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Published in:
2019 | OriginalPaper | Chapter
7. Identifying Drivers of Outcomes: Linear Models
Authors : Chris Chapman, Elea McDonnell Feit
Published in: R For Marketing Research and Analytics
Publisher: Springer International Publishing
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Abstract
In this chapter we investigate linear models, which are often used in marketing to explore the relationship between an outcome of interest and other variables. A common application in survey analysis is to model satisfaction with a product in relation to specific elements of the product and its delivery; this is called “satisfaction drivers analysis.” Linear models are also used to understand how price and advertising are related to sales, and this is called “marketing mix modeling.” There are many other situations in which it is helpful to model an outcome, known formally as a response or dependent variable, as a function of predictor variables (also known as explanatory or independent variables).