Predictive Analytics: Leveraging Machine Learning for Competitive Advantage in Business

Abstract

In the present age of big data and analytics, the prospects of predictive analysis are revolutionizing strategic management initiatives across most industries. This empirical study focuses on the application of machine learning techniques including, SVM regression, neural networks, and K-means clustering for improving the decision-making on demand forecasting, dynamic pricing, and customer segmentation. With datasets drawn from Kaggle, this research shows how predictive analytics helps organizations to enhance performance and improve customer engagement as a result of such insights. Research evidence suggests that these models do not only help improve the accuracy of forecasting and pricing but also enable the right marketing. The study clearly identifies the important benefits of using predictive analytics and offers direction for future work on ethical model transparency and applications in real time.