Retail Analytics (MKTG-462-0)
This course was formerly titled, Retail Analytics, Pricing and Promotion Why is a dress priced at $39 rather than $40? How does a "Sale" sign change customer behavior? Does it matter what other customers pay for an item? Can price changes antagonize customers and reduce demand? How has the Internet changed customer price sensitivity? Are retail loyalty programs effective? How has expansion of retail stores, factory stores and the Internet changed customer behavior? This course seeks to answer these types of questions. Approximately two-thirds of the course covers topics in sales promotion and pricing; the remainder focuses on emerging issues in retailing, such as retail loyalty programs, category management and multi-channel consumer behavior. This empirical, data-driven course provides an integrated framework for studying consumer behavior, which we then take to data. Most of the data is from real-world managerial problems, and students will often study data from field experiments to gain a deeper understanding of consumer and firm behavior. Students will learn how to make informed pricing and retailing decisions using data.

Quantitative Marketing: Structural Modeling (MKTG-551-3)
This course introduces students to demand estimation using individual and aggregate data. The course begins with a discussion of discrete-choice models, their interpretation as random utility maximization models, logit/probit, discrete and continuous heterogeneity, and estimation using maximum likelihood. Some of these topics are motivated around issues such as disentangling state dependence and unobserved heterogeneity, models of learning and search, and estimating advertising effects. Next the course moves to demand models using aggregate data, starting with the aggregate logit model in Berry (1994) and building to the equilibrium model of Berry, Levinsohn, and Pakes (1995). This prompts a discussion of endogeneity and the role of supply-side restrictions. Time allowing, we introduce the notion of dynamic single agent models. Throughout the course, careful attention is given to identification strategies.

Quantitative Marketing: Analytic Modeling (MKTG-550-0)
In this course you will learn what analytic models are, their purposes, and how to build and analyze an analytic model to provide insight into an applied research problem. Analytic models in Marketing are used in many substantive areas, including competitive marketing strategy, pricing, product design, distribution channel design/management, and sales force compensation. They provide insight into the impacts of market forces, competitive actions, consumer segmentation characteristics, and firms’ own choices on outcomes such as profit, sales, and welfare. The course uses these literatures as well as exercises to both give you broad information on these topics, and equip you to use analytic modeling in your own work. This course builds on prior course content in the Economics core coursework.

Topics in Quantitative Marketing (MKTG-552-0)
This seminar-style class exposes students to working papers in current areas of active research. 2nd, 3rd, and 4th year students are required to enroll. Participants will read, present, and discuss recent papers with the goal of improving their ability to evaluate a paper’s academic contribution and managerial relevance and to further extend their knowledge of models and methods. This class will reinforce the research environment and foster collaboration between students and faculty. One or more faculty can teach the course, and we expect to rotate it among the faculty on a consistent basis. Faculty who teach this course must be careful to coordinate the content relative to the three core classes.

Research (MKTG-590-0)
Independent investigation of selected problems pertaining to thesis or dissertation. May be repeated for credit.

Strategic Marketing Communications in the Digital Age

Explore the power of an integrated marketing communications strategy from fundamental planning to tactical execution utilizing the most current thinking about media channels, customer engagement and measurement. The frameworks and examples provided are applicable to developing both B2C and B2B marketing communications strategies.

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