Product Pricing With Marketing Data Under Risk Using Business Intelligence

Abstract

Since product pricing is a significant decision for producers and is known as a challenging problem in today’s marketing operations, the aim of this study is to design an integrated decision support system for pricing. The emerging business environment is highly dynamic in which only companies being higher in terms of competitiveness can succeed in achieving a sustainable market. Nowadays, most companies often use complicated information systems such as business intelligence systems for effective decision making and analytics. Here, by using pricing methods the prices of products are determined on the basis of marketing data under the terms of risk so that to maximize revenue along with fulfilling customers’ demands. A case study is reported to show the effectiveness of the approach. There, we analyzed different effects of our proposed pricing models and studied the influences on the purchase behavior of the customers.