Models for Sales Promotion Effects ... my attention to modeling marketing effects. ... sincere interest and tremendous support during all stages in my life,.
MODELS FOR SALES PROMOTION EFFECTS BASED ON STORE-LEVEL SCANNER DATA HARALD J. VAN HEERDE
Models for Sales Promotion Effects Based on Store-Level Scanner Data
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Labyrint Publication P.O. Box 662 2900 AR Capelle a/d IJssel The Netherlands
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ISBN 90-72591-72-0
c 1999, Harald J. van Heerde All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted in any form or by any means, electronic, mechanical, now known or hereafter invented, including photocopying or recording, without prior written permission of the publisher.
Rijksuniversiteit Groningen
Models for Sales Promotion Effects Based on Store-Level Scanner Data
Proefschrift
ter verkrijging van het doctoraat in de Economische Wetenschappen aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus, dr. D.F.J. Bosscher, in het openbaar te verdedigen op maandag 22 november 1999 om 16.00 uur
door
Harald Johan van Heerde
geboren op 22 april 1972 te Ens
Promotores: Prof.dr. P.S.H. Leeflang Prof.dr. D.R. Wittink
ISBN 90-72591-72-0
Preface
A seminar given by Peter Leeflang and Dick Wittink on the application of econometrics to marketing was an important motivation for writing this thesis. At that time I was studying econometrics, and this seminar very much triggered my attention to modeling marketing effects. Consequently, the Ph.D. project on models for sales promotion effects at the University of Groningen suited my interests very well. During the four-and-a-half years I have worked on this project, I have learned a lot about sales promotions, about modeling marketing effects, and about academic writing. And, in addition, my shopping behavior has become increasingly promotion-oriented. The research in this period could not have been conducted without the help of many people. First and foremost I would like to thank my supervisors, Peter Leeflang and Dick Wittink, for their support, their enthusiasm, and their very high standards for research. As for Peter, special memories concern the evenings spent in Roden, when we discussed not only research topics but also other aspects of life. As for Dick, our very intensive email contacts over the past few years (approximately 2000 emails) is very much appreciated. The speed and the high-quality content of his email responses still amaze me. In addition, I keep very good memories of the hospitality of the Wittink family during multiple visits to the USA. Next, my thanks go to the Ph.D. committee for their careful reading of my manuscript, and for their constructive comments. This committee consists of Marnik Dekimpe from the Catholic University of Leuven, Philip Hans Franses from the Erasmus University in Rotterdam, and Tom Wansbeek and Michel Wedel from the University of Groningen. One of the most important factors that has contributed to my joy in working in Groningen is the warm contact with colleagues. In this respect I especially remember the good times with my room-mate Mirjam Kruijt, the conference visits and soccer evenings with Edward Rosbergen and Rinus Haaijer, and the warmth and keen interest of Liane Voerman. I would also like to mention
Eijte Foekens, for teaching me to write computer codes in Gauss, introducing me to the field of sales promotions, being a very valuable colleague, and for providing detailed comments to my manuscript. AC Nielsen, both in the Netherlands and in the USA, provided the store-level scanner data for this thesis, for which I am grateful. In addition, I would like to thank Eveline van Acquoij, Gilian Halewijn, and Toine Boonman from AC Nielsen, the Netherlands, for sharing their views on the practical issues of sales promotion research. I would also like to thank the following institutions for providing financial support for my research: the SOM Ph.D. school, the Faculty of Economics, the Dutch Organization of Scientific Research (NWO), and Shell. Importantly, I would like to thank my father, mother, brother, and sister for providing sincere interest and tremendous support during all stages in my life, including my Ph.D. years. And finally, I thank Jos´ephine Woltman Elpers for everything she means to me. Groningen, September 1999
Contents
1 Introduction 1.1 1.2 1.3
1.4
1.5 1.6
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Definition of sales promotions . . . . . . . . . . . . . . . . . . Economic theories of promotions . . . . . . . . . . . . . . . . . Focus on sales promotions . . . . . . . . . . . . . . . . . . . . 1.3.1 Manufacturers’ focus on promotions . . . . . . . . . . . 1.3.2 Retailers’ focus on promotions . . . . . . . . . . . . . . 1.3.3 Consumers’ focus on promotions . . . . . . . . . . . . 1.3.4 Reasons for increased focus on sales promotions . . . . 1.3.5 Joint manufacturer and retailer sales promotion programs Sales promotion effect measurement . . . . . . . . . . . . . . . 1.4.1 Overview of sales promotion effects . . . . . . . . . . . 1.4.2 Importance of sales promotion effect measurement . . . 1.4.3 Effect measurement in practice . . . . . . . . . . . . . . 1.4.4 Effect measurement in the marketing literature . . . . . 1.4.5 Research issues in sales promotion effect measurement . Contributions of this research . . . . . . . . . . . . . . . . . . . Research approach . . . . . . . . . . . . . . . . . . . . . . . .
