Telecom Churn Case Study using ML algorithms
The predictive model that has been built will serve two purposes:
-
It will help us predict whether a high-value customer will churn or not, in near future (i.e. churn phase). By knowing this, the company can take action steps such as providing special plans, discounts on recharge etc.
-
It will help us identify important variables that are strong predictors of churn. These variables may also indicate why customers choose to switch to other networks.
Recommendation
- Other models can be used to perform the same based on your knowledge.
Privacy Statement
- No Client data or confidential data has been used. The data used for analysis is downloaded from open source repositories.
- Non of the organizational server and credentials has been used during this project.
- This is a non-monitorial project only for learning and assignment perspective.