Using demographic data.

AuthorCoffey, John J.
PositionDatabase Marketing

Really good marketers (which of course includes you since you are reading this column) are naturally a curious bunch. One thing they are curious about is the answer to the question: "Who are our customers?" Sure, you can get answers to the four P's of marketing (product, price, promotion and place) and have a rough idea of who your customers are--but the reality is that virtually any customer, regardless of his or her demographic attributes, purchases virtually any product you have to offer. To make matters worse, your internal transaction processing systems are of little use helping you understand who your customers really are.

What's needed is a way to household your customers' accounts (See our column titled "Why Householding Is Important in an MCIF," ABA Bank Marketing, June 2002) and a way to attach customer specific descriptive data to these households. Enter demographic data!

The purpose of demographic data

The definition of "demographic" is "of or relating to demography." Demography is actually the combination of two Greek words: "demo," which means "people," and "graphy," means "the art of writing or describing." So demography is simply a way of describing people. Similarly, demographic data is a way of describing the stage of life and lifestyle of your customers.

Companies that specialize in the compilation and sale of demographic data compile their data from many different sources: county real estate records; driver's license data; warranty forms. (Be careful what you say about yourself, it may come back to haunt you!); implied lifestyle based on geographic location; magazine subscription data; credit card data.

After this data has been compiled, it can then be attached or "appended" to the householded data within your MCIF.

Types of demographic data

Demographic data comes in many forms. The data may be reduced to a single element that describes your customer. For instance, you might be provided with a data element that tells you that your customer is "upscale retired" as opposed to "midscale retired" or "downscale retired."

On the other hand, the data might be broken out into many discreet elements that provide a much richer view of the customer's stage of...

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