Customer Churn Model – Part 1

This is part one of the multi part series where we will build a Modelshop model from scratch.  We are making this series because we often get questions about what goes into building a Modelshop model…. What types of problems can be solved, how you get started and what the models can ultimately do for you.  The answer in short is Modelshop can be used to solve a wide array of business problems and is perfect for automating processes ranging from simple to complex. 

In this example we will be playing the part of an analyst at a retail brokerage firm.  The firm has seen significant customer attrition and went through the process of determining why.  With that research done, we have been tasked with doing the ongoing analysis to analyze the current customer set on an ongoing basis and identify customers that may be at risk of churning.  This way we can take proactive measures to intervene and stop before they close their accounts.  This demo will be broken up into several parts.  In this segment we will import our data and do exploratory analysis and test some hypothesis.  In subsequent videos we will implement a machine learning model do make automated churn predictions as well as create an application to share this information other stake holders. 

Can’t wait to see more? Check out part 2, here.

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Tom Tobin is the CEO of Modelshop. Modelshop provides a no-code platform and suite of lending models designed to accelerate automation of credit risk, origination and servicing decisions. Learn More.

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