Predictive Modeling in Marketing Analytics: A Comparative Study of Algorithms and Applications in E-Commerce Sector
Department of Digital Marketing, Al-Zaytoonah University of Jordan, Amman, Jordan
Ibrahim A. Abu-AlSondos
Department of Information Technology Management (ITM), College of Computer Information Technology (CCIT), American University in the Emirates (AUE), Dubai 503000, United Arab Emirates (UAE),
Rana Husseini Frangieh
Department of Applied Foreign Languages, Sorbonne University, Abu Dhabi, 38044, United Arab Emirates (UAE),
Anas A. Salameh
Department of Management Information Systems, College of Business Administration, Prince Sattam bin Abdulaziz University, 165 Al-Kharj 11942, Saudi Arabia
Ibrahim Ali Alnajjar
Department of Computer Science, College of Computer Information Technology (CCIT), American University in the Emirates (AUE), Dubai 503000, United Arab Emirates (UAE),
Abstract
This paper examines marketing analytics within the context of E-commerce in Jordan. A variety of algorithms are analyzed in-depth, along with their numerous applications. Together, these eminent e-commerce companies conducted research. According to the evidence, incorporating prediction techniques strengthens the relationship between strategic decision-making processes and positive business outcomes. Comparing the effects of predictive modeling on company decision-making and online sales productivity in Jordan's internet retail sector, these findings are highly significant in various specialist circles and scholarly works pursuing similar lines of inquiry. Utilizing predictive methods, businesses can gain valuable insights to solidify their leadership position and enhance their market standing. By utilizing predictive analytics, Jordanian e-tailers can improve their marketing strategies, increase revenue, and foster continuous development through in-depth model analysis. This article analyzes in great depth how predictive modeling improves decision-making and achieves success in the fast-paced online retail environment.