DataCamp
FreeBuilding Response Models in R
4.9(30)3k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate R course connects marketing data with statistical modeling to quantify how promotional tactics influence consumer behavior. By evaluating aggregate sales records and individual-level customer choice data, you will learn to build market response models that measure price elasticity, promotional effectiveness, and overall campaign ROI.
Who It\'s For
Marketing analysts, data scientists, and business strategists who want to apply statistical regression and choice models in R to evaluate marketing campaign performance.
Key Takeaways
- Market Response Fundamentals: Understand how digital marketing data translates into empirical market response equations.
- Price & Promotion Sensitivity: Quantify the exact impact of pricing adjustments, discounts, and promotional channels on sales volumes.
- Individual Choice Data: Analyze discrete choice data to model consumer decision-making and preferences.
- Marketing Optimization: Interpret model coefficients to deliver actionable recommendations for maximizing marketing return on investment.
About this course
Almost every company collects digital information as part of their marketing campaigns and uses it to improve their marketing tactics. Data scientists are often tasked with using this information to develop statistical models that enable marketing professionals to see if their actions are paying off. In this course, you will learn how to uncover patterns of marketing actions and customer reactions by building simple models of market response. In particular, you will learn how to quantify the impact of marketing variables, such as price and different promotional tactics, using aggregate sales and individual-level choice data.
Price
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