Computational Advancements and Application of Bayesian Techniques in Marketing

Abstract

Several inferential procedures are advocated in the literature. The most commonly used techniques are the frequentist and the Bayesian inferential procedures. Bayesian methods afford inferences based on small data sets and are especially useful in studies with limited data availability. Bayesian approaches also help incorporate prior knowledge, especially subjective knowledge, into predictions. Considering the increasing difficulty in data acquisition, the application of Bayesian techniques can be hugely beneficial to managers, especially in analysing limited data situations like a study of expert opinion. Another factor constraining the broader application of Bayesian statistics in business was computational power requirements and the availability of appropriate analytical tools. However, with the increase in computational power, connectivity and the development of appropriate software programmes, Bayesian applications have become more attractive. This chapter attempts to unravel the applications of the Bayesian inferential procedure in marketing management.

Citation

Srivastava, R. and Sanjeev, M.A. (2023), "Computational Advancements and Application of Bayesian Techniques in Marketing", Misra, R.K., Shrivastava, A. and Sijoria, C. (Ed.) Technology, Management and Business (Advanced Series in Management, Vol. 31), Emerald Publishing Limited, Leeds, pp. 189-200. https://doi.org/10.1108/S1877-636120230000031015