An introduction to an old acquaintance: using Bayesian inference in sales research.

Given the scant attention paid to Bayesian inference in the academic sales literature, researchers could be forgiven for believing that frequentist methods provide the only feasible way for sales researchers to derive important insights for both theory and practice. The purpose of this research is to demonstrate that this belief overlooks the considerable value that Bayesian inference can provide to sales theory and practice. In so doing, we outline fundamental differences between Bayesian and frequentist methods, and describe how these differences can lead to different empirical insights. We review the extant literature that employs Bayesian methods, with an emphasis on how these studies provide insight that may elude frequentist methods. Then, using a sample of 146 B2B salespeople, we empirically demonstrate that the use of Bayesian methods is both within the methodological reach of the vast majority of sales researchers, and can also provide different empirical insights using the same dataset, than would frequentist methods. We then provide some future research ideas to encourage sales researchers to employ Bayesian methods in their own research. Finally, in hopes that readers do not view Bayesian inference as a "silver bullet", we examine some drawbacks and limitations of this intriguing method of statistical inference. [ABSTRACT FROM AUTHOR]

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