Converting an E-commerce prospect into a customer using streaming analytics

E-commerce is one of the fast growing business models of the present day. Shopping from anywhere & anytime has become a key feature of E-commerce. Because of the huge amount of data generated from the vast population of people & connected devices has posed challenges to manage the stream of data arriving from every device in real time. Big data analytics is a process of examining this big data to uncover unknown correlations, hidden patterns, & other useful information that can be used to make better decisions. In many applications of E-commerce, Real-time & incremental streaming approach for data analysis within a smaller time window is needed to enable proactive care. In this paper, we propose a novel approach for converting an e-commerce prospect into a customer using streaming analytics. The approach uses Markov chains to identify the usage profile and threshold nearest neighbour clustering algorithm as one of the clustering techniques to group the user actions onto clusters.