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Natalie Mizik and Dominique M. Hanssens
Angela Y. Lee and Alice M. Tybout
Marketing academics, managers, public policy makers, and litigators often ponder questions that involve relationships between alternative treatments or strategies and people’s responses. Among the variety of research approaches available to them, only experimental designs afford strong causal inferences about such relationships. The chapter reviews the nature of such experiments, discusses the role of laboratory versus field experiments and explores the design of lab experiments along various dimensions.
Edited by Natalie Mizik and Dominique M. Hanssens
G. Scott Erickson
Chapter 1 covers definitions and methods related to big data systems. Placing big data monitoring systems in the context of loyalty programs developed by Tesco/dunnhumby and Caesar’s, the discussion characterizes what big data is, how systems collect and share it, and how it is used to enhance day-to-day decision-making. Concepts like key performance indicators and action-oriented algorithms are included. Coverage then moves to more in-depth marketing analytics related to big data. Here, the marketing approaches of Spotify and Bloomberg are used to illustrate and explain how analysts cut the data in different ways looking for insights as well as conducting predictive and clustering analysis.