Who's Got the Coupon? Estimating Consumer Preferences and Coupon Usage from Aggregate Information

被引:37
作者
Musalem, Andres [1 ]
Bradlow, Eric T. [3 ]
Raju, Jagmohan S. [2 ]
机构
[1] Duke Univ, Fuqua Sch Business, Durham, NC 27706 USA
[2] Univ Penn, Wharton Sch, Wharton Cosponsorship Indian Sch Business, Philadelphia, PA 19104 USA
[3] Univ Penn, Wharton Sch, Wharton Interact Media Initiat, Philadelphia, PA 19104 USA
关键词
Bayesian methods; aggregate data; structural demand models; coupon promotions; random coefficients;
D O I
10.1509/jmkr.45.6.715
中图分类号
F [经济];
学科分类号
02 ;
摘要
Most researchers in marketing have typically relied on disaggregate data (e.g., consumer panels) to estimate the behavioral and managerial implications of coupon promotions. In this article, the authors propose the use of individual-level Bayesian methods for studying this problem when only aggregate data on consumer choices (market share) and coupon usage (number of distributed coupons and/or number of redeemed coupons) are available. The methodology is based on augmenting the aggregate data with unobserved (simulated) sequences of choices and coupon usage consistent with the aggregate data. The authors analyze various marketing scenarios that differ in terms of their assumptions about consumer choices, coupon availability, and coupon redemption. They illustrate the proposed methods using both simulated data and a real data set for which an extensive set of posterior predictive checks helps validate the aggregate-level estimation. In addition, the authors relate the empirical results to some Of the findings in the literature about the coordination of coupon promotions and pricing and show how the methodology can be used to evaluate alternative coupon targeting policies.
引用
收藏
页码:715 / 730
页数:16
相关论文
共 37 条
[1]   Coordinating price reductions and coupon events [J].
Anderson, ET ;
Song, I .
JOURNAL OF MARKETING RESEARCH, 2004, 41 (04) :411-422
[2]  
ANDRES M, 2008, J APPL ECON IN PRESS
[3]   A hierarchical Bayes model of primary and secondary demand [J].
Arora, N ;
Allenby, GM ;
Ginter, JL .
MARKETING SCIENCE, 1998, 17 (01) :29-44
[4]   Coupon attractiveness and coupon proneness: A framework for modeling coupon redemption [J].
Bawa, K ;
Srinivasan, SS ;
Srivastava, RK .
JOURNAL OF MARKETING RESEARCH, 1997, 34 (04) :517-525
[5]   ESTIMATING DISCRETE-CHOICE MODELS OF PRODUCT DIFFERENTIATION [J].
BERRY, ST .
RAND JOURNAL OF ECONOMICS, 1994, 25 (02) :242-262
[6]   Competitive price discrimination strategies in a vertical channel using aggregate retail data [J].
Besanko, D ;
Dubé, JP ;
Gupta, S .
MANAGEMENT SCIENCE, 2003, 49 (09) :1121-1138
[7]   The recoverability of segmentation structure from store-level aggregate data [J].
Bodapati, AV ;
Gupta, S .
JOURNAL OF MARKETING RESEARCH, 2004, 41 (03) :351-364
[8]   Estimating disaggregate models using aggregate data through augmentation of individual choice [J].
Chen, Yuxin ;
Yang, Sha .
JOURNAL OF MARKETING RESEARCH, 2007, 44 (04) :613-621
[9]   Why don't prices rise during periods of peak demand? Evidence from scanner data [J].
Chevalier, JA ;
Kashyap, AK ;
Rossi, PE .
AMERICAN ECONOMIC REVIEW, 2003, 93 (01) :15-37
[10]   A SIMULTANEOUS APPROACH TO THE WHETHER, WHAT AND HOW MUCH TO BUY QUESTIONS [J].
CHIANG, JW .
MARKETING SCIENCE, 1991, 10 (04) :297-315