Do We Halo or Form? A Bayesian Mixture Model for Customer Satisfaction Data

Identifying the drivers of overall customer satisfaction assumes that the component scores can be uniquely recalled and reported from memory. If the component scores are a reflection of an overall measure, such as with haloed responses, instead of containing independent information on its formation, then they should not be used in a driver analysis. There is likely a mixture of formed and haloed responses in all surveys of satisfaction, which potentially distorts inferences about the relationship between the component scores and the overall measure of satisfaction. In this paper we develop a Bayesian mixture model that effectively separates out the haloed responses and apply it to two customer satisfaction datasets. The proposed model results in improved fit to the data, stronger driver effects, and more reasonable inferences.

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