at expectations of future revenue. That's all it
(14:21):
is. And as those expectations change, the value of the stock
goes up and down in the market. And we could see that in a physical
market, you know, NYSE or somewhere. There is no
such market for lifetime values. Lifetime value is a
real number. Just because you can't know what it is
doesn't mean it's any less real. Consider this. In 20 years,
(14:43):
okay, companies will be able to decide
that. Mark Slayton, his value in
2025 was X dollars. Because
over the last 20 years he's done all this business. We can just add it
up. That's a real lifetime value. It exists today,
but you can't really know it. You have to approximate it.
(15:07):
So increasingly what I'm advising companies to do is if
you don't have a, a sophisticated
lifetime value model, if you're not a subscription business, you have a problem. Come
up with some proxy variables. What's a proxy
variable? Might be simply the
frequency of purchase. Okay. That kind of thing I
(15:29):
sometimes tell a story about. There's a car wash in
Florida, Speedy Car Wash, whose owner told me
that every time a car goes through, the cashier
has to write the license plate number down along with the tape.
Okay? So they charge him the money and they write the license plate number
down. And he said, what we do with that is every
(15:51):
couple of months I print up a list of the top 50
license plates by frequency. And I give
the first employee who can spot one in the day a
$10 cash bonus. So all my employees have memorized these top
50 license plates. Now, are they the 50 most valuable customers
of the car wash? Maybe not, because it doesn't take account of whether it's a
(16:14):
deluxe inside, outside job or just an outside wash, you know,
but it's better than nothing. Okay? It's
workable. So companies have to come up with proxy
variables like that. I know I'm talking a lot, but let me just give you
one more suggestion. Yeah, sure. One of the critical
issues that face businesses trying to deal with
(16:36):
this kind of marketing is
justifying the current
real time, today cost of a better customer experience
in terms of the customer's future behavior.
Okay? Right. In other words, the problem with managing
customer experience, the biggest problem is the costs occur
(16:58):
now and you can measure them precisely. The benefits are later. You
cannot measure them. You can expect them and you can model them, maybe, but
you'll never be sure right until the future.
And nobody can know what the future is for sure. But you can have a
discussion with the CFO in your company and say, you know, I think
customers that have this sort of profile,
(17:21):
I think we should give them a lifetime value for planning purposes of
$500. And the CFO says, no, no, no, it's not that big.
I say, well, what would you say it is? I 200.
Alright, so how about we agree on 300, is
that okay? So you make an arrangement where you actually
have an exchange rate between how
(17:44):
many points of customer satisfaction it takes to create how much dollar
value for the company among this particular set of customers
and this set of customers. You see what I'm saying? We need practical steps like
that and you need to be thinking financially,
okay, but acting in the customer
experience, benefits side of things. Yeah. So
(18:06):
what I hear you saying are a couple things. One is
that customer lifetime value
is something that we can use to get a gauge
of what the return on investment in CX
is, even though it's not a true accounting metric right to
today. But if we, even if we don't have
(18:28):
it perfect because it looks at cost today and predicts out
in the future what the return is going to be, we can use a proxy
and get good data. And we do have reasonable assumptions. An
economist said that he would consider a stock market
to be reasonably good if at Any point in time,
(18:49):
the stocks in that company were no more than 200% of
their actual value and no less than 50%
of their actual value. Now that's a big range, right?
Huge. You can make the same argument for lifetime values. I don't have to know
to the dollar what your lifetime value is to know that you're worth more than
my senile uncle Gerald. Right. Or than my
(19:12):
kid or than somebody, you
know who's not in the right income bracket.
Right. You know, I don't have to know that. I just
need an approximate level so that we can
agree among ourselves inside the company, what
the economics are of some kind of program that I'm going to run. So thanks
(19:34):
for sharing that. I think that's really important. And you're right, it is a tough
nut to crack for CX leaders who are getting beat up all the
time for not doing a better job of it. And I think
you're right in framing it out that way. That's
really helpful, I think.
Now, now the question I have for you is, as you start to think about
(19:56):
AI or generative AI and its applications
in the world to improve or lift SEACs, what are some
strategies that come to mind for you that business leaders should be thinking about?
