himanshu-03/Customer-Churn-Prediction
The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022. We need to predict whether the customer will churn, stay or join the company based on the parameters of the dataset.
This project helps customer success and marketing teams predict whether a telecommunications customer is likely to leave, stay, or join the company. By analyzing customer demographics, service subscriptions, and tenure, it generates predictions that allow businesses to proactively engage high-risk customers. The output helps prioritize retention efforts and understand service quality.
No commits in the last 6 months.
Use this if you need to identify customers at risk of churning so your team can intervene before they leave.
Not ideal if you are looking for a real-time, streaming prediction system for highly dynamic customer behavior.
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Jupyter Notebook
License
MIT
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Last pushed
Jan 08, 2024
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