[APPLAUSE]
PETER FADER: Good
afternoon, everyone.
Wonderful to see all of
you, mostly unfamiliar
faces, a few familiar ones.
And that's great.
It's just really nice to see
a lot of-- not people saying,
oh, it's him again.
A lot of people for
whom some of these ideas
and certainly the
content of our new book
is going to be fresh and new.
So I want to put it all
into context for you.
And then we're all
going to dive in.
So we think about marketing.
We think about what people
say about it, what people
do about it, and it's this.
And it's very troubling,
because so much--
when we talk about marketing,
we talk about the stuff
that marketers do.
We obsess over action.
OK.
It's just all these tactical
kinds of things out there.
But very often lost
in the conversation
is who we do it to, or I'd
rather say who we do it with.
It's almost an afterthought.
We have all of these shiny
objects, many of which
were invented and promoted
right through this company here.
And we're just out
there playing with toys.
And I always found that
very troubling for kind
of obvious reasons as
well as some subtle ones,
that we really want to
spend a little bit more time
thinking about them.
And that motivated the first
book that I wrote back in 2012.
And it was really
nice to get people
to focus a little bit more
on the whole customer thing.
And it was a very nice success.
We sold over 30,000
copies of it.
But even then, it
didn't quite do the job.
You see the problem is
that too many people would
read the title.
They wouldn't read the subtitle.
They'd read the title
and they'd say ah ha.
I know exactly what
you're talking about.
And I fully agree.
It's all about this.
We put the customer at the
center of everything we do.
And that just kills
me, because that's not
what we're talking about.
And maybe it's my fault for
choosing a really bad title,
but it's really less
about the customer
and it's more about
an appreciation
of this wide variety
of customers,
and which ones are the ones
we really do want to focus on.
So again, the book was a nice
way to start the conversation.
But I spent so much of my time
talking about what I don't
mean by customer centricity.
And one thing I
surely don't mean
is that the customer
is always right
and we will do anything for you.
We're going to hire
an army of ninjas
to make sure that
every need you have
is met, every problem
you have is solved.
That's not what
I'm talking about.
But I'm also not talking
about the opposite end
of the spectrum, which is we
got the customers we want.
We got the customers
we don't want.
Let's get rid of them.
Life will be much easier.
OK.
That has problems too.
And again I don't want
to go into the details.
If you want, you can
pick up the old book.
And then maybe the main
point, and the whole reason
I wrote the book to go back
to the research that I do,
is to get people--
to get companies to stop
focusing on the past
and spend a little bit more
time obsessing over the future.
So instead of focusing on
historic profitability,
let's think about this idea
of customer lifetime value.
And is it fair to say
that every one of you,
whether you're working
with these models or not,
at least has those
letters, whether they're
CLV or LTV as part
of your vocabulary?
You know, you're at least
conversant with the [? bait? ?]
That by itself is a
really great thing.
So part of it is overcoming
myths and misconceptions
about what we mean by
customer centricity.
And part of it is we just
didn't go far enough with it.
That book was all
about definition.
It was all about motivation.
It was all about aspiration.
It was just laying out just a
vision of what the world could
look like if we had a magic
wand and you could wave it
over each customer's head.
But it kind of stopped
short of specifics.
And so that's really
where we want to go.
So how do we really
do this stuff?
How do we communicate it
internally, externally?
And how do we demonstrate that
it's actually worthwhile or is
it just another marketing flavor
of the month kind of thing
and it too will pass?
We don't believe that at all.
And so we really wanted
to find ways to really
move this conversation
forward, again
not just in terms of
definitions and motivations,
but in terms of actions.
And so Sarah Toms
enters the picture,
because she and I developed
this really great customer
centricity simulation.
A lot of you have done some kind
of business simulation game.
We have the product.
And let's figure
out with the product
and which segments are
we going to sell it to,
and how much money we're
going to spend on the product.
And it gets back to
all that marketing mix,
4 Ps tactical kind of stuff.
Well, how about a simulation
where it's your job
to grow as profitable a
customer base as possible?
The product is secondary.
The customers are primary.
So that really helped.
That started to move
the conversation along.
But there's still a
lot of room to go.
We're trying every
possible thing,
but we just need broader and
deeper adoption across firms.
And look at all the
different reasons
why people start to
think about this stuff.
Is it, hey, we can make more
money if we have our CLV magic
wand and we allocate our
resources appropriately,
or is it, hey, nothing else
is working for us, and out
of sheer desperation, what
the hell, we'll try that too?
Whatever the reason,
we need to find a way.
And we need to find a
metaphor to try to get
people board with this stuff.
And so all the time
I'm just thinking
about tools, and
models, and simulations,
and stuff like that.
Sarah Toms enters the picture
literally and figuratively
to give us a really nice
way to take the conversation
to a higher level.
SARAH TOMS: Exactly.
So when Pete and I were
writing this book together,
a lot of our conversation
was about the call to action
that we wanted to generate
around customer centricity.
And when you think about this
opportunity and desperation
that really is mounting in
the marketing and sales field,
it reminded me of what
happened in the mid '90s
in software development.
So I entered the tech
field in the mid '90s,
the dawn of dot-com, a
really, really wonderful time
to be an entrepreneur.
I started my first tech company
and, like most entrepreneurs
entering technology
at the time, was
incredibly excited and
ready for the challenge.
The problem was,
in reality, when
I started working
with my clients,
is that the first thing
I would be asked for
is a lot of documentation.
I was following the
waterfall process
like I was being told to.
My tech team was really not
able to deliver in the same way
and to the objectives
of what we were
trying to do as a business.
And one of the problems
with technology at the time
was we were following
old processes that were
quite literally decades old.
They were not fast.
They were not agile.
And they were really
being dictated to us
by bureaucracies such as the
US government who, at the time,
was the largest
developer of software.
So a great example of this
when the Space Shuttle went
into the stratosphere
in 1982, it
had technology on board that was
quite literally from the '60s.
Software took sometimes between
six and two decades to deliver.
And what that led to was the
software development crisis
in the 1990s.
So this is where hardware,
PCs were sitting on desktops.
They were moving into homes.
And software quite
literally could not keep up.
So what we saw here is this
timeline where there were
a few rogue software
development teams who were like,
there's got to be a better way.
They were probably
looking at Deming
and what he was doing
with the iterative
processes in quality assurance
and in manufacturing,
which was more of an
iterative approach, a more
lightweight approach.