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2 Semiparametric Analysis to Estimate the Deal Effect Curve 2.1 2.2
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Introduction . . . . . . . . . . . . . . . . . . . The deal effect curve . . . . . . . . . . . . . . 2.2.1 Threshold effects . . . . . . . . . . . . 2.2.2 Saturation effects . . . . . . . . . . . . 2.2.3 Promotion signal effects . . . . . . . . 2.2.4 Cross-item deal effects . . . . . . . . . 2.2.5 Contributions of this research . . . . . Models . . . . . . . . . . . . . . . . . . . . . 2.3.1 Rationale for regression-type approach 2.3.2 Parametric approach . . . . . . . . . . 2.3.3 Nonparametric approach . . . . . . . .
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2.4 2.5
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2.3.4 Semiparametric approach . . . 2.3.5 Benchmark parametric models Data description . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . 2.5.1 Fit . . . . . . . . . . . . . . . 2.5.2 Predictive validity . . . . . . 2.5.3 Deal effect curves . . . . . . . 2.5.4 Interaction effects . . . . . . . Conclusions . . . . . . . . . . . . . .
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3 The Estimation of Pre- and Postpromotion Dips 3.1 3.2 3.3
3.4 3.5 3.6
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Introduction . . . . . . . . . . . . . . . . . . . Arguments for the lack of a postpromotion dip, model specification . . . . . . . . . . . . . . . Model specification and calibration . . . . . . . 3.3.1 Variable choice . . . . . . . . . . . . . 3.3.2 Model specification . . . . . . . . . . . 3.3.3 Model alternatives . . . . . . . . . . . Data . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . .
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4 Decomposing the Sales Effect of Promotions 4.1 4.2 4.3 4.4 4.5
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Introduction . . . . . . . . . . . . . . . . . . Conceptual decomposition . . . . . . . . . . Past research on decomposition . . . . . . . . Contributions of this research . . . . . . . . . Modeling strategy . . . . . . . . . . . . . . . 4.5.1 Visual model representation . . . . . 4.5.2 Model specification . . . . . . . . . . 4.5.3 Model estimation . . . . . . . . . . . 4.5.4 Model application for decomposition Results . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . .
Introduction . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . Managerial implications from this thesis Limitations and future research . . . . .
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5 Summary and Discussion 5.1 5.2 5.3 5.4
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Appendix: A Suggested sample sizes for nonparametric estimation
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B Kernel method
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C Estimation procedure for semiparametric model
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D Model operationalizations for semiparametric model 141 D.1 Kernel choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 D.2 Bandwidth parameter choice . . . . . . . . . . . . . . . . . . . . . . 141 D.3 Construction of confidence intervals . . . . . . . . . . . . . . . . . . 143 E Estimation results for Chapter 2 145 E.1 Parameter estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 E.2 Fit and predictive validity . . . . . . . . . . . . . . . . . . . . . . . . 150 F Description of regular price algorithm
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G Estimation results for Chapter 3 157 G.1 Introduction and notation . . . . . . . . . . . . . . . . . . . . . . . . 157 G.2 Estimation results for tuna data . . . . . . . . . . . . . . . . . . . . . 158 G.3 Estimation results for tissue data . . . . . . . . . . . . . . . . . . . . 161 H Estimation procedure for structured semiparametric regression model 171 H.1 General outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 H.2 Model operationalizations . . . . . . . . . . . . . . . . . . . . . . . 172 References
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Author index
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Subject index
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Samenvatting (Summary in Dutch)
191
