Quantitative Approaches for Profit Maximization in Direct Marketing

Transcription

1 Quantitative Approaches for Profit Maximization in Direct Marketing Hiek van der Scheer To Ellen

2 The research for this thesis was supported by: Marketing Support Group Groningen Rabofacet Its publication has been made possible by the financial support of: PTT Post Mediaservice ISBN

3 Rijksuniversiteit Groningen QUANTITATIVE APPROACHES FOR PROFIT MAXIMIZATION IN DIRECT MARKETING Proefschrift ter verkrijging van het doctoraat in de Economische Wetenschappen aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus dr. F. van der Woude in het openbaar te verdedigen op donderdag 8 januari 1998 des namiddags te 2.45 uur door Hielke Roelof van der Scheer geboren op 24 februari 1969 te Tweede Exloërmond

4 Promotores: Prof. dr. T.J. Wansbeek Prof. dr. P.S.H. Leeflang

5 Acknowledgements This thesis reflects the research I did at the Faculty of Economics of the University of Groningen in the last four years. I am indebted to many persons who contributed to this research. I am especially grateful to my promotor Tom Wansbeek. It was a privilege working with such a stimulating person. He was always willing to discuss my research and think about all kinds of questions. I have benefited tremendously from his support, knowledge and critical notes. I am also grateful to my second promotor Peter Leeflang. He has provided me with well-considered criticism, which was often complementary to that of Tom Wansbeek. His comments on various aspects of this thesis have been very useful. Further I would like to thank the members of the graduation committee, Ton Steerneman, Michel Wedel and Dick Wittink for reading the thesis and for their useful comments. Moreover, I am grateful to Ton Steerneman for his contributions to various statistical problems throughout this thesis. Special thanks are due to Jan Roelf Bult, Janny Hoekstra, Lars Muus, Pieter Otter and Marco Vriens for their contributions to various parts of this thesis. It was a pleasure working with colleagues with different interests. It goes without saying that I retain full responsibility for any errors. I would like to acknowledge the hospitality of the Department of Statistics of the Australian National University at Canberra, where part of this research was done. I thank Gerard van den Hooff for correcting my English and Erik Frambach for his 4TEX-support. Financial support for this research was provided by the Faculty of Economics, the AIO-school, the NWO (Dutch organization of scientific research), the Marketing Support Group and Rabofacet. The publication of this thesis has been made possible by the financial support of PTT Post Mediaservice. Finally, I would like to thank Ellen for many reasons mainly beyond the scope of this thesis.

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7 Contents 1 Introduction Direct marketing Objective and outline of the thesis 4 2 Target selection techniques Introduction Objective of the direct marketing campaign Selection variables Selection techniques Model comparison Discussion and conclusion 27 3 Target selection by joint modeling of the probability and quantity of response Introduction Description of the model Optimal selection Approximations Operationalization Tobit model Data Empirical results Discussion and conclusion 47 4 Bayesian decision rule approach for target selection Introduction The decision theoretic framework The case of a normal posterior Numerical evaluation of the optimal Bayesian rule 61

8 4.5 Application Point estimation Modeling the quantity of response Discussion and conclusion 76 5 On the value of information Introduction Model Basic model Optimal selection rule and profits Postal code information What is postal code information? Profits and information Effects of using proxy information Application Measurement error Proofs Discussion and conclusion Optimizing the characteristics of the mailing Introduction Conjoint analysis experiments Applications Conjoint experiment for an envelope design Conjoint field-experiment for a letter design Conjoint field-experiment for an opt out reply card Interaction between target and mailing characteristics Modeling the response process Empirical results Optimal target selection Discussion and conclusion Frequency of direct mailings Introduction The model Specification of the model s components Data Simulation of individuals decisions Empirical illustration 160

9 7.7 Discussion and conclusion Summary, future research and management implications Summary Future research Management implications 180 Bibliography 183 Author index 193 Subject index 197