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Customer
cover story
42 jul/aug 2012 salesandmarketing.com
data:
cover story
what to get and
how to make
sense of it
by Paul Nolan
The era of Big Data requires big ideas
There isn’t a sales or marketing manager around who
wouldn’t love to have Andrew Pole on his team. Pole is no
sales superman, nor is he a crafter of the sort of marketing
message that would make Donald Draper weep.
He’s a statistician and an economist. How would a
marketing manager put this self-confessed math nerd’s
skills to good use?
In a New York Times Sunday Magazine cover feature
published early this year, investigative reporter Charles
Duhigg introduced readers to Pole, who had just started
working for Target in 2002 when two colleagues from
the marketing department asked him, “If we wanted to
figure out if a customer is pregnant, even if she didn’t want
us to know, can you do that?”
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Duhigg explains there are brief periods in a person’s life when routines fall apart
and buying habits are suddenly in flux. One of these moments is right around the
birth of a child, when parents are exhausted and their shopping patterns and brand
loyalties are “up for grabs.”
Target’s marketers wanted to beat competitors to this lucrative prize. Of course,
new parents are inundated with offers and incentives and advertisements from all
sorts of companies after the birth of a child. The key is to reach them earlier, before
any other retailers know a baby is on the way. In fact, Target wanted to send
specially designed ads to women in their second trimester, which is when most
expectant mothers begin buying all sorts of new things, like prenatal vitamins and
maternity clothing.
“We knew that if we could identify them in their second trimester, there’s a good
chance we could capture them for years,” Pole told the Times. (That is, Pole told the
Times before Target top brass got wind of his story and shut off access to Pole.)
The Big Data Grab
Collecting customer data is at the core of most consumer marketing plans
nowadays. Target keeps reams of it on every person who regularly walks into one of
its stores. If you have shopped regularly at Target, it most likely knows whether you
are married and have kids, how long it takes you to drive to the store, your
estimated salary and what credit cards you carry. And it can buy even more data on
you — your job history, the magazines you read, the year you bought your house,
whether you prefer certain brands of common household goods and your political
leanings.
“Almost every major retailer, from grocery chains to investment banks to the U.S.
Postal Service, has a ‘predictive analytics’ department devoted to understanding not
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CONSUMER DATA, continued from page 44
just consumers’ shopping habits but also their personal habits,
so as to more efficiently market to them,” Duhigg writes.
The ability of today’s modern marketer to collect data is, to
many, downright frightening. But, as Duhigg points out, all of
that information is meaningless without someone to analyze
and make sense of it. That’s where Pole and dozens of other
members of Target’s Guest Marketing Analytics department
come into play. “It’s like an arms race to hire statisticians,”
Andreas Weigend, the former chief scientist at Amazon.com,
told Duhigg.
What about B2B?
Clearly, the advancement of data analysis has allowed
consumer goods companies to segment consumers and
effectively target them with marketing messages. But have
there been similar advancements on the B2B side? Officials at
SetLogik (setlogik.com), a provider of software solutions for
precision target marketing for B2B marketers, point out in a
company blog that there are distinct differences between
consumer and business markets that present B2B marketers
with the following unique challenges:
• B2B marketers always deal with two
entities, the companies they sell
to, plus the people who
represent those companies in
the purchase decision (also,
keep in mind that people
behave differently when
purchasing a product or
service for the company
they work for). In
comparison, in nearly all
B2C buying situations, there
is only one entity to consider.
• Unlike B2C, B2B does not have
the luxury of richness of
information. B2C marketers have, at
their fingertips, access to buying behavior
and trends derived from lifetime transactional history.
• Information of B2B prospects decays rapidly due to
changes in a prospect’s biographic (title, phone, etc.) and
firmographic (company, etc.) information.
“These significant differences coupled with the challenges of
selling an oftentimes highly complex solution have put B2B
marketers at a distinct disadvantage,” SetLogik argues in its
blog. Still, the company says its B2B Enterprise Edition
software harnesses B2B big data with predictive analytics
techniques to allow B2B marketers to better understand
customers, partners and prospects. The result, they claim is
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higher lead to won opportunities conversion rates and
increased revenue with higher-ranked accounts.
Erik Long, a principal at ZS Associates, a sales and marketing
consultant, says B2B marketers can learn a lot from their
consumer marketing brethren’s use of customer data to
improve target marketing.
“What data are we capturing is a good question, but perhaps
a better question is how do I know what data I need to pay
attention to?” he says. “How do I understand what data is going
to be most helpful? As we call it, relative, high-quality, decision
impact data — the data that’s going to drive how someone
makes a decision. Companies that can [capture] that, they’re
the ones who are really starting to harness data well.”
The 3 buckets
Long separates out B2B data into three buckets:
• Internal transaction data – the easiest to access, it’s
inside numbers such as sales, purchase orders, size of
transactions, inventory control, etc.
• Primary market research – information collected
from customers after a sale
• Secondary data – information such as trends in your
customers’ industries that you collect via social media
monitoring, customer councils, and other highlevel listening
“The ultimate goal is to turn your observations
into revelations about the customer. That’s
the piece many companies fall down on,” he
says, adding quickly that spinning customer
data into gold is a big part of the value that
ZS Associates delivers to clients.
What does that metamorphosis look like?
Different things to different people, Long
says. A market research manager will be more
specific: “I have this customer satisfaction
tracking data that we’ve been collecting and we’re
not finding any nuggets in it. How do I get more
leverage out of it?”
A chief marketing officer, meanwhile, is likely to phrase
things as more of a business challenge: “I can’t find the next
generation of growth for our company and I worry how
effective my sales and marketing efforts are in achieving that
growth.”
Sales managers embrace measurement. They need to do it
here, Long says emphatically. “You can actually link the
performance of things like customer advocacy to business
performance. It’s not enough to say, ‘Hey, we’ve done this great
thing and that improved our customer satisfaction by 3 percent.’
You have to determine how much it actually linked to your
financial outcome.”