“Data: The Ultimate Driver
of Marketing Growth”
by Paul Price
Global President, Rapp
Association of National Advertisers
2008 Annual Conference
Sunday, September 19, 2008
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Slide 1: Data: The Ultimate Driver of Marketing Growth
Thank you, Bob, and our compliments to you and the ANA on choosing
such a prescient topic as growth for this convention. It’s the primary
challenge facing marketers in every era. And at the moment, it seems
less and less under our control.
Fortunately, we have some good news. New technologies and
mathematical modeling are revealing the secrets of growth and
delivering insights that can act as growth springboards. Today we can
map out straightforward steps to increase a brand's control over
growth. We can even make it fairly predictable. These are real
breakthroughs. They are exciting. And they couldn't have come at a
So, this morning I will share a perspective on growth I believe none of
us can afford to ignore — the new competitive advantage of data-
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driven marketing. And I’m delighted to tell you that we have a little
help. In a few minutes our partner Drew Slaven of Mercedes-Benz
North America will be joining me. But in the meantime, I have a couple
of objectives here.
Slide 2: Data is not (necessarily) boring!
The first is to prove conclusively that it is possible to talk about data
without putting everyone to sleep.
Slide 3: Where my money at?
Second, I want to introduce a new concept of marketing that I believe
can make us all more effective, profitable and accountable. A concept
that will help us finally recapture the famous half of the marketing
budget that John Wanamaker, or maybe it was Henry Procter, knew
was wasted but couldn’t identify.
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Slide 4: Adopt some data today!
My third and in some ways most important objective is to convince you
that data can be the best friend any marketer will ever have. Used
well, it delivers invaluable insights, reduces waste, helps you make
better decisions for your brands and, most importantly, drives growth
in a way that is both powerful and predictable.
Now, although we’d all like things to be simple, most things — and
consumers in particular — are not. In fact, if you think about it, with
their intricate neural networks and multilayered decision-making
processes, consumers are a lot like very complex machines.
Slide 5: Image of Robbie the Robot
No, no, not like that.
Slide 6: Image of the Terminator
And definitely not like that.
More like…us. After all, we’re all consumers of something.
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Slide 7: Image of Human Machine
Now imagine that each one of us is filled with countless switches that
respond to every sort of stimulus, from facts to sensory input to the
urges of the emotions. And, making things more complicated, no two
of us are exactly alike in how our switches work.
Whether we’re dealing with humans or machines, our job as marketers
is the same: to inspire a response in a sufficient number of consumers
to create growth. And when we sit down to work out how, the problem
is the same: It’s extremely hard to tell what switches to throw or
exactly what they all do, assuming we can reach them.
What we need is a model, a sort of Google map of the mind. And the
big news is, little by little data is helping us create one. I’ll tell you
more about that in a moment.
But first, let’s spend a minute on how we’ve been making our
marketing decisions until now.
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Slide 8: I feel
For most of marketing history, we’ve had three categories of
information to guide us: attitudes, opinions and behavior. I feel, I
think and I do. Attitude research is certainly valuable — it gives us
general ideas about interests and preferences and a context for more
detailed investigation. But opinions are much less helpful. As many of
us have learned the hard way, consumers are not reliable witnesses
about their future behavior. What people believe about things changes
all the time — just look at the election polls. In some cases, people
probably don’t even believe what they tell us at the time. How else
could “New Coke” or the Edsel have happened?
On the other hand, we are predictable creatures. Once we establish
patterns, we tend to stick close to them. And that means people’s past
behavior is incredibly valuable and helpful — a real marketing
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Slide 9: The Behavioral Data Stream
Marketers have been gathering a widening stream of data on
consumer behavior for decades, but until very recently we lacked an
efficient way to really analyze and use it. Then, in the past ten to
fifteen years, computers became so powerful, so fast, so smart and so
affordable, the world changed.
For starters, computers enabled the arrival of the World Wide Web,
electronic funds transfers, personal electronic devices and other digital
innovations that turned the data stream into a data tsunami. I just
read somewhere that Google has now indexed over 1 trillion unique
URLs — that’s more Web addresses than the number of stars in the
Slide 10: Taming the Tsunami
The good news for us is, expanding computer power also gave us a
way to take all of that data and use it. With the help of cookies and
related technologies, we developed the ability to chart people’s
journeys around the Web and make note of what caught their eye.
