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A Case Study from the Perfume Industry

This tutorial covers Driver Analysis and Product Optimization with Bayesian networks and BayesiaLab. It provides hands-on examples of how Bayesian networks can be used effectively in the field of marketing science.


Secondly, we want to utilize the generated understanding of consumer dynamics so product developers can optimize the characteristics of the perfumes under study in order to increase purchase intent among consumers, which is our ultimate business objective. Using Bayesian networks - and BayesiaLab as the software tool - this optimization process is feasible for the first time and represents a major innovation for product development.

File Download

Download the white paper here (7 MB)