April 30, 2001, 12:00 AM

Mountains of Data

(Page 3 of 3)

practices they’ve already got covered?

 

 

The answer: it depends. Data mining and new analytics technology can

be viewed as a speedier, more powerful way to feed the kind of database

marketing direct merchants have always done. It’s already delivering bottom

line results for companies that use it to manage growing amounts of customer

information across channels. Fingerhut and others are effectively using

data mining that focuses largely on purchase history to zero in even closer

to what customers want, and to target outreach accordingly.

 

But industry observers say buying behavior is just the start, and an

even more robust use of the tons of data being gathered online and across

channels is yet to come. “It’s now possible, for example, to measure customers’

viral propensity,” says David Daniels, an analyst with Jupiter Media Metrix.

“If I’m a loyal customer, I’m influencing other people to buy from the

brand. There’s software that has the ability to track whether customers

send e-mails from the merchant to someone else. You can also measure behavior

that indicates the customer isn’t satisfied and work that into a retention

strategy. AOL, for example, monitors how much time people spend online

with them. When they see a customer’s use going down, the customer will

receive incentives to come back, like $10 off at one of their affiliate

merchants.”

 

 

In other words, if strip mining the data is already

producing results, digging deeper into databases could yield even more

for merchants, as they gain new ways of defining value among customer

segments and target marketing approaches to match. For many, for now,

that will wait for a day when staff and budgets catch up with what technology

makes possible. And if increasingly sophisticated data mining and analysis

can deliver the formula retailers have been looking for, it’s a day that

will likely arrive soon. “The object here is to find the right buyer,

match them with the right products and right price and the right channel.

That’s the ultimate problem of retailing, and technology today, if used

in the right way, can make huge advances in that direction,” Xchange’s

Green says. “We’re just beginning to learn how powerful it can be.”  

 

 

mary@verticalwebmedia.com

 

 

 

 

It’s

not what they buy, it’s how they buy it

 

While

most retailers segment their customers based on what they buy-if they

bought a $1,000 lamp maybe they’d be interested in an oriental rug-Eddie

Bauer is segmenting customers based on how they shop. “Our merchandise

assortment is so much more narrow that we might only be promoting three

men’s sweaters at one time. We don’t need a complex algorithm to recommend

one of the three sweaters,” says Michael Boyd, director of customer relationship

management for Eddie Bauer.

 

 

To come up with segments based on shopping style, Eddie Bauer conducted

an exploratory data mining and analysis exercise, looking at behavioral

data that defined shopping preferences. It considered such factors as

what percentage of a shopper’s total purchases were made on mark-down,

what colors a given customer buys, and what time of day a customer is

most likely to do a transaction. All provided clues linked to larger predictive

patterns. Eddie Bauer also mined its database of attitudinal research

looking for more ways to classify customers in terms of how they approached

shopping.

 

Two segments emerged from the data. One, dubbed Too Busy to Shop, doesn’t

particularly enjoy shopping for apparel, is willing to pay more for a

speedy shopping experience, and likes to buy outfit solutions rather than

apparel pieces. The Professional Shopper, on the other hand, loves to

shop, is more price-aware and prides herself on the ability to assemble

a look from a variety of different sources.

 

“We’ve changed our focus to using all of the data we have to draw only

one conclusion: which type of shopper is this?” Boyd says. “And we develop

different versions of that set of communications.” Before the holidays,

the company tested three versions of an e-mail, including a version targeting

Too Busy to Shop, one targeting The Professional Shopper and a control

group. Tests on and off target resulted in sales 7% to 8% higher when

customers got communications targeted for their type. When they received

communications targeting the group they didn’t belong to, the message

actually depressed sales, making them even less likely to buy than the

control group.

 

The two-segment approach is already in use at Eddie Bauer in the form

of segmented catalog mailings. A roll-out of segmented e-mail campaigns

is likely later in the year-not, however, without additional testing and

validation of the concept.

 

 

 

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