Predicting Consumer Behaviour in Digital Market: A Machine Learning Approach
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Date
2019-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Innovative Research in Science, Engineering and Technology
Abstract
In recent times, customer behaviour models are typically based on data mining of customer data, and
each model is designed to answer one question at one point in time. Predicting customer behaviour is an uncertain and
difficult task. Thus, developing customer behaviour models requires the right technique and approach. Once a
prediction model has been built, it is difficult to manipulate it for the purposes of the marketer, so as to determine
exactly what marketing actions to take for each customer or group of customers. Despite the complexity of this
formulation, most customer models are actually relatively simple. Because of this necessity, most customer behaviour
models ignore so many pertinent factors that the predictions they generate are generally not very reliable. This paper
aims to develop an association rule mining model to predict customer behaviour using a typical online retail store for
data collection and extract important trends from the customer behaviour data.
Description
Staff Publication
Keywords
Association rule mining,, Apriori,, digital market,, consumer behavior,, Machine learning.