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Table 7-4 Responses from an Unknown Source
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Number of log-ons Number registered Cost per registrant Gross revenue Marketing costs Net revenue Direct mail 2,639 1,885 $75.25 $942,500 $141,846 $800,654 Email 553 153 $48.28 $76,500 $ 7,387 $69,113 Unknown source 1,288 882 $00.00 $441,000 $0 $441,000
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T h e C u s t o m e r L o ya lt y S o l u t i o n
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Where did all of these unknown source registrants come from Analysis of this situation tells us a lot about modern direct response techniques.
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The Value of Web White Mail
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In a traditional direct-mail campaign like the credit card example, the responses arrive via a toll-free number. When you call this number, an operator asks you for your source code. Good operators can usually worm this number out of the respondents, even though they may not have it with them when they call. When the operators cannot determine the source, they dub the source white mail responses from an unknown source. On the Web site, it is different. In this example, responders were supposed to enter their PIN when they came to the site as a result of an email or a direct-mail piece. If they did not remember their PIN, they were invited to visit the site and register anyway. As you can see, 1288 of them visited the site, and 882 registered. We will never know whether these 1288 people came as a result of the email campaign, whether they came as a result of the direct-mail campaign, whether they stumbled on the site through the recommendations of a friend or associate at work, or whether they came because of a combination of these reasons. But that points up a difference between live phone operator response and Web response: the fact that an entertaining Web site with a relevant quiz can lead people to visit the site to see what it is. There is no commitment. You can be anonymous, and disappear if you are not interested. On the other hand, practically nobody calls a toll-free number just to see what it is like. There it is tough to be anonymous. You know you will be talking to an operator. You don t want to waste her time. Therefore, Web response will generate a lot more white mail than phone response. This response can be the most valuable output of the entire process.
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Isuzu makes midsized commercial trucks that sell for about $33,000 each. Recently, the truck marketplace was moving very slowly. Furthermore, at that time, Isuzu had no new truck models to offer with which it could beat the competition. As a result, Isuzu had to rely on better marketing and improved ability to target prospects and customers. At the time, Isuzu s marketing budget had been cut back. On the bright side, however, American Isuzu Commercial Vehicles had just completed two major database projects using an updated customer database created by msdbm in Los Angeles. The rst project was to pro le customers, and the second was to model customer purchase behavior. Based on these models, a numerical scoring methodology was developed to indicate purchase behavior. Scores were then grouped into three ranges indicating a high, medium, or low likelihood of purchase. If the methodology was accurate, then customers who received a high score would be more likely to purchase in the near term than customers who received a low score. It was also felt that the company was more likely to be successful at selling a new vehicle to a current customer than at trying to convert a prospect. Msdbm developed a scoring methodology to predict the behavior of Isuzu Commercial Truck owners. The model predicted the propensity to purchase based on four variables: 1. 2. 3. 4. Number of people employed by the business Vocation e.g., landscaping, electrical contractor, towing, etc. Time since last purchase Total number of trucks owned
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Using the model scores, the customers were divided into three groups based on the likelihood of their purchasing a new truck: 1. High probability 2. Medium probability 3. Low probability
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