Predict customer churn daily using ML or LLM models and notify via Slack/email

About

This n8n workflow runs daily to analyze active customer behavior, engineers relevant features from usage and transaction data, applies a machine learning or AI-based model to predict churn probability, classifies risk levels, triggers retention actions for at-risk customers, stores predictions for tracking, and notifies relevant teams. Key Insights Prediction accuracy heavily depends on feature quality — ensure login frequency, spend trends, support interactions, and engagement metrics are cons