Building a User Churn Prediction Model with Scikit-Learn and Vonage

Vonage's Conversation API allows developers to build their own Contact Center solution with voice, text, and integrations to other solutions. The most powerful solutions use AI to route calls, translate text, recommend products, etc. Developers can integrate AI into their application without needing a Ph.D. in AI research. They can also build a machine learning system from scratch using various machine learning libraries. In this post, we'll explore how to predict the likelihood of customer churn using the Vonage Conversation API and the Telecom Churn Dataset from IBM. The project involves building a simple Python server to serve the model, generating user data for prediction, and integrating it into a web app to show churn predictions to a customer service agent. The model achieves 89% accuracy in predicting churn probability.

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