Predicting Customer Churn

tensorflow.rstudio.com

We've been thinking a lot about churn prediction modeling recently—it's a topic that keeps coming up over and over again with our clients. We've played around in this problem space before but are planning to go much deeper in the near future.

There were three articles that I came across as a part of this research that I wanted to share. The first, linked from the title, is a deep-learning approach to churn prediction using Keras. The article is detailed and excellent. The second uses a logistic regression + random forest ensemble that it found to be more effective than a decision tree model. The third recommends a random forest approach as well.

Which approach is best and under what conditions? As of today I have no idea. I was a little surprised that deep learning would be employed as a solution, but I'm trying to keep an open mind. I'll have more to share on this topic soon.

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