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With the enormous increase in the number of customers using telephone services, the marketing division for a telcom company wants to attract more new customers and avoid contract termination from existing customers. This churn prediction model would be able to provide clarity to the telcom company on how well it is retaining its existing custome…

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Telcom-Churn-Analysis-using-SVM-Algorithm

  • Any business wants to maximize the number of customers. To achieve this goal, it is important not only to try to attract new ones, but also to retain existing ones. Retaining a client will cost the company less than attracting a new one. In addition, a new client may be weakly interested in business services and it will be difficult to work with him, while old clients already have the necessary data on interaction with the service.

  • To help the business, I can predict the churn and can react in time to keep the client who wants to leave. Based on the data about the services that the client uses, I can make him a special offer, trying to change his decision to leave the operator. This will make the task of retention easier to implement than the task of attracting new users.

  • Provided data is from a telecommunications company. The data contains information about almost six thousand users, their demographic characteristics, the services they use, the duration of using the operator's services, the method of payment, and the amount of payment. The task is to analyze the data and predict the churn of users (to identify people who will and will not renew their contract). The work should include the following mandatory items:

    • Description of the data (with the calculation of basic statistics);
    • Research of dependencies and formulation of hypotheses;
    • Building models for predicting the outflow (with justification for the choice of a particular model) based on tested - hypotheses and identified relationships;
    • Comparison of the quality of the obtained models.

Data Dictionary:

  • customerID - customer id
  • gender - client gender (male / female)
  • SeniorCitizen - is the client retired (1, 0)
  • Partner - is the client married (Yes, No)
  • enure - how many months a person has been a client of the company
  • PhoneService - is the telephone service connected (Yes, No)
  • MultipleLines - are multiple phone lines connected (Yes, No, No phone service)
  • InternetService - client's Internet service provider (DSL, Fiber optic, No)
  • OnlineSecurity - is the online security service connected (Yes, No, No internet service)
  • OnlineBackup - is the online backup service activated (Yes, No, No internet service)
  • DeviceProtection - does the client have equipment insurance (Yes, No, No internet service)
  • TechSupport - is the technical support service connected (Yes, No, No internet service)
  • StreamingTV - is the streaming TV service connected (Yes, No, No internet service)
  • StreamingMovies - is the streaming cinema service activated (Yes, No, No internet service)
  • Contract - type of customer contract (Month-to-month, One year, Two year)
  • PaperlessBilling - whether the client uses paperless billing (Yes, No)
  • PaymentMethod - payment method (Electronic check, Mailed check, Bank transfer (automatic), Credit card (automatic))
  • MonthlyCharges - current monthly payment
  • TotalCharges - the total amount that the client paid for the services for the entire time
  • Churn - whether there was a churn (Yes or No)

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With the enormous increase in the number of customers using telephone services, the marketing division for a telcom company wants to attract more new customers and avoid contract termination from existing customers. This churn prediction model would be able to provide clarity to the telcom company on how well it is retaining its existing custome…

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