The telecom industry is highly competitive, and customer retention is a critical factor in ensuring the success of any telecommunications company. Orange S.A., a prominent French multinational telecom corporation, is facing the challenge of customer churn, where a significant number of users are canceling their subscriptions. In response to this issue, our exploratory data analysis (EDA) project aims to delve into the Orange Telecom's Churn Dataset, which comprises meticulously cleaned customer activity data and churn labels indicating whether a customer has canceled their subscription. The primary objective is to gain insights into the key factors contributing to customer churn and develop effective strategies to mitigate this trend.
The dataset provides a comprehensive view of customer behavior, encompassing various features that reflect user interactions, preferences, and usage patterns. Through extensive exploration and analysis of this data, we aim to uncover underlying patterns, correlations, and potential indicators that may contribute to customer churn. Understanding the reasons behind customer attrition is crucial for Orange to implement targeted measures aimed at customer retention. Our analysis will involve examining factors such as call duration, data usage, customer service interactions, and other relevant features to identify patterns that differentiate churned customers from those who remain loyal. As part of the project, we will employ statistical and machine learning techniques to model customer churn prediction. By developing predictive models, we aim to create a tool that can forecast the likelihood of a customer churning based on their behavior and interactions with Orange's services. This predictive capability will enable the company to proactively address potential churners by implementing personalized retention strategies.
In addition to predicting churn, our EDA will highlight actionable insights and recommendations for Orange to enhance customer satisfaction and loyalty. This may involve optimizing service plans, improving customer service processes, and introducing targeted promotions to incentivize customer retention. By identifying and addressing the root causes of churn, Orange can create a more customer-centric approach, ensuring that users receive the best value and experience from their telecom services.
The success of this project is not only measured by the accuracy of the churn prediction models but also by the real-world impact on reducing customer churn rates. Implementing the insights gained from this analysis will contribute to Orange's ability to retain more customers, enhance service quality, and stay at the forefront of the competitive telecom landscape. Ultimately, the project aligns with Orange's business objectives of providing better services, understanding customer needs, and maintaining a strong position in the ever-evolving telecommunications industry. Through data-driven decision-making, Orange aims to ensure customer satisfaction, loyalty, and sustainable growth in a dynamic market