And what really
started to happen
with these pioneers
in technology
was they decided that it was
time to all come together
to draw a line in the
sand, or the snow,
because they all came together
in Snowbird, Utah, in 2001,
and they decided to
declare their independence
from the old ways
of doing software.
And here you have
the Agile Manifesto,
which was written in 2001.
Now it's kind of quirky.
And this is still the
website today, by the way.
It looks still
very 1996 or 2001.
They wrote a clear
definition for a vision,
and what needed to be done
in software in particular,
and what was the way
forward for how to develop,
a way that would
be lean, a way that
would bring the
customer or the user
to the center of the design, a
way that was more iterative so
that they could course correct,
and, most importantly, so
that they could communicate
with one another
and also with the business
stakeholders who software
was being developed for.
And this was an amazing
time for all of us
who were in software
at the time when
we saw this manifesto
come to life
and when we started to
see it being adopted.
So stupid question really.
Did agile work?
You guys are all looking at me
like, of course, it did, Sarah.
So here's some study
information from a Gartner study
and other global
studies that have
been done on agile in 2018.
No surprise here.
97% of organizations have
adopted even a small amount
of agile within
their organization.
What we really love-- what Pete
and I are really excited about
is this down here--
is that it's no longer just a
software process or approach.
It's now being adopted
by financial teams,
by middle management teams.
It's been adopted as
a way by lean startup.
It's been adopted as a way
forward to deliver great stuff.
It is product centric.
I will admit that as well.
And of course, I had to put
some Google search results.
Also in these Gartner
studies, when agile projects
are implemented, they're
three times more successful.
For complex projects, six
times more successful.
So clearly this was
the right way to go.
What you see here with
these adoption curves
since the 1900s,
and, if any of you
have been in a marketing class
or in a business class, what
you're seeing is
they're speeding up.
Adoption is faster.
Right here is where
the manifesto happened.
And for a lot of you, you're
probably thinking, well,
it's just processing
power is better.
We're getting better at tech.
But what I actually
believe, somebody
who's been in the technology
sphere now for over 20 years,
is it's really been this shift
in how we create technology
together.
And I believe that
the Agile Manifesto
was that sort of ignition
point, that it was that tipping
point that allowed us
to be able to support
the innovation and now the
adoption that has gone along
with it.
PETER FADER: So let's
take that real story
and now use it as a metaphor
for a kind of the data analytics
customer centricity
thing, because right now,
a lot of companies
believe they're
on the verge of
another tipping point,
because we have so much data.
We have so much computing power.
We have so much
analytical capabilities
that we're just going to
combine all this stuff together
and money is just going to
come raining down from the sky.
We're going to see the same
kind of just breakthrough
in terms of success, not
in terms of hard goods
or services, but in terms
of just our analytical
and customer centric smarts.
Well, that's not
going to happen.
And I've really learned
that the hard way,
because, again, for years,
and years, and years,
I've been going to companies and
saying, here is the CLV model.
Please use it.
And not only is it hard
to get adoption on it,
but even when companies
would adopt it,
so how do we make money on it?
So I really believe it's
less about the ingredients
and more about the process.
And so staying
with this metaphor,
we're talking about how do we
make that process go better.
And so we've had all
these conversations
very often around
the sim and so on.
And so how do we get that
overall call to action?
And of course, it's
up to Sarah Toms
to come up with
the right answer.
Let's create our own manifesto.
And so I'm very pleased--
very, very pleased to present
for the very first time
to an audience here in the US--
are you ready for it?
Drumroll, please.
Good enough.
The customer
centricity manifesto.
So literally taking a
page out of their book,
making it just a
little bit prettier,
and basically coming up with
an organizing set of principles
and then underlying specific
tactical practices, which
is what we're going
to talk about with you
this afternoon, to say
let's all agree on this.
Let's make this happen.
And let's figure out both how
to get buy-in internally as well
as externally.
So we set up a bunch of time.
And I'm being super
honest with you.
We basically had this sim.
We put together the basic
software manual just
to help people play the game.
We said, that's not enough.
We want to help them
play the game smarter.
And again, we realized it
was more than just saying,
here's how you calculate CLV.
It was more about the
mindset that you're
going to take on when you
approach this kind of exercise,
whether it's simulated
or whether it's real.
If you're interested,
you can go to
customercentricitymanifesto.org,
sign the manifesto,
show that you agree,
spread the gospel about it.
And that's what we want to
talk about is to basically take
each one of these four
principles over here
and just bring it to life.
So let's start with this
first one over here, the idea
that we're going to
really celebrate customer
heterogeneity over averages.
So when you start
thinking about, OK,
all right, all right,
I got you, customers
are different from each
other, what immediately comes
to mind is that pain and
suffering that you went through
in your introductory
statistics course,
where that professor-- and
pretty much every professor
since then-- said, everything
follows a normal distribution.
And so stands to reason,
that would be the same thing
with your customers.
You're going to get this
nice, symmetric mix.
You've got the good ones.
You've got the not-so-good ones.
You've got this big
lump in the middle.
And depending on
just how it's shaped,
you might say, you know,
there's so many over here
that we really can
focus on the average.
Well, the problem is
this never happens.
That's just not true.
And it's something that I've
known for quite some time.
But it really,
really crystallized
through my first
startup company,
called Zodiac, that some of
you might be familiar with.
Don't Google it now,
because it's gone.
I'll tell you why.
And basically what
we were doing is
we were working with lots
of different companies,
a wonderful variety of
companies-- products
and services, B2B and B2C,
domestic and international,
big and small.
And we'd just calculate the
CLVs and say, here you go.
Now go make money.
And the distribution
of CLVs that we'd see
would pretty much
always look like this--
very much not normal.
And it's not only
that it's not normal,
but it also gives you a lot of
specific advice and direction,
like who are these
customers over here?
What makes them different
from everybody else?
And how can we find
more like them?
That's what customer
centricity is all about.
And so recognizing the
nature of this distribution
is really critical to kind of
drive you in that direction
and hopefully motivate you to
look for this kind of stuff
and then, of course, act on it.
The bottom line on
the Zodiac thing,
for those of you who don't know,
is just a couple of months ago,
we actually sold
the company to Nike.
And now they're doing just
amazing, wonderful things
with CLV.
Again, a company that
used to be very product
centric, but now doing
just incredible things
by understanding their customers
and doing all the stuff
that we're talking about here.
Got a really nice story for you.
It's more than
just distributions.
It's more than just math.
It's about, how do we get other
people to celebrate customer
heterogeneity?
