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Customer-Churn-prediction

After EDA and modeling evaluation, Logistic Regression model is considered as a most efficient model to predict customer probability to churn. For analysis purpose, I visualize profile of total customer and churn customer to have general vision. Then, based on feature importance and model prediction, only features that affect on customer churn decision are visualized on Tableau public dashboard.

🛠 Toolkit in this analysis: sklearn pandas matplotlib PowerBI Tableau

📊 Summarize current customer versus churner by Power BI

👤 Customer Profile (predict whether with this customer profile, will they churn or not) by Tableau Public

👉🏼Click here to interact with below dashboard


You can visit my other Customer Analysis here 💁🏻‍

📌Customer Clustering using K-Prototypes

📌Customer Clustering using K-Means

📌Customer Segmentation analysis (without ML)

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