Customer churn, also known as customer attrition, refers to the tendency of clients or customers to abandon a brand and cease being a paying client of a specific business or organization. A customer churn rate is the percentage of customers who stop using a company's services or products during a specific time period. A customer may leave after a series of bad experiences (or even just one). And if a large number of dissatisfied customers leave at the same time, the financial and reputational costs would be enormous.
I build a model using logistics regression machine learning approaches to predict the best outcome.
DATASE STRUCTURE
- This is a public dataset; the format is listed below.
- There are 10000 rows and 14 different columns in the dataset.
- Exited is the target column in this case.
VARIABLE MEANING The following data dictionary contains information on all of the columns:
- Variable Definition
- RowNumber :Unique Row Number
- CustomerId : Unique Customer Id
- Surname: Surname of a customer
- CreditScore: Credit Score of each Customer
- Geography: Geographical Location of Customers
- City_Category: Category of the City (A,B,C)
- Gender: Sex of Customers
- Age: Age of Each Customer
- Tenure: Number of years
- Balance: Current Balance of Customers
- NumOfProducts: Number of Products
- HasCrCard: If a customer has a credit card or not
- IsActiveMember: If a customer is active or not
- EstimatedSalary: Estimated Salary of each Customer
- Exited: Customer left the bank or Not (Target Variable)