With the development of online shopping in recent years, more and more e-commerce companies realize the importance of carefully formulating competitive discount policies to attract consumers. JD.com, one of China's largest B2C e-commerce websites, is famous for its high-quality products and excellent supply chain. Whether there is room for improvement in its discount policy, that is, whether it can adjust the discount for different consumer groups to improve its discount policy is the main research issue of this paper. This article used the sales data of JD.com in March 2018. This paper firstly interprets the original data and then integrates the original data. At the same time, to facilitate the subsequent analysis, this paper uses the idea of the control variable method to analyze the data and each customer's characteristic studied. Grouping according to characteristics, and then using linear regression to analyze the data of each group to explore the relationship between different types of discounts and customer characteristics, and find out the determinants of discounts and whether there are significant differences in discounts for different consumers groups. Based on the above research methods, this paper obtains the degree of influence of different customer characteristics on different discount types and the total discount rate and finally recommends JD.com, so that it can improve its discount policies to a certain extent, to attract more consumers and gain more revenue.

No abstract

Abstract

No abstract

No abstract