3 credits
Fall 2026 Lecture Upper Division
This course covers essential decision models and strategic metrics that form the cornerstone of marketing analytics. Using the insight gained in the course, students can predict the outcome of marketing plans to boost return. This course introduces essential statistical tools, strategic metrics, and AI-assisted methods foundational to modern marketing analytics, with an emphasis on managing effective marketing campaigns. The goal is to demonstrate the substantial benefits analytics brings to marketing decision-making, providing students with practical, coding-based experience supported by AI-driven learning. Emphasizing hands-on application, students will immediately utilize analytical techniques to derive insights from marketing data, enhancing strategic decisions to create value and competitive advantage. Key topics include data visualization, exploratory data analysis, regression modeling, A/B testing, experimental design, customer segmentation, and predictive analytics marketing investment (ROMI). The course emphasizes hands-on learning so students can immediately apply the econometric tools and techniques on a variety of marketing applications. A number of relevant topics are discussed, such as market sizing, forecasting and positioning, promotion budget allocation, and profit maximization. The final piece of this course is guiding the students on how best to craft data-driven presentations to key stakeholders through the use of an experiential learning project provided by an external client.
Learning Outcomes1Enhance the student's knowledge on Advanced Modeling Techniques, such as how and when to apply Logistic Regression, Logit, Multinomial Logit, Ordinal Logit, and Tobit.
2Showcase situations across a variety of marketing topics (pricing, sales, advertising, new product development, etc.) where analytical methods can bring greater insight to the marketing practitioner.
3Apply the above information to a real-world consulting project and deliver not only managerial insights, but also a data-driven presentation.
Prerequisites
Restrictions
made by Purdue students.