Did some work with a small, B2B
manufacturer down in Norfolk,
Virginia-- so a very
different kind of company
than a lot of companies that
you would think about when
we're talking about CLV.
And the CEO found
it very frustrating
that after I had this
session and get everyone
all juiced up and jazzed up
about customer centricity,
that he'd listen to
the conversations that
were taking place a day,
a week, a month later.
And everyone was still
talking about the customer,
or the average customer.
He found it frustrating.
And he said, tell you what.
This is what we're going to do.
So he put a fish bowl right
there in the company lunch
room.
And he said, I want
all of you to listen.
I want all of you to
police each other.
And any time you hear
a colleague refer
to the customer in
a singular manner,
and they're not referring to
a singular customer, anytime
you hear people just
talk about the customer,
the average customer,
you call them on it.
You say, I got you.
And they have to put a
dollar in the fish bowl.
And it was a really fun
way to get people to really
think about this one
idea all the time--
nothing about tactical
execution, just the mindset.
And in no time at all,
they had a fish bowl
filled with dollars, very
visible for everyone to see.
And at the end of the quarter or
whenever it was, the CEO said,
you know what?
We're going to have a party
now, using all that money.
And what is it that
we're going to celebrate?
AUDIENCE: [INAUDIBLE].
PETER FADER: Customer
heterogeneity.
So it comes full
circle like that.
And it's just a
clever little way.
I want everyone to go out there
and buy a fish bowl right now,
for yourself or
for your clients.
But it's just a
clever little way
to say, again, it's not
just about geeky math stuff.
It's about figuring out how
to get that message across.
That's our principle number one.
Let me hand things
back to Sarah.
Let's keep on going.
SARAH TOMS: OK, so from
customer heterogeneity,
principle number two is
cross-functional uses of CLV
over siloed applications.
So when Pete and I set
out to write this book,
it was really, really
important to us
that we didn't, again,
create something
that's just going to sit
right in the marketing silo.
This is something that we
need to ignite conversations
across the functional areas.
It's why when you
delve into the book,
we have parts where we're
talking about how you engage
with your technology
teams and you
talk about data, how you work
with finance, how you work
with the other areas
to really start
to get that conversation going,
like Pete's last example,
talking about making sure that
folks aren't thinking just
about the customer.
So what I want to do here
is just share a couple
of really interesting examples.
These are not examples in the
book-- brand new for you folks.
Batteries Plus Bulbs--
no prizes if you
can guess what they sell.
So they have been--
they are here in
the United States.
They are 700 stores.
And they are just a pretty
usual, hard goods, brick
and mortar selling--
what do you think?
Batteries and bulbs.
Exactly.
Good job guys.
So what I like about
this example-- and Pete
and I both know the former
head chief customer analytics
gentleman-- and he
has shared with us
some incredible evolution
of the use of CLV
within their company.
So they started small.
They started experimental.
And it's now grown into being
a cross-functional experience
for them when they think
about their business,
when they think
about their customers
and how they engage with their
customers in different ways
based on CLV.
Higher value customers
are going to want
to be engaged with differently
than their lower value
customers, for example.
So when they have
their customers
coming to them
through their website,
through their call
centers, through retail,
they have ways of capturing
that behavioral data,
so for example, using
a Natural Language
API that's collecting all
of this behavioral data
about their customers.
And they know which
ones are going
to behave a certain way
are more likely to have
higher value, versus
which ones are behaving
a certain way are going to have
lower and middle tiered value.
And all that gets pumped
up every single day
into Salesforce.
And by the next day,
they've created lists sorted
by CLV for their sales force.
Those are now target lists
that they can go after.
And then they cycle
back the performance
of those lists, back
to those various areas.
And they improve on those
algorithms all the time.
So it's a nice
iterative process, where
they're really leveraging CLV.
And not just that-- the company
has been very successful.
They're constantly expanding.
They're looking at mom and pop
shops that they can acquire.
And they use CLV for that.
That's one of their
key indicators for,
where are they going to go?
Which store are
they going to buy?
Which store are they
going to put in?
Second really cool example--
a little bit more exciting,
maybe, for some of you,
than batteries and bulbs
is Electronic Arts.
So gaming company--
we do actually
speak about their origin story
as far as customer centricity.
They are very, very mature
in the customer centricity
space, as far as how
they are leveraging CLV.
Their data analytics
teams are actually
embedded into their
gaming studios,
so that when they
do game launches,
they're feeding back that
game data and those CLV
data, real time, to
the studio developers
and letting them know, were you
successful with this feature?
Were you successful with
this game, et cetera?
So last year in November,
they had "Command and Conquer,
Rivals" was just launched.
And they knew that they
didn't know anything
about really their customer
base when they launched.
And so their advertising
looked like this.
So this was November 2018.
You'll notice that we
have a pretty good gender
representation.
They're playing around
with some imagery as far
as some of the different
weaponry, et cetera.
Fast forward one
month-- they're starting
to collect initial customer
data and information.
By December 2018,
they've started
to make some small
adaptations to that.
You can see it here.
And then by December 2018--
and then-- sorry-- by January
2019, they realized something.
They realized that who
was bubbling to the top
as far as CLV were teenage
boys in North America.
So you'll see here, women
really have fallen out
of being represented
in their ads.
You'll also see that there's
a lot more left-to-right,
because of the
left-to-right reading,
where the call to action
is, et cetera, et cetera.
So this is another great
example of acquisition
where CLV is being leveraged
to help guide the way.
PETER FADER: But
sometimes the best example
is not just getting smarter
about which kinds of customers
to acquire, and how
much to spend to do so,
and where to find them.
But it's what do we do with
the existing customers?
Because this has been a bit of
a mess for a lot of companies,
because companies know what
to do with those existing
customers when it
comes to trying
to make them more valuable.
And they'll ask those two
great American questions,
which you all know so well.
Do you want fries with that?
And do you want to supersize it?
Which of course, we're
using as accurate but kind
of cutesy versions
or proxies for--
AUDIENCE: [INAUDIBLE].
PETER FADER: What's
that top one?
AUDIENCE: Customer
cross-selling.
PETER FADER: Well, got to
be careful about it, right?
The top one is going
to be cross-selling.
People who buy
this also buy that.
And the bottom one
will be upselling.
And the problem
today is that this
is how we fatten up our
customers, whether it's
what they're eating or what
we're presenting to them.
And that's all companies know.
And so we're taking
all of this technology
just to figure out how to
cross-sell and upsell better,
faster, more effectively.
And we're thinking, can't
we do better than that?
