Exploratory Data Analysis and Customer Churn Prediction for the Telecommunication Industry

The telecommunications business is one of the key industries with a higher risk of revenue loss owing to client turnover and environmental impact. Thus, efficient and effective churn management includes targeted marketing campaigns, special promotions, or other incentives to keep the customer engaged in technological progress. There are a lot of machine learning algorithms available now, but very few of them can effectively take into account the asymmetrical structure of the telecommunications dataset. The efficiency of machine learning algorithms may also vary depending on how closely they approximate the real-world telecommunications data rather than the publicly available dataset. As a result, the researchers used various predictive models, including XGBoost, for this dataset. The accuracy achieved on the native dataset is 82.80%. Results show the effectiveness of the predictive model with great technological capabilities.