XAI for Churn Prediction in B2B Models: A Use Case in an Enterprise Software Company

The literature related to Artificial Intelligence (AI) models and customer churn prediction is extensive rich in Business Customer (B2C) environments; however, research (B2B) environments not sufficiently addressed. the business environment more so a B2B context critical, as impact on turnover generally greater than B2C environments. On other hand, data used of this paper point importance relationship between brand through Contact Center. Therefore, recency, frequency, duration (RFID) model obtain customer’s assessment from view their interactions with Center novelty an additional source information traditional based purchase transactions, monetary (RFM). objective work consists design methodological process that contributes analyzing explainability AI algorithm predictions, Explainable (XAI), for which we analyze binary target variable abandonment environment, considering relationships partner (customer) has Center, focusing software distribution company. can be generalized any classification or regression algorithms are required.