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Germany has a printed newspaper circulation of 15 million. We have developed a churn prediction model for Mittelbayerischer Verlag, a large regional newspaper client – first for print/offline products then for online products for 100.000 newspaper subscribers. From business question over data understanding and analysis, to model selection, training, hyperparameter optimization to deployment we have walked through the complete process with the client. Predicting with high quality is hard due to the few features on the actual usage of the print subscribers. Most features are static and they needed to transfer features from one subscriber to peer-groups. The developed solution is based on multiple Gradient Tree Boosting models that each work on different prediction timeframes. They have a lot of lessons-learned due to the large number of features engineered, working with a large group of business people on the client side, going from business question to final deployment in the cloud.