2008 ANA Masters of Marketing Speech

“Data: The Ultimate Driver

of Marketing Growth”

by Paul Price

Global President, Rapp

Association of National Advertisers

2008 Annual Conference

Sunday, September 19, 2008

Paul Price ANA Final Page 2

Slide 1: Data: The Ultimate Driver of Marketing Growth

Good morning.

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

better time.

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-


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.


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.


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.


Slide 8: I feel

I think

I do

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

goldmine.


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

Milky Way!

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.


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.


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


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

brands.

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

their clients.

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!


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

our clients.

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.


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


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.


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.


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-

productive ones.

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


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,


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


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.


Mercedes-Benz, no doubt, stands as one of the world’s great luxury

brands.

But we like to think that beyond the luxury status we are also an

authentic brand.

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.


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

communications.

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.


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

crosswalks.

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.


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.


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

block.


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.


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.


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


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

marketing budget!

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.


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.

Thank you.

Documents

2008 ANA Masters of Marketing Speech