How to forecast and prevent churn with Frisbii Revenue Insights

Silke Hoersch and Erik Mathiesen-Dreyfus discuss the importance of churn management and analytics and guide you through Frisbii’s Revenue Insights lab that helps you identify customers at churn risk and also provides you with information why they might cancel their subscription. Learn why churn reduction and prevention have a significant impact on your revenue and how to turn data insights into actions. 00:00 Why churn is misunderstood 01:11 Reactive vs predictive retention 04:23 Payback period provides a churn risk 07:04 Churn starts before cancellation 08:21 Making the customer journey predictable 10:34 Why retention programs fail 11:24 Handing over to data analytics 13:14 How does predictive modeling work 15:55 How do data models learn from history 17:31 Data and model ingredients 18:45 Demographic vs behavioral signals 21:52 How to turn predictions into actions 25:31 How Frisbii builds models 26:00 Full revenue suite 27:02 How Frisbii helps you with a data base 27:27 Hands-off integrations 28:45 Customer case: media streaming 31:12 Customer case: B2B SaaS 33:14 Customer cases summary 36:22 Q&A data requirements 37:49 Connectors and setup 39:31 Results and benchmarks 42:25 Pricing fit and minimum scale 45:45 Wrap-up and contacts #churn #predictiveanalytics #retention