Artificial Intelligence Techniques Applied in Precision Marketing: A Survey

Abstract

After entering the 21st century, various fields knew significant transformation, like medicine, engineering, etc., due to the fast advancement of artificial intelligence (AI) and the arrival of the big data era. The application of AI techniques in marketing became necessary to improve the marketing strategy for guaranteeing a company's long-term growth. Based on recorded data and appropriate training, artificial intelligence can forecast consumer preferences and make recommendations to accomplish precision marketing. Precision marketing based on AI techniques can provide personalized communication between customers and companies, attract prospective clients, build targeted marketing recommendations for high-value clients, and reduces marketing costs. Therefore, this paper presents a survey on the current trends of AI applications in precision marketing. This survey will introduce and review the artificial intelligence approaches applied to precision marketing in the literature, which can be divided into three categories: ma-chine learning, data mining, and recommendation systems. In this study, we have studied and applied a meta-analysis to pick up the more used methods. Consequently, we find that RF, SVM, and NN, for machine learning, K-means, Naïve Bayes, and CHAID Decision Tree for data mining, and collaborative filtering for recommendation systems provide better results in the literature. This article aims to review these methods based on their algorithms and strategies and discuss their strengths and weaknesses. This study provides a reference for searchers in this domain.

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