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Today, thanks to advances in analytics and modeling, we can convert
that data into reliable insights that help improve the return on our
investments. It’s not quite a Google map, but we’re getting there.
Slide 11: Social Media = Social Data
The latest breakthrough in the effort to track, understand and predict
consumer behavior is a by-product of the rise of social media.
Right now, all over the world, millions upon millions of people are
online sharing their ideas on blogs and forums, sharing news and
gossip on Facebook, sharing photos on Flickr, sharing videos on
YouTube, sharing their most fleeting notions on Twitter, and doing
thousands of other things that tell us not only what they’re up to but
what they are thinking. And all of this activity is generating a vast sea
of data. It is the largest, most organic and most mind-blowingly
detailed focus group ever assembled in the history of mankind.
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Slide 12: Digital Anthropology
To make use of all this data, innovative companies are adding new skill
sets and creating new disciplines. At mine, we’re introducing Digital
Anthropology, which uses the Web as a population base. Our software
sweeps the Web and filters and interprets volume and velocity in ways
that show us how our clients’ brands are faring in online communities.
We scan over three million sources and harvest naturally occurring
conversations. Basically, it’s a massively wild and fast-moving form of
primary research. We entrust that research to our Cultural
Anthropology team, which uses proprietary ethnographic and linguistic
methods to turn data into insights.
Slide 13: image to illustrate customer intimacy
Step back and think about that for a moment. The data we are now
collecting online is allowing us to achieve unparalleled intimacy with
consumers. We know what they are thinking, who they are e-mailing,
who their friends are, what they are buying, what movies they like,
their favorite colors, what they’re planning to do tomorrow…pretty
much anything you might want to know is available. This of course
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places a great responsibility on us to be respectful of people’s privacy.
But it also gives us the ability to establish better, more satisfying,
more loyal and profitable relationships between consumers and our
When we combine this raging tide of online data with more traditional
forms of consumer research, we gain a level of depth and richness that
was unimaginable just a few years ago. And this is no idle exercise.
It’s a discipline that’s already bearing fruit for our strategy teams and
Slide 14: Mercedes-Benz
Here’s a quick example involving our Mercedes-Benz client. Our
company routinely analyzes 100 or more variables for Mercedes-Benz
— things like home value, age and gender and even preferences in
music and pets. This gives us insights we can act upon. And, I confess,
it also gives us facts we find amusing — things like luxury SUV owners
are likely to wear scrubs and dislike cats and classical music!
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For Mercedes-Benz’s new clean diesel SUV line, we recently evaluated
a range of attitudes and behaviors that indicate whether someone is,
or is not, likely to be a luxury SUV buyer. Taking this to a more
granular level, we ran our SUV model on top of Forrester data to
identify SUV buyers with the right attitudes towards technology and
the environment. This allowed us to develop specific targeting
recommendations for a well-defined audience of about 1 million U.S.
households. Drew will get into the implications of this later. For now
let’s just say this is one of the ways data is helping us find growth for
Slide 15: Microsocial Segmentation
Our strategic planners are also developing a new area we call
microsocial segmentation. Stated simply, it is the study of the online
community’s fantastically dynamic consumer segments and cohorts.
People belong to many online communities at once. They move
around, they drop in and drop out. It’s all completely fluid. But that
does not mean it’s unpredictable. We are now beginning to identify
and study segments in this always-changing social setting, looking for
the best ways to tap into consumer advocacy.
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Imagine the possibilities. One day we will be able to identify the most
powerful social influencers and advocates for our clients’ specific
brands. And we will be able to leverage their network influence.
Imagine your brand instantly appearing in global conversations —
persuasively, for free, with the degree of momentum that could be the
difference that creates a market leader. That’s what we’re going for.
We’re developing and testing new analytical models right now.
Slide 16: What’s in it for me?
In the broad area of predictive modeling, we have already achieved a
level of sophistication that yields measurable marketplace
improvements. Let’s take a look at a few real-world examples.
Slide 17: Seeing the future
One of the most fascinating and powerful skills we’re developing with
all this data is the ability to predict what real people — individual
customers — are going to do next. That’s right — we can see the
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future! But instead of gazing into a crystal ball, we use advanced
modeling tools that allow us to analyze data in completely new ways.
