DOMAIN: Telecom
•CONTEXT: A telecom company wants to use their historical customer data and leverage machine learning to predict behaviour in an attempt to retain customers. The end goal is to develop focused customer retention programs
• DATA DESCRIPTION: Each row represents a customer, each column contains customer’s attributes described on the column Metadata. The data set includes information about: • Customers who left within the last month – the column is called Churn
• Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies
• Customer account information – how long they’ve been a customer, contract, payment method, paperless billing, monthly charges, and total charges
• Demographic info about customers – gender, age range, and if they have partners and dependents
•PROJECT OBJECTIVE: Build a model that will help to identify the potential customers who have a higher probability to churn. This will help the company to understand the pain points and patterns of customer churn and will increase the focus on strategising customer retention.