Linear Regression for Marketing Budget Optimization
12 Inputs
1 Hour
Intermediate
Industry
retail-and-cpg
Skills
approach
Tools
python
Learning Objectives
Understand the fundamentals of linear regression and its application in Market Mix Modeling.
Identify key factors influencing marketing performance and define them as model variables.
Build and evaluate linear regression models using Python libraries like sklearn and statsmodels.
Interpret regression outputs, including coefficients, p-values, and R-squared metrics, to derive actionable insights.
Overview
In this masterclass, we explore how linear regression can be applied in a marketing budget optimization context using Market Mix Modeling (MMM). Learners will analyze real-world marketing data to determine the impact of various channels on sales performance. The session includes hands-on activities where learners build regression models, interpret key metrics, and make data-driven recommendations for budget allocation.
Prerequisites
- Basic knowledge of Python programming
- A foundational understanding of data manipulation using libraries like pandas and numpy.