Public sample Data files
Understanding Customer Churn: Analyzing Key Variables to Predict and Retain Customers
The table contains customer data with key variables such as age, gender, tenure, support calls, payment delay, subscription type, contract length, total spend, last interaction, and churn status. This data can be used to analyze customer behavior, predict churn rates, and optimize marketing strategies to retain customers.
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