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, 2017 to December 31, 2017. 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. K. Sudhir Yale University

In collaboration with three companies selling a diverse set of products, we conducted randomized field experiments in which experimentally tailored email ads were sent to millions of individuals. We found consistently that personalizing the emails by adding consumer-specific information (e.g., recipient’s name) benefited the advertisers. Importantly, such content is not likely to be informative about the advertised product or the company. In our main experiment, we found that adding the name of the message recipient to the email’s subject line increased the probability of the recipient opening it by 20% (from 9.05% to 10.80%), which translated to an increase in sales’ leads by 31% (from 0.39% to 0.51%) and a reduction in the number of individuals unsubscribing from the email campaign by 17% (from 1.2% to 1.0%). We present similar experiments conducted with other companies, which show that the effects we document extend from objectives ranging from acquiring new customers to retaining customers who have purchased from the company in the past. Our investigation of several possible mechanisms suggests that such content increases the effort consumers make in processing the other content in the rest of the advertising message. Our paper quantifies the benefits from personalization and sheds light on the role of noninformative advertising content by analyzing several detailed measures of recipient’s interaction with the message. It provides external validity to psychological mechanisms and has clear implications for the firms that are designing their advertising campaigns. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1066 .

We quantify the effect of consumers’ price uncertainty on gasoline prices and margins on an Italian highway. We observe the change in prices triggered by a longitudinal policy-based change in consumers’ price information from one in which drivers on the highway have no information on the prices of stations they encounter to one that allows consumers to observe the prices of four upcoming stations on a single price sign by the side of the highway. Using these data, we estimate a model of consumer search and purchase behavior and a corresponding model of gas station pricing. We then measure the impact of varying degrees of price information on equilibrium prices, including (i) no price information, (ii) the current policy, and (iii) full price information. We also compare the current policy with an alternative policy in which stations’ prices are advertised with individual price signs. We find that when consumers do not have price information, gas stations are able to charge 31% more, in terms of higher price-cost margins, than when prices are known. Our welfare analysis suggests that price information is worth €0.57 to consumers every time they take the highway. Relative to the current mandatory policy, advertising price on individual signs is worth €0.19 more to consumers. The e-companion is available at https://doi.org/10.1287/mksc.2018.1105 .

Firms often learn about their own capabilities through their products’ successes and failures. This paper explores the interaction between learning about capabilities and product strategy in a formal model. We consider a firm that can launch a sequence of products, where each product’s success probability depends on the fit between the firm’s capabilities and the product. A successful new product always causes the firm to become more optimistic about the capability most relevant for that product; however, it can also cause the firm to become less optimistic about some of its other capabilities, including capabilities the new product does not use. The firm’s optimal forward-looking product strategy accounts for short-run expected profits as well as for the information value of learning for future decisions. We find that a product sharing few or even no capabilities with potential future products can have a greater information value than a product that shares more capabilities with future products and that learning about capabilities can affect the optimal sequence of product launch decisions. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1068 .