Here’s an example. For a marketer of big-ticket durable goods, we had
to consolidate data from 65 different sources to find a way to make
the sales process more predictable. It took us about four weeks. When
we were done, we were able to tell the marketer precisely which
customers were loyal to its brand and which were not. More
amazingly, we were able to predict — within a 30-day window — when
a past customer was likely to make another purchase. This meant we
could forecast with the highest degree of probability both who was
likely to repurchase, and when.
Just imagine yourself sitting in your living room, and you’re looking at
your TV and thinking, “Monday Night Football starts next month. I
want one of those huge new flat screens.” So you go to your mailbox,
and there’s a brochure all about flat screens made by a brand you like.
You might think, wow, that’s a little spooky! But you also might do
what the customers we targeted in our program did: purchase at a
rate almost three times higher than other customers — because our
data told us you probably would.
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Here’s another example, in this case a retailer. Purchase Pathways is a
new analytical tool that allows us to predict with great accuracy when
our client’s customers are likely to make their next high-margin
purchase. To figure this out, we slice and dice massive amounts of
data from 80,000-plus SKUs covering more than 20 standard product
paths. When we’re done, we have a very good idea of what a given
customer will buy next.
It works like this. Let’s say a customer has just bought a new suit.
Purchase Pathways tells us what the next purchase is likely to be — a
wristwatch, perhaps. Based on this information, our client starts
sending that customer offers and messages for watches well in
advance of the purchase. And every communication is personal. We
leverage attitudinal segments and value models to deliver targeted
messages online, offline and in-store.
Since Purchase Pathways was introduced in 2006, incremental sales to
customers involved in the program have totaled nearly $1 billion. This
is what I mean when I say we can now make growth more controllable
and more predictable.
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Slide 18: Increasing customer loyalty and involvement
We’re also using today’s data and analytical tools to increase customer
loyalty with more engaging and individualized solutions. Let me give
you an example from the tourism and travel category.
For one client, cutting data in non-traditional ways allows us to see
which customers will spend enough to qualify for the chain’s highest
loyalty tier. We then assign customers to “value tiers” and increase
investment with profitable segments, and reduce spending in the non-
The chain’s most loyal customers earn rewards based on points and
transactions, but those incentives can only go so far. To truly
transform the loyalty platform, we wanted to create a real sense of
community around the brand. We’ve helped our client do this by
developing a consumer-driven online service. Customers themselves
provide travel tips and then other members rate them. As they
exchange information and content, users are building loyalty and
simultaneously creating new data sets that we can put to work in other
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member communication. To date, over 20,000 customers are working
with this program.
Slide 19: Neighborhood-level solutions
A third really cool thing we can now do with data is figure out what’s
going on with a specific consumer segment and even daypart in a
given neighborhood. We’re doing that right now for a major grocery
chain. And along with studying behavior patterns at a really granular
level, we’re also tapping into the local insights of front-line employees
and store managers.
This particular client had seen its market share erode even though
they had increased advertising spending. The loyalty program they’d
created to help combat the erosion wasn’t doing the job. Our role was
to reduce costs with smarter marketing, use existing and ongoing
loyalty data to create more effective offers, and design specific
solutions for different customer segments.
Our initial analysis put the focus on two basic groups — people whose
spending was on the rise but sub-par in certain product categories,
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and people whose spending was declining. By exploring and analyzing
data in new ways, we were able to develop a multilayered program
with tailored solutions for each group.
One of our innovations was hour-by-hour day-parting of shopping
trends in specific stores. This allows store staff to maximize sales by
setting up appropriate displays and offers at particular times of the
day. Similarly, our analysis addressed customer segmentation by
identifying the most effective triggers and offers for different groups
on a store-by-store level.
The results: Streamlined communications, more relevant offers, a
reduced bonus and incentive structure, greater focus on profitable
private label products and, best of all, growth — a 10 percent increase
in year-on-year sales and a 40 percent reduction in costs!
Slide 20: Mercedes-Benz
One of our most outstanding success stories is with Mercedes-Benz.
