Data Mining in the 21st Century
Scotts LawnService, an on-site lawn, tree and shrub care service—and an organization that already understands the marketing power of data mining—was intrigued by the ability to integrate demographics with property data (e.g., lot size, purchase price, square footage). Using a base of recent responders and non-responders, a model was created from hundreds of atomic demographic and property elements to identify prospects most likely to respond to a direct mail offer for lawncare service.
The challenge was to exceed current model performance by at least 25 percent. According to Scott Jablonski, marketing manager at Scotts, “We are testing new data sources and a new type of thinking. We’ve just begun to tabulate the results from our spring campaigns and are anxious to see whether results meet their model forecasts.”
Robert Groessner, CEO of direct mortgage lender HomeStar Direct, is a disciplined direct marketer looking to boost his firm’s campaign performance to the next level. A structured test of high-performance data—more than 300 individual-level credit elements modeled to identify interactions between variables, e.g., home equity, revolving debt, age—was launched, and the results were 30 percent to 40 percent higher than head-to-head testing against current control programs using creative and copy approaches developed based on more traditional models.
Groessner says, “Testing [new data approaches] not only convinced us to proceed further, but it helped us realize that the reason for this success is the combination of disciplined database marketing and ‘out-of-the-box thinking’ that we’re able to do with such an in-depth level of available data.”
Good Marketing Is Continual Innovation
This brings us to the next most important aspect of data mining that direct marketers face. It has to do with a question that one of my company’s most advanced clients asks me each time we meet: “What are you going to do for me next?”