Subdividing trade area of cigarette retail stores based on big data analytics

The traditional partition method of trade area based on location information can not reflect changes of trade area, affects the launch of products and other marketing decisions with use of massive mobile terminals. Based on the analysis of the traditional partition method on trade area, this paper proposes a method to subdivide trade area based on big data analytics by focusing on the correlation and real-time data of trade area, which we name it micro trade area partition (MTA partition). By using about 700 retail stores´ data of Guiyang Tobacco Company in a certain area from Jan to Mar in 2014, the validity of the proposed method has been verified. The result shows subdividing trade area with the proposed method is valuable for practical applications, and supports marketing decisions for Guiyang Tobacco Company.