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A mi predictive model for customer churn at a b2b software company
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Orientador(es)
Resumo(s)
This 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.
Descrição
Palavras-chave
Customer churn Churn management Churn prediction Machine learning