Big Data-Driven Customer Experience in E-Commerce: Personalizing User Journeys with Advanced Analytics

In the dynamic nature of business especially in e-commerce, the management of customers has greatly been made to be a cardinal focus of any organization. This paper aims to analyse and discuss applications of big data and customer big data experience to improve the overall customer journey. Application of modern technologies including machine learning, deep learning, and processing real-time data is in the scope of the proposed methodology, which contains a full set of stages including data collection, preprocessing and feature engineering, as well as recommendation generation at the personal level. Neural collaborative filtering (NCF) improved performance results, and the precision and recall rates are greater than 93% suggesting that these methods can better capture complex patterns of user behavior. Real-time personalization also brought sustainable benefits regarding the most important metrics: a 50% increase in average session duration, a 73.5% increase in conversion, and a 38.2% decrease in the cart abandonment rate. Strong customer privacy protection measures were in place to address legal requirements including GDPR, and algorithm ethicality, specifically in bias in personalization guarantee. The results highlight the innovativeness of big data approach in designing positive buying experiences bye-commerce firms. This research offers recommendations for organizations that want to use advanced analytics for digital business innovations based on customer value, which sets the basis for future developments in the realm of personalized electronic commerce.