Do Sales Promotions Affect Dynamic Changes in Sales Outcomes: Estimation of Dynamic State of Product Sales

In recent years, the consumer tastes have become complicated and store managers are increasingly required to execute multiple promotions and increase sales. In this research, we introduce a dynamic Bayesian model that applies a Cauchy distribution to the estimation of the dynamic state of a product sales trend. The time evolution of the sales data trend reflects customer purchase behavior, and shows a characteristic variation for each brand. We show that the proposed model can better explain the dynamic change of sales by comparison with a regression model. We compare the benchmark and proposed models based on variance, fitness, and prediction accuracy. We show that detecting change-points lurking in time series data of sales leads to important management improvement suggestions.