Research on Multi-Dimensional Differentiated Marketing Pricing Strategy of Big Data Products and Services

Abstract

Nowadays, the data elements have become the key factors of production with the explosive growth of data business. However, there are still some challenges to the application of traditional market segmentation theory to data pricing, such as market subject segmentation to be innovated, privacy protection segmentation to be strengthened, vicious pricing induced by supermarket segmentation, and absence of market feedback segmentation. Facing new opportunities and challenges, it is of great significance to introduce multidimensional market segmentation theory for pricing big data products and services. In this paper, the segmentation standard was innovated from a multi-dimensional perspective, and the main factors that affect the pricing strategy of big data products and services were studied by combining data statistics and classification, namely, market subject, data protection level, applicable scope of market segmentation and feedback information. Finally, aiming at promoting the development of big data products and services market, market segmentation was carried out according to the multi-dimensional attributes of products, and differentiated pricing strategies were put forward based on the differences in the utility of data products and services.