Abstract

The development of internet and e-commerce websites has led to the digitalization of\ndata. Digital data in massive numbers leaves traces of what customers see, what they read, their\ninvolvement, and behavior which can be mined for learning experiences. Predictive analytics in\ndata utilization, statistical algorithms and machine-learning techniques were used to identify\npossible trends, events and behaviors based on historical data. There is a countless variety of\nresearch so far with the end goal to predict customer intention of items. Several techniques have\nbeen accessible in data mining and supervised learning for predicting customer intention, for\nexample, Recurrent Neural Networks, Session-based algorithms, etc... In this paper, the\ndifferent strategies that are available and used for forecasting customer prediction have been\ndiscussed.