Predictive Analytics for Predicting Customer Behavior

Abstract — Making predictions about future events or behaviors based on historical data is the goal of the data analysis discipline known as predictive analytics. The ability to comprehend and forecast client behavior is a key use of predictive analytics. Firms can use predictive analytics to obtain insights into customer behavior and preferences using the massive volumes of digital data generated by customers online. This data can then be used to help firms make better business decisions. To gain a deeper understanding of customer behavior and support predictive analysis, the study suggests using behavior informatics and analytics methodologies. This will help decision-makers make better choices. Additionally covered are the potential uses of predictive analytics in a variety of fields, such as fraud detection and healthcare. Along with the technology and technique involved, predictive analytics' benefits and drawbacks are discussed. Finally, potential research directions and their potential effects on enterprises and society are examined. Keywords- Predictive analytics, Customer behavior, Big data, Machine learning, Statistical analysis, Data mining,