video1.0<iframe src="https://www.loom.com/embed/b188e256fe4a4164a1a0f71f074e5fd6" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/b188e256fe4a4164a1a0f71f074e5fd6-8c580721241b5371.gif257.814In this video, I demonstrate how to read and analyze customer data to identify those at risk of churning, focusing on a sample of 5,000 customers where 310 are flagged as high risk. We explore various analytics, including engagement rates and lifetime value trends, and I show how to generate AI-powered insights and recommendations. I also run a joint accuracy test, revealing that nearly 800 customers are at high risk, and discuss the importance of understanding customer behavior through technical insights. My goal is to equip you with the tools to prioritize these at-risk users effectively. Please take a look at the insights and consider implementing the recommended actions.