Telecom customer behavior analysis using naïve bayes classifier

Abstract

A deep understanding of customer's needs and efficient analysis of customer behavior is such a measurement tool on which the paramount success of each enterprise relies upon. The customer retention ability is being focused on effective studies of potential customers, better decision-making, and enhanced business processes. Naive Bayes (NB) classifier, a simple classifier can be used for anticipating customer behavior. Through an excellent understanding of customers and their consuming behavior, a firm can retain loyal customers, improve its online footprint, forecast how customers will react to the company's marketing strategies, enhance business policy to discover new consuming areas, and boost profits income. The goal of this study is to look into the purchasing habits of telecom firm customers to help them be one of the leading brands in terms of implementing services in the telecoms sector. We conducted our data analysis on a customer records dataset from a telecommunication company, composed of various service usage records of its customers from various states across the United States of America.