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The objective of this case is to predict the whether the customer will churn or not. Churn (loss of customers to competition) is a problem for companies because it is more expensive to acquire a new customer than to keep your existing one from leaving. This problem statement is targeted at enabling churn reduction using analytics concepts.

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churn_reduction's Introduction

CHURN-REDUCTION-R-PYTHON

The objective of this case is to predict the whether the customer will churn or not. Churn (loss of customers to competition) is a problem for companies because it is more expensive to acquire a new customer than to keep your existing one from leaving. This problem statement is targeted at enabling churn reduction using analytics concepts.

Attribute Information:

  1. STATE (Total 36 states present)
  2. ACCOUNT LENGTH
  3. AREA CODE
  4. PHONE NUMBER
  5. INTERNATIONAL PLAN (Whether customer has international plan activated or not)
  6. VOICE MAIL PLAN (Whether customer has voice mail plan activated or not)
  7. NUMBER VMAIL MESSAGES
  8. TOTAL DAY MINUTES
  9. TOTAL DAY CALLS
  10. TOTAL DAY CHARGE
  11. TOTAL EVE MINUTES
  12. TOTAL EVE CALLS
  13. TOTAL EVE CHARGE
  14. TOTAL NIGHT MINUTES
  15. TOTAL NIGHT CALLS
  16. TOTAL NIGHT CHARGE
  17. TOTAL INTL MINUTES
  18. TOTAL INTL CALLS
  19. TOTAL INTL CHARGE
  20. NUMBER CUSTOMER SERVICE CALLS
  21. CHURN (whether the customer churn or not)

Programming Language : Python 3 and R Language

Note:

Please refer the project report

churn_reduction's People

Contributors

skynoid2612 avatar

Forkers

deepak-rai-1027

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