chapter one
How This Book Will Help You Grow Your Business
I work in an industry known for reducing complicated ideas to a single
thought. These tag lines--"Merrill Lynch is bullish on America,"
"Finger lickin' good," and "Don't Leave Home
Without It"--were all created by my colleagues at Ogilvy &
Mather.And in my corner of the ad agency--I run Ogilvy's analytics
team--we operate on a single premise: The most successful companies
today are those that are able to convert the "data deluge"
we all face into insights that drive real growth.Our job is to help our
clients uncover those insights. To do that, we need to explain what we
discover within their data in simple, straightforward terms. (While
the CFO is probably comfortable when I talk about "logistic
regressions," the rest of the people in the C suite--the CEO, the
chief marketing officer (CMO), and the others we present to--usually
don't speak math shorthand, and their eyes glaze over after ten
or fifteen seconds when I do. So, I have learned to present my ideas
the way the "creatives" do, in simple, hopefully memorable
images such as "at sixty miles an hour, the loudest noise in this
Rolls-Royce comes from the electric clock." (That was another one of
ours.) And I will try as much as possible to use this type of language
in this book.Simple language only enhances this powerful fact: There
is now a proven way to increase dramatically both your company's
sales and its ROI using data you probably already have but may not
be aware of.How?Well, if you think about it, there are really only
two sides to every business: supply and demand. The supply side, how
a company is going to fill orders--i.e., how they will fulfill their
customers' needs--is the one that a business controls. The company
heads know, for example, how much productivity will increase if they buy
a new machine.The supply side is where most left-brainers--the logical,
financial types--feel comfortable. For decades, they have increased the
efficiencies of supply chains, streamlined processes, and developed
measurements to track progress.The demand side, on the other hand,
is something companies don't control; consumers do. Sure, you can
try all kinds of things to reach customers, but ultimately it is the
customer/consumer/client who decides if he is interested in what you
have to offer. The demand side is the fuzzy place where cause and effect
are not always clear. Did he buy because the product was perfect for
his needs, because he liked your ad, because your price was appealing,
because of word-of-mouth--or was it some combination of those factors
and a hundred more?Here finding out what happens when you turn the dials
and push the buttons is a messy business. The customer bought immediately
after clicking on your Internet ad; but was the banner ad the reason she
bought? Figuring it all out is what I do on a daily basis. As you will
see, I use the clean, tried-and-tested tools from the supply side and
apply them to the messy demand side of the business.These tools can help
you, in the words of the book's subtitle, grow your business in a
way that increases both your sales and profits.This is not only vitally
important to those of you in the C suite--after all, the shareholders
ultimately will judge you on how effectively you deploy their money--but
to employees at all levels of the company. Marketers and people who run
business units need to know which are the most profitable customers to
target; researchers must have a (profitable) consumer in mind as they set
off to create new products or services; those in customer service want to
pay the most attention to the firm's most valuable users/buyers; and,
of course, the people in finance will always ask whether the company
is going to make any money on its latest undertaking. By employing the
ideas we are about to talk about, the return on your investment can be
huge.How huge? Here are two quick examples using the techniques I will
be sharing with you: Caesars improved their return on online
advertising spending by 15 percent to 30 percent by analyzing data
generated from customer reviews about the hotels the company owned. There
are software programs that not only search out every comment customers
make on the web, but automatically sort those comments into scores of
categories, and the company used those findings to change their offers
and the language in their ads. For example, customers raved about the
views from the hotel, and now those views are featured prominently in
Caesars ads, while the price of the room is given less prominence.
TD Ameritrade increased new account openings by 14 percent from the
company website just by making very small changes to the copy, design,
and images on the site, based on an incredibly thorough examination of its
home page. Our team at Ogilvy tested every single word, color, and design
element with customers to see what could be improved. It turned out that
simply changing the signup language from "Apply online now" to
"Get started" and altering the color of the button customers
clicked from orange to green made a dramatic difference in the number
of people who opened accounts.As these examples show, the material in
this book is not theoretical. It is already being used by companies to
increase demand for their products. I am going to show you how you can
do the same thing.By looking differently at the existing data you have
about your customers, you can improve:Your strategy. You'll learn
how to fine-tune your overarching approach to both your customers and
the competition based on the insights the numbers about your business can
provide. For example, you will discover who your most profitable customers
are, who is most likely to buy from you, and which customer segments are
not worth targeting.The tactics you use to carry out your strategy. Your
data, when viewed correctly, will tell you how to approach and sell to
your most profitable customers and the best ways to reach those who are
likely to buy more from you.The execution of your tactics. Your data will
help you pinpoint where you will get the biggest returns and when would
be the best time to implement your tactics.There are two simple reasons
why these improvements are possible: First, remarkable breakthroughs in
technology allow us to sort through all the data about customer behavior
to find discernible--and predictable--buying patterns. We have always
had the data; but until now, companies could use it only in the crudest
terms. Second, just about everything we do today generates data, giving
us a much more complete picture of the people who do business with us,
and the potential revenue companies are missing, as the following story
shows.On a recent business trip, I woke up in the Canary Wharf section
of London and checked out of the Hilton. I took the subway to Paddington
Station. From there, I hopped on the Heathrow Express, supposedly the
most expensive train in the world, but still cheaper and faster than a
cab (and it doesn't make me carsick).I checked in for my British
