Beyond Experiments: A Modern Guide to Operationalizing Customer Churn Prediction

Does your business have customers and want to keep them?  Bet you said yes, which is why predicting customer churn in order to prevent it is one of the most important AI/ML use-cases.  It’s also one of the most broadly applicable given most businesses have enough customer data for machine learning.

While churn prediction is well understood in theory (the internet is plastered with toy examples), every business and therefore every churn model are different. It’s also not simply about having a good ML model: churn predictions need to be deployed to applications that impact customer interaction and be monitored and maintained for accuracy as customer behavior changes.

The good news is that there are new approaches that make it easy.  In this webinar you’ll learn:

• How to handle the essential complexities of predicting customer churn for your unique business

• How tools like Continual and Census make it easy to generate and deploy predictions into customer engagement systems

• Lessons from the field: what applied ML practitioners wish they knew when starting their first churn prediction projects

Plus you’ll see a live demo of operationalizing customer churn on the modern data stack.

Register and join us - we look forward to seeing you on June 9th!