Machine Learning as an Efficient Tool to Support Marketing Decision-Making

Personalization and relevance have become more and more critical factors for all kind of media used in digital marketing. Email marketing which is the most used media in the field can be more effective if emails can reach the right customers at the right time. However, the use of data analytics technics and machine learning algorithms can help marketers to make a good decision about how to plan a successful campaign strategy based on legitimate predictive intelligence. In this paper, our research team will present several experiences in how to make a learning model, to predict the clicks of the targeted emails. The proposed model will be based on several features extracted from different campaigns and email recipients profiles. Then it will be established by using five Machine learning algorithms for classification including Decision tree, Bagging classifier, adaptive Boosting, Neural Network, Random Forest to choose which one of them is suitable to predict clicks rates according to several criteria like subject-lines, from-lines, device, offers and vertical.