Can't we come up with
just different ways
of growing the
value of customers
or growing the value of the
customer base, outside of just
doing old-school stuff a
little bit differently?
So we took a step back and
rethought about these kinds
of tactics, through the
lens, through the mindset
of customer centricity.
And we came up with
two dimensions.
They're kind of
obvious in hindsight.
But they're just not--
they don't show up
a lot in practice.
The first dimension would
be, which kinds of customers
are we talking about
either making more valuable
or just holding onto?
As Sarah has said, and
as it's entirely obvious,
the kinds of tactics
we use should
vary based on
whether we're talking
about really valuable
customers or so-so ones.
That should be explicitly
taken into account, not just
to say which kind of
cross-sell message
we're going to be using for you,
but what kind of overall tactic
we should be deploying.
Different kinds of tactics for
different kinds of customers--
that's number one.
Number two, when it comes to
retention and development,
you get the basic idea of the
right way, which is development
is let's take those
existing customers
and make them more valuable.
Retention is let's hold
onto the customers we have.
But there's a lot of
crossover, especially
in the tactical execution
of those things, where
they start to blur together.
We want to break it apart and
make it more explicit about,
what kind of strategic objective
do we really have in mind?
Are we playing offense or
are we playing defense,
and again, for which
kinds of customers?
So if you take these
two dimensions,
you get what every marketing
professor is contractually
obligated to share with you--
a two-by-two matrix.
And so basically,
we're trying to come up
with an overall
organizing framework
that, again, from the
customer-centric standpoint,
we ask the question,
which kind of tactic
are we going to
use, at which time,
for which kinds of
strategic objective
and for which
kinds of customers?
And I'm not to take you
through the whole thing.
But we just want to
bring clarity, not only
to which tactic are
you going to use when,
but even, what do we exactly
mean by these different kinds
of tactics?
So just as one example,
there's one area over here--
the idea of premium offerings.
You've got these
high value customers.
Don't give them a buy
nine, get one free thing.
I mean, really?
Can't you do better than that?
These are the people
who, for whatever reason,
very strongly identify with you.
They like the products you sell.
They like the way
that you sell them.
They resonate with the
brand, with the people.
For a variety of reasons,
these are the folks
who are going to go through the
gates of hell to stay with you.
And you know what?
They don't mind going even
deeper into the relationship.
They don't mind
paying more-- not
that you want to gouge them.
You don't want to
risk the relationship.
But lots of opportunities,
starting with some of the real
well-known ones, like
LinkedIn Premium--
so how many of you are
LinkedIn Premium folks?
Raise your hand proudly if
you're a LinkedIn Prem--
this is my point, OK?
It is a premium service.
It is not for everybody, OK?
But for those one or two
people who put their hands up,
LinkedIn means a great
deal to you, right?
And so there's lots of
other companies out there
that have been a little
bit too shy to do this.
(PRETENDS TO COUGH) Twitter.
Just don't you think
our president would
pay a premium to kind of--
I'm just saying.
And I'm not joking about that.
There's a lot of people
out there, myself included,
who actually would happily
pay whatever it would be-- $7,
$8 a month--
to get extra
value-added services
that maybe they couldn't
justify offering to everybody.
A recent example
would be Lululemon.
Lululemon recently
announced what the press is
calling a new loyalty program.
But it has a little
twist to it, because you
have to pay a bunch of money
upfront to be part of it.
That's not a loyalty program.
That's a premium service.
So let's bring clarity to
what label we're using,
on which tactic, and at
what time we're using it.
And I'm not going to go into
the rest of the details here.
Read the book.
Page 44-- it's all right there.
But really, using
this as the lens
to look at a lot of the
tactical things that companies
are doing--
customer experience, and
so many other things that
are going on out there--
where does it fit?
And does it make sense
to use it or not?
So that's just
giving you the tip
of the iceberg on a broad
variety of different kinds
of applications of
all the CLV stuff,
that it's going to be more
than just your standard kinds
of how much should we pay
for the customer thing.
There's much more to say.
Point number thre--
this one over here--
we want companies to
choose their metrics very,
very carefully.
See, the problem
is very often, even
companies that are kind of
data-driven and metric-oriented
are choosing the
metrics that reflect
their strategic
orientation, which
means they're very much focused
on, well, volume and cost.
And a really good example that
might be surprising to some
of you is this one over here.
People love this one over here.
So let's look at the world's
most valuable brands, right?
And I can show this
with pride over here,
because you know that Google
is towards the top of the list.
And people just like it.
I could just leave this up
here for the rest of our time.
You could just stare
at it quite happily.
But I actually have a
bunch of concerns about it.
I think they're very
serious concerns.
And I think that
companies are just
obsessing over
this kind of thing
because it's shiny and cool.
But it's not aligned with
customer-centric thinking.
Now, having said
that, I'm not throwing
branding under the bus.
Branding's still
really important.
And that's what I
want to do here.
I want to talk both
about what are the--
how should we be
thinking about metrics,
and what is the role of
branding in the customer-centric
enterprise?
So what are some of my concerns
about this idea of brand
equity?
Number one, I think there's a
bit of a backwards causality
thing going on.
Google was not near the top of
the list back in the late '90s.
It wasn't until it became
a behemoth company,
and then, oh-- then
everyone knows the brand.
It's top of mind--
oh, lots of brand equity there.
So I think a lot of
that brand equity
really just reflects volume,
just the overall size
of the company.
You don't see anyone
showing to you,
here's a chart of the companies
with the highest average
customer lifetime value.
You don't see that one.
And that is what I want
to start to talk about,
to put those kinds of
metrics front and center.
And secondly is this
point over here.
Can we really
measure brand equity
with that kind of precision?
You can go back to that slide.
And you see that
they're measuring
the value of the Google brand
or Apple or whomever else
with six significant figures.
I defy you to find a single
chief financial officer
on the planet who would
say, yeah, I buy that.
I mean, we'll all
agree that the Google
brand is incredibly valuable.
We'll all agree that the brand
and everything that it stands
for could well be worth
on the order of hundreds
of millions of dollars--
hundreds of billions
of dollars.
But could we really specify it
to six or seven decimal places?
I don't think so.
So we have a couple of
objectives over here,
which is to try to come up
with metrics that we really
can trust, that we really can
share across the organization,
instead of just a bunch of
marketers flattering themselves
with it, but also reflect more
about customer equity instead
of brand equity.
In my first book,
I had a picture
that looked kind of like this.
And it basically said, customer
equity is not for everybody.
There are some
companies where it's
going to be hard to measure.
