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The Weekly Standard is a conservative weekly political journal. The magazine conducts extensive direct-mail campaigns using rented lists, most of which are political fund-raising and subscription lists. For help in increasing its subscriber base, it turned to Brian Brilliant at BMD in Alexandria, Virginia. The source of a list often demonstrates the mindset of the people on that list. To leverage the limited data on potential customers, BMD s
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strategy was to insert a variable headline at the top of the letter that would relate in a marketing sense to the list from which the recipient came. For example, if John Doe s name came from a military list, then he would get a headline such as: John Doe, we have some shocking news about American s decaying military. Seven headlines were created to match up with the rented lists. As you might expect, there were some lists that didn t t any speci c pro le. They received a generic headline. The headlines that were not selected for each prospect were then used in the rst paragraph as part of a variable message describing the variety of subject matter that readers might nd in the publication. How well would such an approach work To nd out, Brian created a control group for each list. The control group did not get a customized headline, but instead got a generic headline about the magazine. Comparing the controls to the customized headlines, the custom letters had, on average, a 24.8 percent better response rate and a 62.3 percent better pay-up rate. The agency attributed most of the boost in initial response rate to the openability of the package because of the personalized message. And it attributed the lift in pay-up rate to the fact that subscribers were told up front that the magazine contained content that would interest them. The method worked.
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For the past 15 years, Claritas has done a brilliant job of dividing the U.S. population into 62 clusters with catchy names like Shotguns & Pickups and Pools & Patios. These clusters roughly re ect household income and living style. For some products (although not for most), the cluster someone lives in has something to do with the products that person tends to buy. People in some clusters drink imported beer. People in others drink only domestic. Folks in some clusters read the New York Times. Folks in others read the New York Post. People in still others do not take a newspaper at all. If your product can be shown to be particularly attractive to people in certain clusters, you can use this in your retention program. In a previous book, I described how the Globe and Mail in Toronto made highly pro table use of cluster coding to determine who read its newspaper and who didn t. With that
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knowledge, it was able to concentrate its telemarketing on the correct postal walks, saving millions of dollars per year in acquisition costs. Should you use cluster coding First of all, remember that cluster coding works only with consumer products. Second, consider whether your product appeals particularly to a certain class of people. If you think that it does, spend the money to have cluster coding af xed to 20,000 of your customers, ranked by revenue, and see if the clusters show you anything worthwhile. Any good service bureau can have cluster codes af xed to your le for about $120 per thousand, so your 20,000 will cost you a minimum of about $4000. In most cases, the clusters won t show you anything at all. If they do, you can use them to make some money. Let s assume that you have been sending direct mail to about 1.2 million customers per month, for which you spend about $650,000. Table 13-2 shows what your results might look like. It is costing you about $30 to acquire a customer. This is your control. Now let s try to beat that. We are going to select prospects for mailing mainly from the correct clusters, with some others added to make sure you are right. Your mailing next month could look like Table 13-3. Table 13-2 Results before Using Cluster Selection
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Nonselected direct mail Clusters with over 20% penetration Clusters with 5% to 19% penetration Clusters with less than 5% penetration Total customers 219,499 452,991 601,223 1,273,713 Cost $111,944 $231,025 $306,624 $649,594 Sales 7,463 9,513 4,810 21,786 Rate 3.4% 2.1% 0.8% Cost per sale $15.00 $24.29 $63.75 $29.82
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