Proposition of Machine Learning Driven Personalized Marketing Approach for E-Commerce

摘要

The ubiquity of digital devices and Internet has formed a constantly connected online environment which led to the extensive adoption of e-commerce. However, the active participation of growing number of stakeholders intensifies the highly competitive landscape of the dynamic e-commercemarket and the scarcity of trust in e-commerce business impede the generation of consistent sales growth. The obstruction necessitates the implementation of innovative marketing strategies to enhance the relationships with customers to develop customer loyalty. Therefore, a machine learningdriven personalized marketing approach is proposed to facilitate the implementation of personalized marketing in which there are 2 significant sequential elements namely, the development of personalized marketing contents and delivery of the contents to prospective customers. Cluster analysisis employed to perform customer segmentation to discover customer segments due to the capability of the analysis to identify similarities in customer preferences in which the discovered customer segments are used to construct personalized marketing contents. In addition, artificial neuralnetwork is employed to predict prospective customers due to the capability of artificial neural network to comprehend complex relationships between customer demographics and buying behaviour in which the prediction facilitates the delivery of the constructed personalized marketing contentsto potential repeat customer to optimize the marketing initiative. The combination of cluster analysis and artificial neural network empowers the construction of an efficacious marketing pipeline which enhances the competency of e-commerce businesses.