Abstract This article will examine new CX research tools for conducting key driver analysis. More specifically, this article puts forth a process and empirically demonstrates the value of employing latent class regression (LCR) and correlated components regression (CCR) together for conducting key driver analysis with CX data. In this research study, LCR was employed first to identify the number of key driver segments along with segment membership for each customer. Subsequently, CCR was implemented to refine the key driver analysis for each segment. The results show that two key driver segments exist, with each segment possessing significantly different CX attribute importance scores, performance scores, and prioritized improvement opportunities.
|Journal||Quirks Marketing Research Review|
|State||Published - Oct 2017|