Prepare for marketing mix modeling interviews with a structured sequence of technical, commercial and communication questions. This course is designed for analysts, data scientists, marketing scientists and marketers who want to explain MMM concepts clearly and connect modeling decisions to business needs. Across ten video lectures, the course moves from definitions and measurement approaches to data, statistical foundations, transformations and model development. You will review how MMM differs from attribution and incrementality testing, what data a model needs, and how issues such as correlated media, omitted controls, autocorrelation and endogeneity influence the discussion.
The middle lectures focus on adstock, saturation, variable selection and validation. They provide material for explaining the reasoning behind a specification and for discussing why model fit alone cannot establish a reliable recommendation. You will then examine ROI and ROAS, average and marginal returns, budget constraints, Bayesian ideas and experimental calibration.
The final lectures apply these concepts to interview scenarios and stakeholder conversations. Topics include unexpected coefficients, limited data, disagreement with model outputs, refresh cadence and communicating results to a non-technical audience. Behavioral examples provide a structure you can adapt to your own experience while keeping your account of actions and results accurate.
