Prediction of Consumer Behaviour using Random Forest Algorithm

In the ultramodern age of technology, anticipation of market trend is very important to observe consumer behaviour in this competitive world as trends are volatile. Building on developments in machine learning and prior work in the science of behaviour prediction, we construct a model designed to predict the behaviour of Consumer. The aim of this research paper is to examine the relation between consumer behaviour parameters and willingness to buy. First we investigate to find relationship between consumer behaviour to buy products on changing parameters such as environmental factor, organizational factor, individual factor and interpersonal factor. Thus this paper proposes time-evolving random forest classifier that leverages unique feature engineering to predict the behaviour of consumer that affect the choice of purchasing the product significantly. Results of random forest classifier are more accurate than other machine learning algorithm.