It's going to be
hard to leverage it.
And there's going to be other
companies out there that
are just great at
building terrific brands.
Good for them.
That's fine.
Let them be.
They don't have to do the
customer-centric thing.
But as time goes by, as I
have these conversations
with lots and lots
of executives,
I'm kind of changing
my tune on it,
because I've come to realize
that a lot of the things
that on the surface could
lead to a really strong brand,
but don't necessarily show
up in customer equity--
I don't believe it.
What are the kinds of things?
Oh, we can go out there, and
we can hire great employees.
We can get special tax
breaks and other privileges
from government-- things
that don't necessarily
show up immediately as
more customers buying
more stuff at higher margins.
But if you think about it
over the long run view,
which is what we like
to have, so what if you
can hire better employees?
Big deal.
Good for you.
Unless those employees can help
you bring in more customers who
will buy more often
at higher margins,
there's no equity in it.
So pretty much all
of the things that I
used to say belong over here
really are subsumed by this.
And so the picture
we have in the book
now looks a little
bit more like this.
And so there's a couple of
important points about it.
Number one, that
customer equity is
going to be potentially
larger, that it's
going to subsume all of those
elements of brand equity
and just a lot of the
boring transactional stuff.
Number two, there could still
be some aspects of brand equity
that we don't pick up.
It's just not going
to be that much.
It's not going to
be that substantial.
But important-- number
three is that a huge chunk
of the customer equity will
be associated with the brand.
Having an awesome
brand will enable
you to acquire better customers
a little bit more cheaply.
It will enable you to hold
onto them a little bit longer,
with lower costs to
keep them around.
So branding absolutely
helps maintain and magnify
that customer equity.
It's just that you can't
measure it directly.
It's just folded into
all of the stuff that
shows up in lifetime value.
And so a lot of people
read my first book
and took me as a brand hater,
that he's against branding.
No, no, no, no, no.
I'm just concerned about brand
measurement and the podium
that we put it on.
And so the happy middle
ground that I and that Sarah
have found is this over here.
It's that, as I said,
branding is super hard
to measure by itself.
And in many cases,
it's super hard
to see the specific
effects that it will
have on different customers.
So let's not try to do
all of that measurement.
It's just going
to make us cuckoo.
But it does show
up in so many ways.
And those are important ways.
And so the metaphor that
we like to use over here
is that branding is really the
lubrication for the customer
centricity engine.
You can't do the customer
centric thing as well as
possible unless
you have branding
that's going to help
you do acquisition,
retention,
development, employees,
and all that stuff a lot better.
So it's important.
You need to invest in it.
It's much harder to measure
the ROI on those investments
than it might be for some
direct marketing campaign
or something like that.
You need to run a lot
of experimentation
to figure it out.
But so it's still there.
But it's just an overall
component of customer equity.
We just want to change the
way that people are thinking
about those kinds of metrics
and a few other metrics, too,
that are worth talking
about, some I'm
sure that you're
quite familiar with.
SARAH TOMS: Definitely.
So I want to recognize
the fact that it's not
a new idea, thinking
about your customers
and different-- that
they perform differently,
that they work differently.
This actually was first--
from modern times, anyway--
launched in this book
by Frederick Reichheld.
So he's a Bain consultant--
principal at Bain--
and he wrote this book in 1996.
And it's called "The
Loyalty Effect."
And what he wanted
to do in this book
is explain that
there's a mechanism.
There's a way that
customers behave.
And really, instead of trying
to push as much product
blindly to as many faceless,
nameless customers,
what you should be
doing is looking
at the behaviors
of your customers,
learning what those
are, and then working
to really reduce the friction
in that relationship.
And what happens when
you reduce the friction
in the relationship, especially
with your higher value
customers, is you
grow their value.
And when you grow
their value, you
reduce the cost that they cost
you to have as their customers.
And as you reduce the costs,
you have this virtuous cycle
start to happen, where
the next thing you know,
they see you as a
trusted advisor.
And they're going
to start referring
other customers to you.
So in this book,
Reichheld really
was aiming to just describe
that this mechanism exists.
It's different for different
types of customers.
And it was really that
first seed of an idea
that I think was going
to eventually lead
to customer centricity.
So in his first
book, he was really
aiming to explain the
nature of customers.
And then fast forward
to 2006, and he
released this book,
"The Ultimate Question."
And what he was
driving at in this book
was really understanding
how to measure that.
And so I'm sure you'll
not be surprised to see
the measurement being
net promoter score.
So I know that there are
probably a lot of detractors
in here as far as NPS goes.
There definitely
are some haters,
and we want to recognize that.
But the reason Pete and I liked
this was this was first time--
NPS really was one
of the first times
that it elevated this idea
of customer differences
in sort of our business sense.
So let's look at NPS through
a customer-centric lens.
So some of the reasons
Pete and I like NPS--
number one, it celebrates
customer heterogeneity.
Number two, it gives an elite
status to the promoters.
So in the equation, the
promoters definitely
have an elite status.
Third, it's simple.
It's an easy way to
have a conversation
about your different customers.
And it's an easy way to evaluate
them, and slice and dice,
and look at them across
different segments
to really understand
your customers more.
Now again, we recognize that NPS
has been implemented blindly.
Pete and I would probably
complain about things
like it's been
implemented too narrowly.
There are ways that it could
be looked at beyond referral.
And really the biggest
problem with NPS
is it doesn't take
into account value.
So it's missing a key
component of that relationship
with the customer.
PETER FADER: So NPS is a great
step in the right direction.
And really, understanding the
interplay between NPS and CLV
is a great area of research
that's going on right now.
But it really does
get to this idea
that, OK, it's one
thing to come up
with the right
metrics that reflect
customer-centric practices.
But it's a whole other
thing to figure out
how to get them out there,
so people believe you
that you really are
doing this kind of stuff
and doing it well.
And you know what?
We understand that maybe you're
not maximizing your profits
this quarter.
But by doing the
right things in terms
of customer centricity, that
it's going to be so well worth
it in the long run.
So let me just go
through this fourth point
with a very interesting and
very contemporary case study.
You all know Wayfair--
online furniture company.
It's another good news
and bad news story.
First, from Wayfair's
perspective, the good news.
Look at those revenue numbers--
everyone's dream come true,
that hockey stick convex curve,
revenues through the roof.
My concern, going back
to point number three,
is that this just
reflects overall volume.
I want to know more about the
quality of those revenues.
Instead of just saying
how many dollars
are flowing in the door,
I want to understand
the nature of the customers who
are bringing in those dollars.
