Structured decision rules for ranking and selecting mailing lists and creative packages for direct marketing

The field of direct mail advertising is becoming increasingly important. Many selection decisions must be made by direct marketers, such as those concerning package testing and list and segment within list selection. These decisions can be quite complex, especially when sample sizes and average order size per package and list are not equal. In this article, Bayesian and non-Bayesian statistics are applied to these problems to generate optimal decision rules for package testing and list evaluation and selection. An example is given using real data from test results.