Bossé, Aliénor Alexia Désirée2024-09-242024-09-242023-01-242023-01-24http://hdl.handle.net/10362/172303This paper proposes a machine learning model predicting customer churn at the studied B2B SaaS company. The model is based on a real-life dataset of the studied company’s active customers. The dataset considers various factors specific to B2B customers. The model is trained on this dataset and its performance is evaluated. The evaluation shows that data helps understanding some factors impacting the studied company’s customers’ behavior to churn. However, the quality of the available live data is questioned and will have to be tested in further iterations. Additionally, a new practice for customer churn management is derived from this analysis.engCustomer churnChurn managementChurn predictionMachine learningmaster thesis203316436