I mean, you have to
believe that a sale
to a new, unproven
customer is going
to be different in terms
of lifetime value enhanced
than the fourth sale to someone
who's been around with you
before.
So let's peel that apart.
And one of the problems
is, with most companies,
it's just impossible to do so.
How would you be able to
take all of this revenue
and decompose it into the CLVs?
Well, one of the things that
I give Wayfair a lot of credit
for is that they make it easy.
So if you look at their
own financial statements--
this is a paper that I
wrote with Dan McCarthy.
We're basically using
data from Wayfair
and from another
company, overstock.com,
that you might know,
that also reveals
a lot of really
interesting metrics--
the right kinds of metrics
that external stakeholders want
to see and should demand to see.
Well, here's their data.
So in addition to
giving us revenues--
OK, fine.
That's not surprising-- they
give us a lot more metrics,
like how many customers
did we add this quarter?
OK, that's not that surprising.
A lot of companies will
give us that kind of metric.
But again, it's not required.
Accounting Standards Boards
don't say anything about that.
Some companies just voluntarily
choose to put that out there.
This might help you
understand us better.
But it's the other two metrics
that really make them unique.
You can see them right here.
One of them is QTO,
Quarterly Total Orders.
They are telling us how
many orders are being placed
on their website every quarter.
This is all public data.
And the last one over here--
AAU.
I bet you can
guess what that is.
What is AAU?
Annual Active Users.
Again, I take your
silence as a sign
that we have a long
way to go here.
We really want to make
these kinds of metrics part
of the everyday vocabulary.
And we're not just
waiting for some companies
to charitably provide them to
us for reasons I don't even
understand, but for
investors, for analysts,
for marketing professionals
to demand them,
so we can really understand
how those dollars are working.
Here's the cool part about it.
You give me these metrics.
Or you can give them
to Dan McCarthy.
This was part of
his dissertation.
And I can peel back
the onion and look
at the nature of
heterogeneity of this company,
almost as accurately as if I had
the raw transaction log data.
Now for Wayfair, I don't.
And they're not going
to give it to me.
They don't like me
very much over there.
You'll see why.
But that's what we're going to
do is instead of just saying,
here's revenue
today, this is what
revenue is going to
be tomorrow, we're
going to peel it all back.
And let's understand
the components--
the customer-centric
components of revenue.
So let's forecast how many
customers will we acquire?
How long will those
customers stay with us?
How many transactions will
they make over that horizon?
And how valuable will
those transactions be?
I hope you agree with
me on two things.
Number one, those would be
really good things to know.
Again, as an outside
evaluator of the firm,
you got to tell me that.
And number two, if you add all
that stuff up, that's revenue.
So we're going to come at
revenue from the bottom up.
So we're going to take all
of this data in these columns
that you see over here,
and we're going to model it
through May of 2017.
And we're going to
show how well we can
capture all of these patterns.
So here is how many
customer we've added.
Here's the total orders.
Down here is revenue.
But I want to
emphasize that we're
not modeling revenue directly.
That's what the people
on Wall Street do.
We're modeling--
here we go again--
how many customers are
we going to acquire,
how long are they're going to
stay, how many transactions are
they going to make, how valuable
will those transactions be,
and then combining it
all together to say,
that's what we think revenue is.
OK, so we're deriving this.
We're not modeling it directly.
And we're doing a
pretty good job of it.
Gives you a good feeling
in the belly that we could
take this curve-- we can take
these underlying components
and project them
out into the future.
And we can project
them out pretty far.
And then we could do a little
bit of accounting stuff
to turn it into an overall
corporate valuation.
So that's what
we're going to do.
So on the next slide, I
want to point out two things
before I dazzle you with it.
Number one, we're going to
start with this curve over here.
We're going to say,
all right, look.
We've captured revenue
through May of 2017.
Let's go beyond it.
So you're going to see that
curve all compressed and 50
years to the right of it--
50 projected years.
Number two, we recognize that
not all models are perfect.
It's just that some
suck less than others.
And so we're going
to acknowledge
that there could be errors
in each one of our models.
So we allow for each
one of our curves
to be slightly different.
So I'm going to show you
several hundred-- maybe
several thousand-- different
trajectories that Wayfair's
revenue could take on.
And here it is.
There's the revenues
through middle of 2017.
And there's a very bleak future.
We give this company a lot
of credit for its successes
to date and for the
metrics that they share.
But it is not a pretty picture.
Their acquisitions are growing
too fast and too expensively.
They're acquiring a lot
of very bad customers.
And they're not-- they haven't
established enough of a base
of repeat buying that when
acquisitions level off,
which they will do--
they must.
Usually what happens with most
companies is when acquisitions
peak, there's enough
established base
of ongoing repeat buying that
you don't even notice it.
I mean, did any
of you notice when
Amazon's acquisitions peaked?
Nah, because the repeat
buying was so high
that it was all good.
This company will crash.
It might crash this year, as
some retail experts are saying.
It might crash in--
I don't know.
Our best guess is
sometime in the mid 2020s.
I don't know.
But they're just imbalanced
in their allocations.
And, well, let's take
each one of these numbers
and turn it into a valuation.
Here we go.
In May of 2017, the company
was trading for $65 a share.
We come up with a mean
stock price of $10.
And we're right.
Well, time will tell.
Interesting to see that this
simple academic paper had quite
an impact on the stock price.
In September of 2017, the stock
was trading in the mid $80s.
The day the paper
came out, Wayfair
had the biggest drop
in its stock price
in a couple of years.
And it just kind of kept
on going from there.
And it's just really
interesting to see the way
that people picked up on
it, including our own Philly
guy, Jim Cramer.
[VIDEO PLAYBACK]
- say, the [INAUDIBLE]----
he's really into this one--
struck again when he tweeted
his support of an academic paper
published by professors at
Emory and the University
of Pennsylvania, calling it
the smartest piece ever written
on Wayfair.
It did the job, causing Wayfair
to plunge from $83 to $70
as of today.
What was so devastating about
a high level academic paper?
The professors tried
to come up with a way
to pin a value on Wayfair's
current and future customers,
based on how many--
on how much they make from these
customers versus how much they
spend to acquire them.
[END PLAYBACK]
PETER FADER: Let's think
about this for a second.
Let me just kind of
tone it down, Jim.
[LAUGHTER]
The professors said
that they're going
to figure out the
value of the company
by looking at the
value of the customers
and the cost of acquisition.
What's your reaction to that?