Well, the biggest problem that most companies have in implementing
AI or any technology, but
specifically this kind of technology is coming to grips with the cultural
(20:19):
and organizational obstacles to the
success of that kind of strategy. In the same way that most
companies are product managed companies and not customer managed companies,
one of the problems that that creates is that the entire company's
structure is aligned with product sales and
product profitability. And as I said, you can find the people who
(20:41):
are accountable for that. So
if I were in business today and had the gen AI
tools to do better and better with the data,
I would want to set up a structure where I could hold
some executives accountable.
And when I say that, I mean reward them for
(21:04):
increases and you
know, manage them across the quantitative side
of things. I like to hold some accountability, some customers, some
managers accountable for how much value particular
types of customers create for the business.
The product centric market, product centric competition is all about
(21:26):
trying to maximize the profitability of every product,
okay, across all the customers. Now my product meets a certain need. I want to
try to find as many customers as I can who want to have that need
met and sell as many products as I can. I'm managing the
maximizing, trying to maximize. The profitability of each product. The
customer centric organization needs to maximize the Profitability of each
(21:48):
customer. Okay. How can you maximize the value
created by a particular customer? Now, that
value is created by in two things. Okay? It's created when the customer
buys things right now, or if the customer is destroyed when customers cost
you more to serve or whatever. Right? But it also
value is created if I have a really good experience
(22:11):
with you. And so as a result, my likelihood of buying
in the future goes up, so my lifetime value is increased. Right?
So when you think about maximizing the value that customers create, you need to
think about both the customer's lifetime value and increasing that lifetime
value as you think about the
actual revenue generated by the customer in the future.
(22:34):
Problem that most companies have is that
this comes into conflict with return on
investment. Companies think that
the most important measure of success is return on
investment. How much money can I get for the money I have to
spend? But Martha and I wrote a book. Hang on.
(22:56):
We wrote this book,
Return on Customer. We proposed a metric. Think about it this
way. I'm an investor. I buy a stock for
$100, and at the end of the year, the stock has increased in
value to $210. And I also got a $5 dividend. What was my
ROI on that $100 investment in percent. Right.
(23:20):
We argue that you should use the same kind of metric when
trying to measure the efficiency with which you're creating value in your
company through customers. I have a customer's got a lifetime value of
$100 today. And during the year, I get a $5
profit from that customer. And my model says that by the end of the year,
the lifetime value has increased from $100 to $110. Then
(23:41):
my return on customer, my ROC is
15%. Now, here's the thing. Return on
customer, if you look at it at the enterprise level, it's
equal to total shareholder return. Because
at the enterprise level, okay, you're going to look at all
the customer equity you have across all your current and future customers now,
(24:04):
and you want to generate revenue from that, and you want to increase that
customer equity, okay? And the revenue generated, the profit
generated during the period, and the increase in the customer equity,
that's what you put. Over the denominator, the initial customer equity. And that is
equal to total shareholder revenue, total shareholder return.
So return on customer is a much more
(24:27):
exact approximation of
your total corporate. Benefit generated with customer oriented
activities than is return on investment. And so
assuming what I heard is, the first thing is you really need to
reframe the yardstick you're using to measure
Success. And think about it in terms starting
(24:48):
with the baseline of the customer. What are some
strategies that AI affords us that we
should be thinking about to drive those numbers in a positive direction?
Well, I think one of the tools is that it can take
data in the wild and make more sense of it. It's
more likely to make more sense. AI tools can actually compose
(25:10):
their own algorithms to show the relationships.
One of the biggest problems with the statistical quantification
of numbers in the customer area
or in any area really, is it really does
take a statistician to
drill down and try to figure out what's really important, whether
(25:33):
the. Whether you're dealing with a normal curve or a
log normal or some other sort of curve of
statistical relevance. And so the
AI tool can eliminate all that. You can ask it
the question and they'll tell you the answer if it's a good
tool. But it also requires good data.
(25:56):
Now, a lot of companies don't really
have good data. There's still companies out there that can't agree on what the
definition of a customer is. Okay. Like, is the
customer the consumer who's buying my product or the grocery store
I distribute to product through? Right. Because the grocery
store who's paying is paying me, but the consumer is paying the.
