Due to the importance of Customer behaviour prediction, it is
necessary to have a systematic review of previous studies on this subject. To
this effect, this paper therefore provides a systematic review of Customer
behaviours prediction studies with a focus on components of customer
relationship management, methods and datasets. In order to provide a
comprehensive literature review and a classification scheme for articles on this
subject 74 customer behaviour prediction papers in over 25 journals and
several conference proceedings were considered between the periods of 1999-
2014. Two hundred and thirty articles were identified and reviewed for their
direct relevance to predicting customer behaviour out of which 74 were
subsequently selected, reviewed and classified appropriately. The findings
show that the literature on predicting customer behaviour is ongoing and is of
most importance to organisation. It was observed that most studies investigated
customer retention prediction and organizational dataset were mostly used for
the prediction as compared to other form of dataset. Also, comparing the
statistical method to data mining in predicting customer behaviour, it was
discovered through this review that data mining is mostly used for prediction.
On the other hand, Artificial Neural Network is the most commonly used data
mining method for predicting customer behaviour. The review was able to
identify the limitations of the current research on the subject matter and
identify future research opportunities in customer behaviour prediction