Airways flight to JFK airport. Before boarding, I stopped at Boots,
the largest drugstore in the UK, to get a four-pack of cucumber wet
wipes. My wife, who is British, tells me they are the best in the world
and she cannot find them in the United States (like Marmite and Cadbury
Creme Eggs, this is another strange product British expats miss when
living abroad). I also browsed the perfume section, where a saleswoman
complimented me on buying Gucci's latest fragrance, Flora. Three
hours after waking up, I boarded my plane home.In this short period
of time, I left behind a rich trail of data. Hilton, if it knew where
to look, would have seen it was my third stay in that hotel within
six months. They also could have discovered I like a glass of wine
before I go to bed and that I prefer the continental breakfast despite
a promotion for the full English one. The London Transport Authority,
if it wanted to, could see I was in town for a week--I had purchased
a seven-day pass--and that I had crisscrossed the city during the day,
always to go back to Canary Wharf in the evening. They might also have
noticed that seven years ago, when I lived in London, I did the same
thing every day.The people who run the very expensive Heathrow Express
now have buried somewhere in their records that I used their services
for the third time in six months. British Airways would have noticed the
same. Boots could have figured out that I was probably another British
expat (well, Belgian with a British wife, actually) hamstering their
fabulous cucumber wet wipes. And Gucci, had it been paying attention,
would have noticed I bought the fragrance in a store with a couple
of big video-screen monitors advertising it nonstop.All this data was
being gathered without my even going online to surf the web. If I had,
then companies would have been able to track my every click, even if
I didn't purchase from them.The point is not to tell you how much
I travel for business, but to give you a tiny example of the volumes of
data that are being collected and hardly used. Sure, Hilton knows (if they
look) that I have a frequent-stayer account (Hilton HHonors), but I have
yet to receive a targeted email or letter that says, "The next time
you are London, Mr. Maex, may we suggest . . ."
(some hotels have started to do these kinds of mailings). Boots has never
mailed a catalog to our Brooklyn apartment, and I have never received
a solicitation from Gucci, which is probably a good thing, given how
much my wife likes their products.While I was traveling, millions of
others were generating similar volumes of data that same morning. They,
like me, do this through interacting with websites, social networks,
mobile devices, cash registers, etc.Companies haven't been using
the vast majority of information we generate because--up until now--it
has been too difficult to get at it in an useful way. I sympathize. The
volume of data gathered every day is staggering. To put the amount into
perspective: Imagine a database holding all words ever spoken by human
beings since the beginning of time. Now, if you were to take 200 of
those databases, you would have just about enough storage to hold all
the data that will exist by the end of 2012. That's a lot of data
and the numbers will only increase dramatically in the years ahead.But
companies no longer have the excuse that the data is too hard to sort
through. The tools invented in the last few years make it remarkably
easy.Let's see how. Here's a real-life example involving
strategy. The story begins right after my wedding.Cisco Systems: A
Case StudyKatherine and I chose the most romantic destination for our
honeymoon: Silicon Valley. It wasn't exactly what we had planned.A
couple of days before we got married, in 2004, I got a call about a job
opening in San Jose. While I love my native land of Belgium, I'd
always wanted to work in the United States. You need big volumes of
information to make my job fun. There are only ten million people in
Belgium, so the databases are small. This was a great opportunity to
work where the markets have bigger scale and are more sophisticated.So,
right after Katherine and I got married in Antwerp's beautiful
sixteenth-century town square, we found ourselves in the center of Silicon
Valley with all of our stuff in boxes. My job would be working with Cisco
Systems, the forty-billion-dollar technology company.Cisco's new
head of demand generation had asked Ogilvy for help in setting up what
they were calling an "advanced analytics" group. The goal of
this new unit would be to figure out precisely to whom Cisco should be
marketing and how much they should invest to reach those people. Up until
this point at Cisco--and maybe at your company as well--these decisions
were made by gut feel backed by some, often anecdotal, data.That might
be fine for a start-up company, but when you are an established firm,
one spending a lot of money on marketing--hundreds of millions of dollars
a year, in Cisco's case--you need to do better than hunches and
one-size-fits-all rules of thumb, such as you should spend 5 percent of
revenues on marketing.So Ogilvy sent me to Silicon Valley to see if I
could help Cisco. Apart from their head of demand generation, nobody
else at the company was necessarily waiting for the creation of an
advanced analytics group. Marketers in general weren't particularly
interested in analytics back then. Most people didn't go into
marketing because they liked math; quite the opposite. So I had some
convincing to do. Especially since the person who asked me to set this
up, the only advocate I could count on, had left Cisco to join Oracle by
the time I landed in San Jose!So there I was in my little gray cubicle
(the concept of a cubicle was foreign to me; I had seen it only in movies
like Clerks, where the people who inhabited them always seemed to have
dead-end jobs), on my first day at a new job in a new country. No one was
asking for my help. No one really understood what advanced analytics was
for. Heck, they didn't even know what the term meant.Given all this,
the first thing I did was to look for buddies, like-minded people who
understood the potential power of data and analytics in marketing. One
of them was Mike Foley, who was in charge of Cisco's marketing
database. He could tell me all about the information Cisco had on their
customers and prospects. This was great. If I was going to set up an
advanced analytics function, I would need data. Data is the raw material
for everything I do.Mike and I teamed up, and I started to delve into
the data, familiarizing myself with everything Cisco knew about its
customers--which was a lot. For every company that had ever bought a
Cisco product, there was data on when the companies bought, what they
bought, how much they spent, and how often they bought from Cisco. (You
probably have--or can get your hands on--this kind of data, too. Someone,
or some department, in your company is sending out invoices. The data
is probably inside their computers.)