Churn analysis is the evaluation of a company's customer loss rate in order to reduce it and also referred to as customer attrition rate.Customer churn forecast is a difficult problem in many corporate sectors, particularly the telecommunications industry. The introduction of artificial intelligence (AI) and machine learning (ML) technologies in recent years has resulted in improved company performance. Customer churn is a major problem and one of the most important concerns for large number of companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn.
The main contribution of our work is to develop a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn. Churn prediction will help companies to plan their strategy accordingly and can use the robust model to analyze how far they can retain the customers.
Techniques and Agorithms applied :
- Loading and examining data
- Data wrangling
- Data manipulation
- Data Preprocessing
- Feature Scaling
- Model building
- Model Validation
- Model Evaluation
- Logistic Regression