This paper examines the strengths and weaknesses of four commonly used tools for modeling customer satisfaction data. Most customer satisfaction (CSAT) studies are plagued with multicollinearity, meaning that several of the independent causal variables are highly correlated, resulting in output that may cloak true drivers of satisfaction or dissatisfaction.
This whitepaper on multicollinearity will:
- compare six traditional CSAT modeling techniques
- discuss the relative impact of multicollinearity on each technique
- demonstrate how the various method perform using a case study