• Refreshers on old topics:
  • algebra and statistics, with a special focus on linear regression
  • 4 Ps
  • Basic Principles of Causality
• Price modeling
• Promotion modeling
• Model Validation and Diagnostics
• (Time permitting) Advanced Techniques:
  • Adstock,
  • Lag Effects,
  • Diminishing Returns
• Stakeholder management and communication

The course is meant as a gentle introduction to the complex world of MMM. By the end of this course, students will be able to:

• Understand the role of MMM in marketing and business strategy.
• Identify the types of data needed to build an MMM.
• Apply linear regression to model marketing effectiveness.
• Evaluate model performance using statistical metrics.
• Interpret and communicate marketing insights from MMM analyses.
• Develop a basic MMM from raw data through to final presentation.

• Students must attend at least 80% of the lectures. 
• Absences must be communicated in advance.

Lectures and Workshop-like sessions. Students will be given content and will have the chance to practice with coding exercises. 

• Quizzes/Participation: 30%
• Exam: 30%
• Final Project: 40%

Students must have attended any introductory course in statistics and be familiar with R. 

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• Basic Statistics (mean, variance, correlation, regression fundamentals)
• Familiarity with Marketing Principles
• Basic familiarity with R