The Application of Multi-Criteria Decision Making in Precision Marketing: a Case of Shopping Mall

With the information and communication being progressed and upgraded, the collision of the virtual and physical worlds is fundamentally changing the customer purchasing behavior. The retail industry is in the midst of a customer revolution. There are industrial transformations that trigger the vigorous evolution and development. When Internet arises, physical retail faces challenges. Irrespective the rapid change in digital technologies and the popularity of handheld devices, “pure e-commerce“ cannot meet the lively consumer demand. In the data driven Internet of Things (IoT), “new retail” infiltrated the overall consumption structure and consumer groups with various patterns and affected the overall retail business model. The emergence of “new retail” not only redefined the new scene of consumer channel, but also brought information transmission innovation. Data-driven decision-making to provide exclusive target customers or groups sales and service. Customer relationship management (CRM) for physical retail operators more effectively integrate store and customer data to provide customer touched experience. This study aims to establish the precision marketing of consumer activity recommendation system based on the CRM database of mall member information. Initially, the depth interview and Delphi technique are used to identify the criteria. Then, AHP is used to obtain the criteria weights. Finally, SAW is used to rank the scores of all alternatives based on the real sample data. Data mining technology is adopted to identify the customer preference. The expected contribution of this research is to propose a hybrid model for business to reach the target of precision marketing.

Project ID:PB10708-1964
External Project ID:MOST107-2410-H182-006