Working closely with our clients, we have used data, analytics and
modeling to improve Mercedes-Benz’s direct marketing sales rate by
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50 percent. And at this point I’m going to ask our Mercedes client,
Drew Slaven, to tell you what we’ve done. Drew…
(Drew takes the stage, Paul leaves)
Slide 21: Drew Slaven
General Manager, Marketing, MBUSA
Good morning everyone. And thanks Paul, for inviting me here.
I don’t have many rules that I hold true to when it comes to public
speaking. I do, however, have a few that I never break. And the one
at the top of that list is to be sure I never… ever, under no
circumstances, follow a speaker who has either a British or Australian
accent. Because no matter what I say or how well I say it I will always
come off as a complete bore in comparison.
However, because both Paul personally and Rapp Collin as an agency
have been so helpful to Mercedes-Benz I really couldn’t refuse. So
forgive me, I’ll try to do my best.
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Mercedes-Benz, no doubt, stands as one of the world’s great luxury
But we like to think that beyond the luxury status we are also an
And at its core is a foundation based on over a hundred years of
manufacturing excellence and automotive innovation.
After all, it was Carl Benz, who in 1886 invented and then patented the
very first car.
Since then Mercedes-Benz has led the industry in automotive
innovations. From developing the first crumple zones, to being the first
to install seat belts, to more advanced technologies like inventing the
air bags, anti-lock brakes and stability control systems you will find on
most cars sold today.
And that very same tradition continues to live on. Earlier this month,
for example, Mercedes-Benz introduced BlueTEC, the first clean diesel
system to meet all 50 states’ emissions standards.
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You can then imagine that with such an emphasis on developing
automotive technologies and maintaining state of the art
manufacturing standards that it is those very departments, research &
development and production that receive our greatest financial
commitments year over year.
Now, the upside to this as a marketer of Mercedes-Benz is that we are
in the fortunate position to leverage an incredibly powerful brand in
The flip side, however, is that we often find ourselves competing
against brands from Tokyo and Detroit that have significantly more
marketing budget than we do.
The result of this fact has meant that we have had to adapt our
marketing strategy to overcome this deficit... Said another way, we
simply have to be smarter than our competitors. And at the core of
that strategy is what we believe to be a far greater emphasis on data.
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Data is our competitive advantage… and as a result we know a great
deal about our customers and prospects.
Now to illustrate this I was going to say, purely as an example, that if
you were to step into on coming traffic at the corner of North Rodeo
Drive and Wilshire Blvd in Beverly Hills California you would stand
about a 60% greater likelihood of being run over by a Mercedes-Benz
than any other single luxury make.
But in reviewing my presentation with my PR department they became
tremendously unnerved by mentioning being run over by a Mercedes.
So they took the speech to the legal department and the attorney’s
agreed citing California’s motor vehicle laws which mandate drivers
yield to pedestrians even when those pedestrians are not crossing at
This all became far too much for me so I offered up an alternative
scenario and said, well, what if someone is stepping onto West Grand
Avenue in Haysville Kansas. You see, we haven’t sold a car that was
registered in Haysville Kansas in over seven years. Therefore someone
would stand only a 1 in 6,542 chance of being hit by a Mercedes.
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They thought about that for a while but ultimately concluded that this
was also risky because the average life cycle of a Mercedes-Benz is ten
years and what if, just what if that very same driver happened to be
driving down West Grand Avenue at the time you stepped into traffic….
It was at that point I decided a new approach was necessary and that
I would be better off sticking to some real life examples of how richer
data is helping my company sell more cars more efficiently.
Slide 22: Image of C-Class
My first example relates to the launch of the all-new C-Class, which we
introduced to the public last September. This was a pivotal launch for
Mercedes because the car was designed to expand our owner base by
bringing younger consumers into the brand. With the help of Paul’s
data and analytics, we were able to launch an integrated
communications campaign across print, TV, direct, online and event
marketing that yielded not only a 44% sales increase overall, but
critically a 32 percent sales rate increase with prospects 30 to 34
above and beyond our more traditional 35-to-49-year-old customer.
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Slide 23: Mercedes-Benz Fashion Week image
A second example relates to Fashion Week. As many of you are
probably aware, Mercedes-Benz is the proud sponsor of Fashion Week.
