Course Detail (Course Description By Faculty)

How should a firm set prices when customers differ in their willingness to pay? Which consumers should be targeted with an offer or advertisement? What is the ROI of a digital ad campaign?

In this course, you will learn how to address these and other questions in modern marketing analytics by combining big data with AI/ML methods. We will use AI agents to reduce the coding burden and focus instead on developing the key skills needed to apply these tools effectively: framing questions appropriately, evaluating the quality of the output, and using the results to guide business decisions.

We will cover a broad range of topics, including demand modeling, customer relationship management, optimal targeting, and digital marketing. Throughout the course, you will work through the full pipeline of a marketing analytics project: processing raw data, applying statistical and machine learning methods, generating predictions, and translating those predictions into concrete marketing decisions. In-class presentations will help you develop the ability to communicate and defend the conclusions of your analyses.

Cannot enroll if BUSN 37105, 37103, 37113 or 20620 taken previously. No MiM students.

Lecture Notes

Grades are determined based on the following components:

• Assignments: 35%

• In-class presentation: 35%

• Class participation and discussion: 30% 

I will use the maximum average GPA allowable under the Booth School grading policy. I will submit provisional grades for graduating students who are meeting the course requirements.

Grades