Testing New Direct Marketing Offerings: the Interplay of Management Judgment and Statistical Models

The launch of a new product or service via direct marketing is nearly always preceded by a test of that offering. Such a "live" test, conducted with a subset of the entire list of customer prospects, can sometimes be useful in a "go/no-go" decision regarding a full-scale launch of the offering. More commonly, the test is used to direct the offering more effectively toward the market segments that appear most promising. Specifically, test results are used and useful to determine whether a particular rental list of customer prospects should indeed be rented, and(for both rental and in-house lists) which specific customer segments should be contacted with the offering. This paper examines the effectiveness of managers' decisions related to designing a test and interpreting test results both conceptually-based on the literature of heuristics and biases in expert judgments-and empirically, for two new direct marketing offers. The paper describes how an interplay of management judgment and statistical models can lead to increased profits for new direct marketing offerings.

[1]  Ilan Yaniv,et al.  A case study of expert judgment: Economists' probabilities versus base-rate model forecasts , 1992 .

[2]  Bob Stone,et al.  Successful Direct Marketing Methods , 1975 .

[3]  H. J. Einhorn Expert judgment: Some necessary conditions and an example. , 1974 .

[4]  Fred Collopy,et al.  Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations , 1992 .

[5]  Ahti Salo,et al.  Adjustment of forecasts with model consistent expectations , 1996 .

[6]  Manohar U. Kalwani Maximum Likelihood Estimation of Zero-Order Models Given Variable Numbers of Purchases per Household , 1980 .

[7]  A. Tversky,et al.  Subjective Probability: A Judgment of Representativeness , 1972 .

[8]  J. Scott Armstrong,et al.  Long-Range Forecasting. , 1979 .

[9]  R. Dawes,et al.  Linear models in decision making. , 1974 .

[10]  W. Estes The cognitive side of probability learning. , 1976 .

[11]  David C. Schmittlein,et al.  Surprising Inferences from Unsurprising Observations: Do Conditional Expectations Really Regress to the Mean? , 1989 .

[12]  R. Hogarth,et al.  Confidence in judgment: Persistence of the illusion of validity. , 1978 .

[13]  Paul D. Berger,et al.  Direct Marketing Management , 1989 .

[14]  Berend Wierenga,et al.  The Integration of Marketing Problem-Solving Modes and Marketing Management Support Systems , 1997 .

[15]  D. Bunn,et al.  Interaction of judgemental and statistical forecasting methods: issues & , 1991 .

[16]  E. H. Bowman Consistency and Optimality in Managerial Decision Making , 1963 .

[17]  Colin Camerer,et al.  The process-performance paradox in expert judgment - How can experts know so much and predict so badly? , 1991 .

[18]  Derek W. Bunn,et al.  Non-traditional methods of forecasting , 1996 .

[19]  Robert C. Blattberg,et al.  Database Models And Managerial Intuition: 50% Model + 50% Manager , 1990 .

[20]  Stephen J. Hoch,et al.  A psychological approach to decision support systems , 1996 .

[21]  L. R. Goldberg Simple models or simple processes? Some research on clinical judgments. , 1968, The American psychologist.

[22]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[23]  Eric J. Johnson,et al.  Expertise and decision under uncertainty: Performance and process. , 1988 .

[24]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[25]  A. Tversky,et al.  Evidential impact of base rates , 1981 .