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Customer Churn and Reasons Analysis



Customer churn rate is an important metric that companies should follow carefully to identify and prevent customer churn. Customer abandonment rate analyzes help solve these problems by identifying the reasons for customer churn. In this project, we will analyze customer abandonment rates and determine the reasons for abandonment by examining the demographic characteristics and behaviors of customers who abandon.


Dataset Description

The data set we created for this project includes customer demographic information, subscription types, payment methods and customer abandonment situations. The data set is contaminated with incomplete, erroneous and outlier data, just like real-world data.

  • CustomerID: Unique ID of the customer

  • Gender: Customer's gender (Male, Female, Other)

  • Age: Customer's age

  • Region: The region where the customer lives (North, South, East, West)

  • Tenure: Duration of customer stay in the company (in months)

  • SubscriptionType: Subscription type (Basic, Standard, Premium)

  • MonthlyCharges: Monthly charge

  • TotalCharges: Total charges paid

  • NumOfProducts: Number of products the customer has

  • ContractType: Contract type (Month-to-month, One year, Two year)

  • PaymentMethod: Payment method (Electronic check, Mailed check, Bank transfer, Credit card)

  • Churn: Customer abandonment status (Yes, No)


Project Steps

  1. Data Loading and First Look: We will load the dataset and get an overview. We will examine the structure of the data and detect missing or incorrect data.

  2. Cleaning of Missing and Erroneous Data: We will fill in the missing values and correct the incorrect data. In this step, we will perform the necessary cleaning operations to ensure the accuracy and integrity of the data.

  3. Calculation of Customer Abandonment Rates: We will calculate customer abandonment rates for certain periods.

  4. Demographic and Behavioral Analysis: We will analyze the demographic characteristics and behavior of abandoning customers.

  5. Determining Reasons for Abandonment: We will determine the reasons for abandonment by examining the data of abandoned customers.

  6. Behavioral Analysis: We will identify signs of abandonment by analyzing the behavior of abandoned customers in the last 6 months.

  7. Visualization of Results: We will present the analysis results by visualizing them.



 

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