I'll tell you what your
reaction should be.
Your reaction should be, duh.
That's how every company
should be valued.
Instead of just looking
at this almost meaningless
overall revenue stream,
let's decompose it
into the stuff that
really matters,
that really reflects what
this company is all about,
and build it up from there.
And so that's the kind
of thing that I've
been really pushing, both--
primarily as a way just to
make the customer-centric thing
happen.
But here's my new startup.
If you're interested in this--
and I'm not here to sell it--
but if you're interested in some
of these ideas about how we can
revolutionize finance through
customer-based corporate
valuation--
to basically take these
principles of customer
centricity and bring them to
a very different audience,
to get the CFO and the VP of
investor relations on board
as well, to say, tell me
more about those methods.
And hey, you guys
in marketing, you
might want to see
these models over here.
They're kind of interesting.
That's the conversation
that I want to create--
and so far, so good.
And I hope it's been so far,
so good for all of you as well.
Those are our four principles
of our customer centricity
manifesto.
Let me hand it over to
Sarah to wrap it up.
And we'd love to get
some questions from you.
SARAH TOMS: Awesome.
Thanks, Pete.
OK, so beyond the
manifesto-- just
some quick, quick
takeaways for you.
So we'd like you to join the
customer centricity revolution.
That's why we wrote the book.
We hope you'll read the book.
It's really little,
easy to carry around
in your pocket, and
a nice quick read.
But really, our goal
was, like I said,
is to distill these ideas and
provide that call to action,
and not be in that
academic sphere--
although it is grounded in
academic research and also
business research--
but to give a clear
roadmap for how
to implement customer
centricity in your organization.
Second, we'd love you
to sign the manifesto.
Third, integrating the
essential frameworks
that Pete and I have been
talking about here today, also
in the book.
Also if you google
Pete Fader, of course,
there are plenty of
other pieces where
he's providing advice that would
be incredibly useful for you
to follow into your
everyday business practice.
The one thing that I
found really interesting
in this journey of
customer centricity--
I've had the
opportunity to interview
a lot of folks in
the business world
when we were putting
the book together--
Pete and I are writing
articles, currently--
also putting this
presentation together,
is every single
organization that I've
spoken to who are now mature
in customer centricity,
they all started small.
They all started with
teeny tiny experiments.
Often it was actually middle
managers or data scientists
who had an inkling that
something wasn't quite right.
And there was ways to define
and fine tune their strategies
around customer lifetime value.
When I talked to the folks
over at the LA Dodgers,
they actually made a lot of
mistakes for a number of years
when they were trying
to experiment with CLV.
But those mistakes really
have helped them now
where they are with their
use of CLV in their business.
So it's really interesting.
And this is-- a key point
is living it, experimenting.
Our call to action in the
book is quite literally
diving in and just
start getting to work.
And then last but not least--
so I lead the simulation
team at the Wharton School.
The simulations really hold
a tremendous amount of power.
They provide folks
with an opportunity
to roll up their sleeves.
Think about something
like a simulation--
a way to bring your
teams together and really
experience what
it's like, becoming
familiar with
customer centricity,
and laying out that roadmap.
And so when Pete and I reflect
on where we've come from
and where we're
going, we really hope
that something
like our manifesto
is going to remove
this question mark.
And we are going to
see customer lifetime
value become a common metric
in every single business.
And it will become a way to
really drive strategy forward.
So I want to thank
everybody for coming today.
Do you have any
closing remarks, Pete?
PETER FADER: No.
We'd love to get your
questions and comments, though.
SARAH TOMS: We would
love to get questions.
Yes, we would.
PETER FADER: Great.
[APPLAUSE]
All right.
We've got a couple
of microphones here.
What do y'all think?
Please.
AUDIENCE: Thank you so much.
That was a very, very
interesting approach.
We really appreciate it.
I do have a question.
You mentioned the customer
centricity components
of revenue.
Any advice that you
can give us in terms
of how to lead
those conversations
with the customers,
given that we have
so many variety of them,
and their business models
are very different?
What would be a couple
of key questions
that we can ask our clients
to identify those components
for their business models?
PETER FADER: Sure.
I really have to say that
moving the conversation
over too early-- starting the
conversation with the folks
in finance and then kind
of backing into marketing
has been incredible, to get
that kind of a broad buy-in,
and especially from an audience
that's not as afraid of models
and forecasts and so on.
So here's the question.
Do you want to know what
your company is worth?
I mean, it's as simple as that.
Most of the time, we're working
with private equity firms,
late-stage VCs, who are
looking at a company they
want to acquire.
But it becomes
really interesting
when we're looking at a company,
and they just know internally
that they're really worth a
lot more than the market seems
to be saying.
And they can't quite come up
with that rationale for it.
So they'll turn to
us to say, so what
are we really worth in terms
of the value of our customers?
So they can come up
with the number--
hopefully higher than
what Wall Street thinks--
and then make a whole
big deal about it,
not only that the number is
higher, but to explain why--
that we've actually been
acquiring more customers.
They're staying around
longer than you think.
And again, that
translates directly
into the marketing and other
operational kinds of issues.
So I really think that sometimes
starting on the finance side
or maybe doing that at least
in parallel while you're
doing the less unusual,
but still difficult,
marketing tactics--
but bringing it all
together, I think,
is a very, very convincing way
to say that this stuff's real.
AUDIENCE: Thank you, Peter.
SARAH TOMS: Any other questions?
PETER FADER: Look, I'm in
teaching mode right now.
I will cold call.
So--
AUDIENCE: I have a question.
PETER FADER: Please.
AUDIENCE: So I think if there
was the anti-book for this,
it would be "How Brands Grow."
Are you--
PETER FADER: Oh, no, no, no, no.
AUDIENCE: So yeah.
So could you reconcile
those two areas of thought?
PETER FADER: I can.
And of course, I can get into
a pretty technical explanation
of it.
But I won't.
If you don't know "How
Brands Grow," by Byron Sharp,
I actually highly
recommend it, because--
he doesn't talk about the
models or anything like that--
but the models that
I'm talking about
are very, very, very
similar to the models
that are underlying a
lot of his principles.
So I actually agree with
most of what he's saying.
I agree with the
idea that when you
have that incremental
dollar to spend,
Byron Sharp says,
grow your base.
You must have more buyers.
I agree, but for a
different reason.
I say, let's focus
more on acquisition.
Let's go out there and find
more valuable customers
and not worry so much
about trying to fatten up
the ones that we have.
So it's actually a lot
of alignment with it.
