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

Abstract

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.

Correcting for “regression to the mean” in list selection decisions

“…We use the letter " p " to connote the observed response rate. Bias: Referring to equation ( 2 ) , the bias is-…”

“…Alternative decision rules have been presented in Ehrman ( 1 ) , and these results are presented in Exhibit 1. A structured decision-theoretic approach has been presented in Ehrman and Miescke ( 2 ) . In this paper, we remedy the "regression to the mean" problem for the point-estimate decision rule used by practitioners.…”

Optimum Selection Procedures in Multi-Stage Screening, Reliability, and Time

“…In a general cost-benefit approach, which fits into various frameworks .of applications, the optimum predetermined number of competing binomial populations to be tested at the first stage has been found for the purpose of using the most promising competitor later, at the second stage, on a much larger scale. This research [4], which is jointly with C.M. Ehrman, will appear soon.…”