(26:18):
So where is the customer relationship? So a lot of companies need to make those
kinds of decisions, like how to. How
to handle fuzzy
definitions and so forth. But
it's not beyond the realm of possibility. It's just
not something that's been a high priority for a lot of businesses. Because
(26:40):
what do I care what customers are worth? I'm just trying to sell this product.
So get clear. Get a clear definition of what is a customer,
and you can get a better vision into how to treat
that customer through the use of AI tools that now exist. Yeah. And by
the way, I think you should think of a prospective
(27:01):
customer as a customer with whom
your current share of customer is zero. Okay.
And your goal is to increase your share of that customer's business. I think
anybody who could buy from you should be considered a
customer or prospective customer. Okay.
And I would argue that when you look at your customer
(27:23):
equity, customer equity is defined as the lifetime values of all your customers. I
think it includes the lifetime values of all your prospective customers as well.
Okay. What's the lifetime value of a prospective customer? Well,
it's their lifetime value if they were to become a customer
times the likelihood that they're going to become a customer. And so
therefore, you can manage that kind
(27:45):
of issue in two different ways. You can
increase the likelihood that they're going to become a customer by increasing
your marketing acquisition, or you
could increase their lifetime values by targeting your acquisition
to a higher lifetime value prospects. You see what I'm
saying? But I think that the definition of customer
(28:07):
equity is not what the lifetime values of all your
active customers are, but what the lifetime value of all your
current and potential customers is.
And that might be. It's easy to think about, it's a little harder to measure,
but it's not impossible. And conceptually it makes a lot of sense.
Yeah, it does. So, all right, so I'm hearing two things. One is,
(28:30):
is think about, number one, reframe it in terms of
customer metrics, in terms of what we're measuring. And two,
understand what the market potential is out there by including
your current customer base or the total customer
equity, but current and the prospective as well. Right, right, right,
right. And there's one more thing I really need to get in here.
(28:53):
Yeah. It's a very important issue, and that
is if my goal as
a business is to maximize the value that each
customer creates for my business. Okay. Then that
inherently means that I should be
working hard to earn the trust of all my customers,
(29:15):
each and every one of them. Because think of it this way, A customer is
likely to create the most value for you when they think you're
creating the most value for them, all the things being equal.
And when is that? When does that happen? It happens when the customer can trust
you always to act in their interest when they don't think that
you're simply telling them something to sell another product. Okay.
(29:36):
When they think that you're giving them advice that's inherently good for
them, they're going to want more of that advice. They're going to want to deal
with you more. So maximizing the value of
customers is exactly in sync with. It's simply the flip
side of trying to treat customers the way you'd like to be treated
if you were the customer. That's all it is. That's all it is.
(29:57):
It's the principle of reciprocity.
But Quantified. Yeah. No, 100%. I think
Charlie Green, who wrote the Trusted Advisor, talks about
first you have to trust in order to be trusted. That's a
huge factor. I couldn't agree more. And Charlie Green had it
exactly right. Yep.
(30:19):
Dawn, I have a follow up question that is
in my mind comes up the idea of influencers. Right. Influencers who
may not. May not actually purchase a lot from you, but can
ultimately help you generate a ton of business. How do
they factor into the equation? How should we pay attention to them?
Well, an interesting study was done of customers
(30:42):
buy the value at a telecom company. They looked at
a consulting firm, looked at the value of customers through
their purchases and customers through their referrals. And what they found
was the highest referring customers are not the highest
value referrers are not necessarily the highest
value buyers. And if you think
(31:04):
about it, it makes sense because if you're thinking about buying from
company A, but you don't know whether you're shrewd or not,
who's, whose advice will you seek? Will you seek somebody who buys
a lot of stuff from company A or would you seek somebody who
you think knows a lot about the category and the problem that you're trying to
solve? Right. So what that says to me is
(31:27):
that if you want to influence the influencers,
you need to focus on generating the
most knowledgeable customer proposition that you can. You want to
focus on improving influencers expertise
and as a result influencing the influencers. You know, you
give them acknowledgement, you acknowledge they're an
(31:49):
influencer, you reference them, you give them information, maybe
even you give them access to your engineers, their thing of
what would your opinion be? The more you can do that, the more you increase
their expertise and the more valuable they're going to be to you,
in my opinion. Assuming you've kept your
product up to snuff. Yeah. And
(32:12):
I guess the baseline for that is you got to know who they are. Yeah,
right, right. That's not hard today. That's really not hard.