Now there are some differences.
And I have the ultimate
love-hate relationship
with Byron Sharp.
And just to kind of summarize
the biggest difference,
the CLV distribution
that I showed--
the fact that we got this tail
of people out there that sticks
out--
I was going to say, like a
sore thumb, but a very healthy
thumb--
he doesn't really
believe in that.
He believes that-- it's not so--
he believes in
heterogeneity, but not
that there's as
much of a skew to it
as we see in the actual data.
So a lot of my career has been
taking the kinds of models
that Byron Sharp and other
folks have been building,
and then adding slight
little bells and whistles
to them to capture reality
a little bit better.
So the basic fundamental
principles-- double jeopardy,
all that kind of stuff--
holds.
But there's actually more to it.
And then it leads to
other kinds of advice.
So we're actually-- it
might seem surprising.
And I don't blame you
for thinking that way.
But there's a surprising
amount of alignment there.
AUDIENCE: Great.
Thank you.
PETER FADER: And I will even
say that as we were pulling this
together and I was trying to
get Sarah into this world, one
of the early things that I did--
maybe one of the first books
I pulled off the shelf
was that red-covered book.
Say, you got to
read this one, too.
AUDIENCE: Awesome.
Thank you.
SARAH TOMS: Thank you.
So we have a
question here from--
I'm not sure where.
But I'll read it.
"Is CLV reserved to
relatively large companies
with a lot of
resources, or is it
applicable to small
companies as well?"
So Pete, do you want to
take a stab, or you want--
PETER FADER: Go for it first.
SARAH TOMS: OK.
All right.
So what we think here is that
these are universal principles,
for sure.
When you're thinking
about your customers,
it's also-- one thing you
have to be worried about
is the over-investment, right?
So if you're over-investing in
customers that really aren't
worth it, that's something that
will happen to you regardless
of the size of your company.
The other thing that
we work really hard
at in the book-- in
fact we've structured
the book in such a way
that we're talking-- we're
trying to train your eye to
look at acquisition, retention,
development, and
then understand time.
There's a time
component to that--
where you are in the
maturity of your company,
whether you're large
or small, and how
that changes your tactics.
We're talking
about being nimble,
about experimenting
like I said before,
about testing your hypotheses.
And these are
principles, especially
in the era of data
that we're in,
that are applicable whether
you're large or small.
PETER FADER: And let me just
add to that, because in an era
where everyday we're talking
about the retail apocalypse
and all this kind of thing, I'm
actually very hopeful about it.
And I think that the future
rises from the small companies.
Those digitally-native,
direct-to-consumer companies,
many of which are
right around here--
I don't want to say that they're
textbook customer centricity
examples.
But they're are a heck of a
lot better than their older,
bigger, slower brethren.
And so again, implicitly
or explicitly,
they're starting to embrace
a lot of these ideas.
They're starting to tag and
track customers, calculate CLVs
a lot earlier than
traditional companies would.
And what's happening is
those big old companies
are starting to take them
a lot more seriously.
Instead of dismissing them as
a passing fad or just a little
teeny tiny niche,
they're saying,
we can learn a lot from them.
You know what?
Let's hire some of them to
start running our marketing
or our whole company.
So I think a lot
of these ideas are
kind of working their way up.
And sometimes it's the little
companies leading the way.
Rodney.
AUDIENCE: Hey, hey.
Hi.
Thank you guys both for today.
Kind of related to
that last point--
is there a certain threshold--
not so much size of company--
but maybe threshold
of data that you need?
So for instance, do you need
5,000 customers or 5 million?
Do you need two
years, three years,
or five years of
transaction data
to actually make
that model work?
What's the thresholds?
Because that will
definitely tell us.
It may be a small company
growing very rapidly.
But then you hit a certain
threshold of customers,
but you don't have enough
years or enough data
to actually make the model work.
Any thoughts or comments?
PETER FADER: Absolutely.
I sort of almost implicitly
answered the question
when I was talking about
the kinds of companies
that we work with on
customer-based corporate
valuation.
I said, late-stage VCs.
You can't really do it
at the early stages,
for exactly the reasons
you pointed out,
that you don't have
enough customers to really
see or estimate that
full CLV distribution.
And in terms of the length
of the runway that you need,
it's kind of
interesting that I don't
need a long runway of data.
I need enough customers.
But I don't need a
long amount of time
in order to estimate
these models.
But I still don't
really trust them
until I have about
two or three years.
And why is that?
Because one of the issues
that we haven't spoken about--
but we make a big deal
about in the book,
and I can't say enough
about it in practice--
are cohorts of customers.
We always run these models for
a given group of customers,
generally who we acquired
at the same time.
And the issue is that the
cohorts are not all created
equal, and that as
we go over time--
so we get that first cohort
of customers we acquired soon
after we were founded--
they tend to be much
better customers.
And so we don't want to just
calculate CLVs on them and say,
we're an amazing company.
Let's raise some more capital.
So we need enough time to see a
bunch of the different cohorts.
We have to play connect
the dots across them.
We've got to watch them start
to stabilize a little bit,
so we can anticipate
what the subsequent
and the steady state, mature
cohorts are going to look like.
So yes, we do need
enough customers
to see the heterogeneity.
We do need enough of a runway to
see the cross-cohort dynamics.
And obviously, we do need
enough cleanliness of data
to trust those results
in the first place.
Sometimes these models
that I endorse--
sometimes they're too
good, that they'll
work really well even when
you put in crappy data.
And it gives you this false
sense of security about it.
So all the issues you raised
are right on the money.
And with that in
mind, I recognize
that most companies aren't born
to do customer centricity right
out of the gate.
They're going to be born
around a particular product.
We just want them to
look ahead and start
doing all that
tagging and tracking,
because two, three years
later, maybe it's time
to do that pivot towards it.
But it's going to
take some time.
AUDIENCE: Great.
Thank you.
PETER FADER: Sure thing.
We don't want to hold
people hostage here.
See if there's time for
any other pressing issues.
If not, you got our
contact info over here.
And we are absolutely delighted
to keep the conversation going.
As I said before, this
really is the first time
that we've presented
this content.
The book's only been
out for a few weeks.
So we're very much open, not
only to questions but feedback.
And just tell us how we can
spread the gospel of customer
centricity and how we can help
you do it more effectively as
well.
So with that, I
want to thank Neil
and the rest of
the team over here
for giving us this
opportunity, and for all
of you for taking the time.
And best wishes on your
customer-centric journey.
[APPLAUSE]
