Big Data Oriented Planning Of Commercial Management System In Shopping Center A

In the era of big data,feedback economy is affecting every business area with the newcommercial mechanisms and models.As a shopping center in the platform industry,how to use data to drive consumer behaviors has become the most important issue to be considered.At the same time,the shopping centers have been over developed and built in China.Affected by consumption structure evolution and e-commerce blossoming,the challenges to the shopping centers become more and more critical.Meanwhile,with the trend of experiential consumption upgrading,brand expansion and demand of city expanding,it brings a great opportunity to the retail industry.Compared with the traditional consumer behavior,in the era of big data,it tends to be more rational and personalized,social media evaluation referred,and relying less on brand which urges the shopping centers to collect the customer data to predict their consumption,and to guide the service innovation.Based on the SWOT analysis of the competitive environment and the current problems faced by shopping center A,the paper studies the big data planning in the business management system with BSP.It aims to maximize the profits of shopping center A by analyzing the consumption data,customer data,and behavior data to closely connect the shopping center,retail tenants and consumers together,to help them to find the real needs of the consumers,to adjust the business planning and positioning.Finally,it realized that the customer oriented marketing activities could be implemented by dynamic management.This paper focuses on the collection and analysis of three major data categories,and they are consumption characteristics,geographical features and time preference.Hope the suggested system implementation plan to play a reference role.