The Customer Churn Prediction System Pronosys

Abstract

As it assists businesses in identifying customers who are most likely to terminate their subscriptions or cease using their products, churn prediction is an essential aspect of customer relationship management. In this study, we present a churn prediction system that forecasts the likelihood that a given client will depart using machine learning techniques. The scalability and adaptability of the system permit its implementation in a variety of commercial contexts._x000D_ Prior to identifying the most effective models and predictors for attrition prediction, an examination is conducted on a range of feature selection strategies and machine learning algorithms. Subsequently, the performance of the system is evaluated by employing a dataset comprising real-life customer behavior and instances of churn. The results demonstrate that the system is capable of accurately predicting churn with notable accuracy and recall._x000D_ Additionally, we provide an innovative feature importance ranking algorithm that identifies the most crucial features for attrition prediction, thereby enhancing the model's interpretability. This enables businesses to identify the root causes of customer attrition and take targeted actions to retain those clients who are at risk,_x000D_ In summary, our attrition prediction method offers a valuable asset to organizations striving to enhance customer retention and reduce churn rates By utilizing interpretable feature priority evaluations and machine learning algorithms, the system provides a comprehensive and actionable view of customer behavior that can direct effective retention efforts.