So give me one more strategy on how to
differentiate how AI is going to help businesses
differentiate on the experience. The problem that most companies
have, as I said, was cultural or
(32:35):
organizational issues. Right, right.
And if you want AI to
power through those kinds of issues, you have to start
small with pilot projects,
put a few customers in a laboratory, in a sense, do AB
tests. And this side of the business we're doing AI
(32:56):
generated things. And I think over time what will happen is
that the successes on the AI side of
things will generally pay
off. But realize also that even as
you're doing this, customer expectations are going up. The
reason customers don't feel a lot more satisfied today than
(33:18):
they did 20 years ago. And that's true statistically, the average
level of customer satisfaction, despite the fact that 20 years ago, I mean, our
products have dramatically improved in 20 years, we really
have improved. You know, I mean. Right. Could
you imagine when you were 10, taking out some object in
your phone and saying, tell me who the author was. You know, come on.
(33:41):
It's ridiculous. Right. So customer experience has dramatically
improved, but people's expectations are
competitive. Okay. My expectation of you is based on
what my experience was with A, B or C. Right.
And so therefore the more customer expectations
improve, the more customers expect them to. Right. And it's a competitive
(34:03):
battle. What you need AI to do is to
help you be first in
raising the customer's expectation above the static level it is
today. Right. You want to be first and then when it reaches it,
you want to be again and then again and then again. So you
can't rest on your laurels with an AI tool and say,
(34:25):
okay, we're there now. It's not going to happen. It's a
journey. You're never going to reach the destination. It's a direction in which
you're pointing your business. Right. That's the issue.
Good stuff. Good stuff. You know,
so many great gems in here. I pulled a few out already. Some
come to mind. Before I ask you my last question here. Here
(34:48):
you talked about the yardstick. You know, start thinking about measuring
from the customer backward rather than use traditional.
And what's customer equity in your organization? Start thinking
about that. Start identifying your best customers. Right.
And figure out who is worth the extra value
and then give them that value and they'll reciprocate
(35:11):
back. But you've got to do it through trust. Yes, that's
true. And also
it's not just the value by which you're differentiating
customers. Customers are different in two ways. They're different in terms
of their value to you and they're different in terms of what they
need you for. Okay. That's both sides of the value proposition.
(35:33):
What you need from the customer is money. What they need from you is solving
their problem. Right. Each of those things can be
different and different customers. And so needs based
differentiation of customers allows you to
to look at particular types of customers or particular profiles of
customers and understand that I've got five customers
(35:54):
of this profile. They all need this. This other customer looks like this. He's probably
needs this. Right. The same thing. And I think
needs differentiation is also a critical issue that AI can help
in. And also double click on this one for me and make sure I'm thinking
about this. Right. But way back when you and Martha wrote the one to One
future book and you wrote on that, now
(36:17):
we've come full circle with AI and you mentioned early on, near the top
that we're getting closer to that. How close
Are we? We're close, but not there yet.
Martha and I, in chapter nine of the One to One Future was make
money protecting privacy, not violating it.
And guess what? All those big companies out there,
(36:39):
Meta, you know, Google, they all make money by violating
your privacy. They don't make money by protecting your privacy. Now, Martha and I,
when we imagined the world that was interactive, we
thought that probably interactivity would have to be hosted by some
large enterprise. All right, like,
you'd have to go to, let's say, either Google
(37:02):
or Facebook for your thing. But the truth is,
when HTML came into play and the first web
browser came out, the fact that nobody with a website
has to agree for you to be able to see it, Right.
You know, I can go look at it
without your permission. Right. And
(37:26):
if, on the other hand, you. You had to give permission, okay,
then you'd have a. You'd have a moderated interaction.
