Analysing the Effect of Platform and Operating System Features on Predicting Consumers’ Purchase Intent using Machine Learning Algorithms

Ramazan Esmeli, Alaa Mohasseb, Mohamed Bader-El-Den


Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers’ purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users’ behaviours is explored. In addition, the effect of users’ platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users’ operating system and platform types as features. The results showed that the users’ purchase intentions and behaviours are correlated with these features.


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