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Customer Data: What to Get and How to Make Sense Of It

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?”

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 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 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 high-level 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.”