We wanted to leverage this event to increase our share of female car
buyers. Through the use of data analytics we were able to reach a
large group of what we call “fashion-focused females” to position
Mercedes-Benz as the automotive leader in style and design. The
result of our targeted communications… Mercedes-Benz sold 5,263
vehicles to women.
Slide 24: AMG Performance Tour
My final example is around a distinct brand within the Mercedes-Benz
line up called AMG. Known for ultra-high performance and racing
heritage, AMG follows the philosophy of “one man, one engine,”
meaning each engine is literally hand assembled by a single engineer
that then signs and numbers a plate that is welded onto the engine
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The AMG Performance Tour is a unique way to introduce and
demonstrate the exceptional attributes of the AMG brand to customers
and prospects alike.
The Performance Tour includes things like test drives, an interactive
history of our racing lineage, an acceleration simulator and other
features designed to get top prospects behind the wheels of our cars.
Based on our targeted data, we created an invitation tailored to a
highly qualified segment of affluent individuals who have shown a
propensity to shop for brands like Porsche, Ferrari and Lamborghini.
The success of this program can be seen in the results. AMG sales
increased nine-fold among event attendees who purchased a vehicle.
As different as each of the three aforementioned groups are (e.g.,),
what all three of these examples have in common – aside from
impressive ROI – is the ability to use data to reach people with
messages that are relevant to them, and, in the process, the ability to
reduce cost and waste.
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Okay Paul, back to you.
(Paul returns, shakes Drew’s hand and takes the stage)
(to Drew) Thank you, Drew.
(to audience) You know, one of the main reasons why we’re able to
produce results like that for Mercedes-Benz is because we have Drew
for a client. (something personal about working with Drew)
At this point, let’s sum up and, at the same time, take a little glimpse
at some of the ways data will shape the future of marketing. The first
thought I want to leave you with is this one:
Slide 25: Torture the data and it will confess!
Torture the data and it will confess! I realize that may sound a bit
harsh, but it’s true. With the amount of up-to-the-moment data that is
now available to us, there is almost no question about consumer
behavior that cannot be answered with a fair degree of accuracy. All it
takes is the right model and the right analysis.
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Slide 26: The human machine
Those human machines I spoke about are giving up their secrets.
Every day we are identifying more and more of those little switches on
an individual level.
Slide 27: Predictable steps toward brand loyalty
More and more, we not only know what consumers did yesterday, we
know what they are doing at this moment and what they are likely to
do tomorrow. This is huge. It means we can map out the most likely
and effective steps to move the consumer from ignorance about our
products to trial, adoption, loyalty and predictable growth.
Slide 28: Marketing budget allocation demystified
And how about this: We are finally solving the mystery of marketing
budget and resource allocation.
In fact, with that goal in mind, our agency is developing a new
platform for marketing integration. It’s what we call the targeting
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agency. The targeting agency is the marketing partner with advanced
data tools. Behavioral and attitude data, analyzed by anthropologists
and strategists, can already tell us with extraordinary precision what
mix of apertures and content has the best chance of engaging
consumers with your brands. This means that well before any
campaign elements are developed, the targeting agency can help
marketers accurately estimate how to allocate their budgets. We’re
talking about replacing hunches with science.
And this means we can now begin to recover that missing half of the
Slide 29: True Accountability
This also means that, once and for all, we can bring true accountability
to the marketing profession. When TV campaigns are no longer asked
to do jobs shopper marketing can accomplish more effectively, and
when each agency is given the right budget to accomplish its specific
objectives, effectiveness will speak for itself, loud and clear.
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Finally, at this turbulent moment in time, every one of us is facing
more challenges than ever before in driving the growth our
stakeholders demand. As I hope I have demonstrated, data is a
critically important ally in this effort. But data alone is not enough.
Slide 30: Data + Creativity = Growth
Data, when teamed with creativity, is the real key to driving a degree
of growth that once seemed impossible. Now, I know that for some,
data and creativity don’t appear to be natural allies. Up until now data,
has generally been viewed as a sort of creative straightjacket. But
that’s not the case today — or, at least, it shouldn’t be. The intimate,
granular revelations and insights that data provides today have the
potential to act as creative rocket fuel.
By unleashing these endlessly surprising insights with true creativity,
we will have the power to drive growth in any climate.