Blake McShane joined the marketing faculty at the Kellogg School of Management in 2010 as a Donald P. Jacobs Scholar. He has developed and applied statistical methodology to topics ranging from optimizing internet ad-serving algorithms to forecasting home runs in baseball. His specific research interests include Bayesian hierarchical modeling, statistical learning, and generalized Markov models. More generally, he seeks to develop statistical methods to accommodate the rich and varied data structures encountered in business problems and to use these methods to glean insight about individual behavior so as to test and supplement existing theories. Blake earned his PhD and MA in Statistics, MA and BA in Mathematics, and BS in Economics from the University of Pennsylvania .
**This course was formerly known as MKTG-953-0**Marketing is evolving from an art to a science. Many firms have extensive information about consumers' choices and how they react to marketing campaigns, but few firms have the expertise to intelligently act on such information. In this course, students will learn the scientific approach to marketing with hands-on use of technologies such as databases, analytics and computing systems to collect, analyze, and act on customer information. While students will employ quantitative methods in the course, the goal is not to produce experts in statistics; rather, students will gain the competency to interact with and manage a marketing analytics team.
We will use the statistics program R in Customer Analytics. R is harder to use that Stata but has become the industry standard (together with Python) and is extremely good for data management, visualization, and Machine Learning.Before you start the course, you will need to learn how to use R using tutorials and screencasts I will make available on December 15, 2018. There will be a quiz to make sure that you are sufficiently proficient in R before the course starts. Please do not take this class if you are not willing or able to make this investment.