So all the print newspapers would now be
online newspapers and just as profitable as before because they'd have
subscriptions. The subscriptions might be in pennies instead of dollars,
okay. But it would still be an economic model. Instead,
(37:47):
what's happened is the currency of interactivity is
advertising. And clicks and click throughs. Right? If I can
show that your ad got more clicks, and guess what, guess what incentivizes
clicks better than anything else? Outrage. So is it any
surprise that we have the chaotic system we have
right now? And
(38:10):
so Meta and Google, they make a lot of money
by simply running over your privacy
and not representing your good interest. And I think
that. I think that will eventually change somehow. I'm not exactly
sure how, but when Martha and I wrote that book, we thought we were writing
about a future, an interactive future that was still a decade or two away. When
(38:31):
we wrote the book, we thought that the key barrier
to introducing interactivity was that they'd have to dig
cables to people's homes to put into fiber optic lines. We
didn't think about being able to do all this stuff simply by phone
connection, which turned out to be perfectly fine,
you know, there you are. Well, it was incredibly,
(38:53):
incredibly visionary to think the way you were thinking back then and to
think about the idea that we could have these mass
customization and personalized experiences
that give consumers a better experience at scale.
Yeah. I'll tell you one story. When Martha and I
were working on the book, we were thinking about writing a book about
(39:16):
technology and how it's going to change. And
the editor at Doubleday, who hadn't given us
an advance yet, came back and said, look, I like your concept, sort
of, but I want you to tell us what technology will do to business.
What will business have to do differently because of technology? Okay, so we're thinking
about this. And I, at the time I was president of direct
(39:38):
marketing at Chiat Day, the advertising agency. I was in charge of the direct marketing
and our client for direct marketing, that is for the direct mail,
okay, was the gold Amex card. We
sent letters, we managed all the mail for the gold American
Express card. Ogilvy and
Mather managed all the mail for the green card.
(40:01):
In those days they had the green and the gold. That was it. Right.
But here's the problem with that. And I was talking with
my, my
colleagues, we were trying to solve the problem, how we adjudicate all
this stuff and what the issue was when you
give up your green card and get a gold card. Back in those
(40:24):
days, back in the 1980s, 1990s, you got two
letters from Amex, one from the Gold card people, us saying, wow,
this is great that you've joined us and look at all these benefits. It's great.
And another one from the green card people. Oh, what can we do? How do
we support screw up? What can we do to get you back? It's like
nonsensical to the customer, right? So my
(40:44):
executives and I were around a roundtable and I think, well, you know, what Amex
needs to do is they need to manage their customers, not their cards.
What if we were in charge of certain elite customers and Ogilvy had other
customers? Then wait a minute, manage customers.
And what's the measure of success? Share of customer, not share
of market, share of customer.
(41:08):
And we take products to customers. We don't take customers to the products in the
store. We collaborate with
customers. We don't. And those are the, those became the
chapter titles to our book, the One to One Future in 1993. Things
like, if I read the chapter titles here, manage your customers,
not your products. Share of customer, not share of market. Differentiate
(41:31):
customers, not just products. Engage customers in dialogue.
Take customers. Take products to customers, not customers to products. And chapter
nine, make money protecting privacy and not threatening it. There you go, There you
go. There it was. What a great conversation. Don,
I've got one last question for you. What advice would you give to your 20
year old self? Business advice. I would say
(41:53):
any advice. Any advice?
I would say always assume
that somebody you have a disagreement with has good
intentions, but you just don't understand
why. Maybe, you know, always assume good intentions in
others. I think if I had to give, I've given this advice to
(42:16):
my, my own kids. Assume good intentions in
others and whenever you're about to have a big argument or a big fight,
stop, step back. Assume their intentions are good. What should you
do? You know, how would you deal with that? How could you understand
their intentions? That I haven't heard that one in almost 120
episodes, but it's a true gem and it could probably
(42:37):
save people a lot of heartache, headache and counseling fees. It's
particularly good in today's political environment where intention, where, you know,
sentiments are so diabolically different.
You know, so when I meet somebody who doesn't agree with me politically, I assume
good intentions and, and I try to get at it. We don't always
resolve them, but we have reasonable questions
(43:01):
at least frequently. Excellent. Don Peppers, thank you so
much. It's been such a privilege to have you on the Delighted Customers Podcast.
Thank you. Mark Slayton, thank you very much. I hope you enjoyed
this episode of the Delighted Customers Podcast. It would mean so
much if you would take a moment to subscribe. You can go to Apple,
Spotify, Amazon Music, or wherever you listen to podcasts.
(43:23):
Click on the plus sign or follow button and that will ensure that you don't
miss an episode and it helps. Get the word out to others. While
you're there. I'd love it if you leave a five star review. I look
forward to seeing you back here next Thursday.
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