A data match made in heaven

Aug 01, 2006 9:30 PM  By

Joe and Ted both spend the same amount of money annually with a multichannel electronics merchant. But by analyzing both behavioral and demographic data on Joe and Ted, the company can see that the amount of money they spent is pretty much the only thing the two customers have in common — and can then tailor its marketing to each.

An ideal marriage

Catalogers have long placed a premium on behaviorial data — information regarding what a person does or has done, including buying behavior. That’s why they overwhelmingly prefer to rent catalog, or response, lists over compiled files for prospecting: A name on a catalog list has obviously purchased from a catalog, whereas a name on a compiled list may have no inclination to ever buy direct.

“With a response list,” says Joe Pych, founder/president of Hanover, NH-based direct marketing services provider NextMark, “you’re getting right to the meat of the matter, based on what a customer has done in the past.”

But behaviorial data alone can be misleading. Let’s say Terry purchases infant clothes from a children’s apparel merchant. That doesn’t necessarily mean that Terry recently became a mom and should therefore be marketed to as such. Demographic information — age, income, household makeup, educational background, zip code, and employment status, among other types of information — could reveal that Terry is a 72-year-old childless bachelor. He may well have purchased the outfit as a one-off gift, so frequent mailings to him may be a waste of resources.

Andrew Belth, vice president, direct marketing for New York-based marketing services firm Alloy Media + Marketing, provides another example: AARP, the nonprofit group for people 50 years of age and older, wouldn’t rent a list of mail-order insurance buyers without overlaying demographic data to remove those under the qualifying age.

“In most cases, behavioral data is the most valuable information you have,” says Belth. “It’s indicative of some kind of intent to make a purchase or to respond to a particular offer. But hand in hand, demographic data is vitally important. The combination of demographic and behavioral data is more powerful than either one is individually.”

Getting the picture

As Katie Cole, vice president of research and analytics for Merkle|Quris, the e-mail marketing agency of Lanham, MD-based database marketing agency Merkle, sums it up, “The value of the demographic data is a rich, narrative profile of your customer that you cannot get just by looking at sales history. Multichannel merchants need a full picture of customers, and you can get that by blending the demographic data with the actual response. Having one set of data without the other means you only have partial data, and not the whole picture.”

The use of cooperative databases and data overlays are two common methods of gaining a complete picture.

“Co-ops have all the consumers of all its members in one database. They know their history, they know when they bought it, and they know what SKUs were bought,” says Phil Wiland, president/CEO of Longmont, CO-based co-op database Wiland Direct. “You ask for the selects, and the system automatically finds those consumers who are most indicative of responding.”

The co-ops could be better for the marketer looking for either demographics or behavior because of the hundreds of thousands of subsets to choose from, says Wiland. For example, as opposed to a broad market affinity like computers, a co-op may be able to segment out purchasers of scientific calculators.

“The more a marketer pays attention to its customer data, the more relevant and tailored its campaigns will be,” says Marc Fanelli, vice president of the Business Strategies Group for Schaumburg, IL-based database firm Experian Marketing Solutions. “Customer data is playing a very critical role for merchants. It’s not necessarily creating a one-to-one situation, but it’s letting them know that different consumers require different things. It’s all about understanding the profile of your customers.”

Let’s get back to the earlier example of Joe and Ted, who both spent $1,000 with a consumer electronics merchant. If the marketer used a behavioral select, the merchant could see that Joe spent $1,000 on a full-price one-time purchase, while Ted made several smaller purchases of sale and clearance items.

“In that case, I’m not going to cheapen my brand image and send a 10%-off coupon to Joe,” Fanelli says. “But I would send that to Ted, since he responds to sale-priced goods.”

A behavioral select would also reveal that Ted was loyal to the company last year, while Joe spread his money around. Joe actually spent $20,000 on electronics, with most of his expenditures made at one particular rival merchant.

“With that data, I would change the way I communicate with both customers,” Fanelli says. “My strategy may be more about retention with Ted because you don’t want to lose that $1,000. And Joe is not as engaged to my brand as Ted is because he’s spending $19,000 outside my four walls. I need to know what makes Joe tick so that my brand can be more relevant to him.”

Fanelli says he would do that by placing a demographic overlay on the behavioral data. Demographic data can be rented from a number of compilers and list services firms. The information might then reveal that Ted is a single twenty-something who makes $30,000 a year and is into gaming, while Joe is a 45-year-old married male with three teenagers and a household income of $120,000. The demographics may show that Joe isn’t even into electronics, but the household makeup would explain why he bought two computer systems, a home entertainment system, and three MP3 players during the past year.

More digging into the behaviorial data reveals that Joe is a technophobe who required a fair amount of hand-holding and VIP treatment from the merchant he spent most of his money with. Not only did he call the retailer’s contact center for instructions on setting up the computers, but he also paid to have the home entertainment system set up in his home. To win more share of wallet from Joe, then, the marketer may want to emphasize its customer service when communicating with Joe.

“More multichannel retailers are coming on line in understanding that different sources of information offer different sources of insight, but no one source of information will give you everything you need to drive relevance and be a more efficient marketer,” Fanelli says.