Enhancing user experience with detailed dataanalysis andintelligent systems

Abstract

Enhancing the user experience (UX) is crucial in the quickly changing digital landscape to keep users engaged and satisfied. This study presents an innovative approach for improving user experience (UX) through the utilization of advanced analytical methodologies, intelligent systems, and user session data. We store the data in a MongoDB database by gathering comprehensive user logs using JavaScript scripts and processing them using the Flask framework. After that, this data is analyzed to produce useful insights like heat maps, session replays, and different metrics related to user behavior. Our system uses Random Forest algorithms for its recommendation system and K-means and DBSCAN algorithms for anomaly detection. In order to improve user engagement analysis even more, we also suggest adding gaze tracking and facial expression detection in the future. Elastic Load Balancer (ELB) and Linux OS deployed on an AWS virtual machine (VM) guarantee a scalable and secure environment.