Churn-Detect
Price sensitivity - Customer churn analysis
Analyzing price sensitivity and its impact on customer churn is necessary to keep the business going. It helps optimize pricing strategies and enhance customer retention for the company.
Client
RV College of Engineering
Services
Data Analysis
Industries
Any B2C company
Date
February 2023
Researching price sensitivity and customer churn involved data analysis using Python, where I applied a Random Forest Classifier to achieve a high predictive accuracy of 92%. Feature importance analysis helped identify key factors influencing churn, and a correlation matrix with a heatmap revealed limited correlation between price sensitivities and churn. Leveraging libraries such as numpy, pandas, sci-kit learn, matplotlib, and seaborn facilitated a comprehensive exploration of the dataset.
The final outcome highlighted the significant role of non-price factors in customer churn, suggesting a need to focus on holistic customer experience improvements. Conclusions emphasized the importance of diversifying retention strategies beyond pricing adjustments, considering the nuanced interplay of various factors in customer decision-making.