Data-Driven Customer Experience Enhancement using Behavioural Analytics

Shifa Khan, Simon Fernandes
Department of Computer Science, M.Sc. (Data Science) Savitribai Phule Pune University, Pune, India

Abstract:Customer experience (CX) has emerged as a critical factor for organizational success in highly competitive digital markets. Conventional CX measurement techniques such as surveys and feedback forms provide limited and delayed insights into customer behavior. With the rapid growth of digital platforms, large volumes of behavioral data are generated continuously through customer interactions. Behavioural analytics leverages this data to understand customer patterns, predict future behavior, and enable personalized engagement strategies. This paper presents a data driven approach to enhancing customer experience using behavioural analytics. It discusses key data sources, analytical techniques, a proposed behavioural analytics model, and a working machine learning implementation for churn prediction. The study demonstrates how data-driven insights can improve customer satisfaction, retention, and overallbusiness performance.
Keywords: Customer Experience, Behavioural Analytics, Data-Driven Analytics, Personalization, Churn Predictio