Nuts & Bolts: Case Study

Better Name Selection For a Franchise

September 2007

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Challenge: Better pinpoint homes likely to hire an in-home cleaning service.

Solution: Employ predictive modeling for more accurate name selection.

Results: Increased campaign response and lower acquisition costs.

The Maids International (TMI) was casting its net too wide. The Omaha, Neb.-based residential cleaning service was relying on simple geography and broad selects, such as households with incomes of more than $100,000, to build mailing lists for its franchise direct mail campaigns. As a result, the mailings produced few leads and even fewer new customers for its 90 franchises.

To better pinpoint households likely to hire an in-home cleaning service, TMI enlisted the help of Genalytics, an Andover, Mass.-based data solutions provider that produces predictive models to create targeted prospect universes that are customized to campaign objectives.

According to Dave Griebel, TMI’s vice president of marketing, implementing Genalytics’ modeling software was relatively simple. Using one franchise as a test, TMI provided Genalytics with its current customer names and addresses, which were uploaded into Genalytics’ On-Demand Targeting platform. This customer information was summarized into a profile report that provided a demographic snapshot of customers who purchased in the past and compared them to local market averages.

From there, Griebel says, Genalytics created a model comparing TMI customers to noncustomers to determine what customer characteristics were unique and predictive. According to Griebel, by applying more than 500 variables to more than 120 million households, then examining hundreds of data elements, Genalytics pinpointed 10 variables that were the most predictive of a consumer’s need for a cleaning service. These variables included: home value, an income of more than $150,000, presence of children or pets in the home, length of residency and geography.

Reports Griebel, “The attributes that made someone more likely to respond to an offer were measured and used to score households in the Genalytics prospect universe.”

When mailed, those households yielded a 49 percent lift in response over nonmodeled names. In addition, the modeled names generated higher revenue per response, and the mailing achieved a 105 percent increase in ROI, Griebel says.

Once TMI’s other franchises saw the test results, the number of franchises electing to use the Genalytics’ tool jumped from one to 90 branches in just nine months. Genalytics’ On-Demand Targeting platform helped TMI franchises build customer bases faster and more efficiently, says Griebel. The predictive modeling tool was instrumental “in increasing the cost-effectiveness of direct mail and lowering acquisition costs for TMI corporate while providing an additional marketing approach for TMI franchises,” he says.

—Kate DeBevois

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