Knowledge that Transforms

Marketing Science greatly benefited from the admirable and fastidious efforts of more than 200 different individuals who provided manuscript reviews last year. Beyond those individuals already recognized on the editorial board, the editor-in-chief and guest editors of Marketing Science are indebted to the many guest editors, guest associate editors, and ad hoc reviewers who provided expert counsel and guidance on a voluntary basis. The following list acknowledges the contribution of guest editors, guest associate editors, and ad hoc reviewers who served from January 1, 2016 to December 31, 2016. Finally, our sincere appreciation to the authors, whose outstanding submissions and careful revisions make the journal the go-to resource for leading edge knowledge in quantitative marketing. Marketing Science mourns the loss of Professor Frankel ter Hofstede, University of Texas at Austin, who passed away in an untimely accident in December 2016. The marketing science community has lost a wonderful scholar, colleague, and friend. K. Sudhir Yale University

Efforts on developing, implementing, and evaluating a marketing analytics framework at a real-world company are described. The framework uses individual-level transaction data to fit empirical models of consumer response to marketing efforts and uses these estimates to optimize segmentation and targeting. The models feature themes emphasized in the academic marketing science literature, including incorporation of consumer heterogeneity and state dependence into choice, and controls for the endogeneity of the firm’s historical targeting rule in estimation. To control for the endogeneity, we present an approach that involves conducting estimation separately across fixed partitions of the score variable that targeting is based on, which may be useful in other behavioral targeting settings. The models are customized to facilitate casino operations and are implemented at the MGM Resorts International’s group of companies. The framework is evaluated using a randomized trial implemented at MGM involving about 1.5 million consumers. Using the new model produces about $1 million to $5 million in incremental profits per campaign, translating to about 20¢ in incremental profit per dollar spent relative to the status quo. At current levels of marketing spending, this implies between $10 million and $15 million in incremental annual profit for the firm. The case study underscores the value of using empirically relevant marketing analytics solutions for improving outcomes for firms in real-world settings. Data are available at https://doi.org/10.1287/mksc.2017.1039 .

For many years, marketing managers have used dynamic sales response models to compute expected sales conditional on the available information. These models fail to recognize that the volatility (conditional variance) of sales can vary over time. Moreover, the covolatilities (conditional covariances) between sales and marketing-mix variables can be time varying. Both concepts introduce a new range of strategic and tactical considerations for product and brand managers. Using a multivariate volatility model, we investigate the covolatility of sales and the marketing mix of a focal brand and competing brands in the market. We also examine carryover effects from a volatility perspective. The methodology is applied to six product categories sold by Dominick’s Finer Foods. The results reveal valuable implications for marketing managers. Data and the online appendix are available at https://doi.org/10.1287/mksc.2016.1013 .