Transformation and Upgrading of Fresh E-Commerce Mode Based on Big Data Conception

Abstract

In recent years, the fresh products market online in China has developed rapidly with a rapid growth rate and a large transaction volume. Three major fresh e-commerce modes have been basically formed, namely, platform fresh e-commerce mode, vertical fresh e-commerce mode and online sales mode of physical supermarket [1]. These three models have their own advantages and disadvantages, which are insufficient to meet the needs of customers of online fresh products. This paper analyzes the needs of fresh online shopping customers, including the main reasons, key factors, channels and types, frequency and the concentration time period of fresh online shopping, and analyzes the existing problems of fresh e-commerce model, including imperfect fresh product standards, distribution time difficult to meet customers, limited types for customer purchased actually, low frequency. Then, it puts forward the regional + platform + customer’s E-commerce model, and establish a distribution ecosystem, customer relationship management methods and product quality and safety management based on big data. The purpose of this article is to make up for the shortcomings of the existing fresh e-commerce model and promote the healthy development of fresh e-commerce in China.