Customer Analytics addresses how to use data analytics to learn about and market to individual customers. 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. This is the key part of learning how to take advantage of Big Data. 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. The course uses a combination of lectures, cases, and case assignments to learn the material. Students will learn all stages of the analytics process: how to identify marketing problems that can be addressed with analytics, how to decide which analytical method is best suited for a specific marketing problem, how to conduct the analysis using modern-day statistical and machine learning methods in R, how to interpret the results, and how to use the analytical results to make better marketing decisions. This course takes a very hands-on approach with real-world databases and equips students with tools that can be used immediately on the job. This course focuses specifically on how companies can use individual-level data to target customers, recommend products to them, predict their purchasing patterns, and retain them over the long run. Students who are interested in other marketing analytics topics such as automated product development, algorithmic price optimization, online advertising, platform design, and social media are encouraged to also take the other classes in the Foster marketing analytics specialization: Analytics for Marketing Decisions and Digital Marketing Analytics.