Machine Learning Algorithm to predict product discontinuation for cdmon

inLab FIB is collaborating with cdmon on the development of a solution based on machine learning techniques to predict the non-renewal of contracted products. The project aims to analyse historical data and available internal information to identify behavioural patterns that allow anticipating, with a certain degree of confidence, which products present a higher risk of non-renewal.

The solution develops a predictive model capable of processing large volumes of data and generating estimates of the probability of non-renewal for the various products. These predictions provide decision-making support and enable the planning of preventive and corrective actions well in advance.

The project provides cdmon with a data-driven decision support tool, which facilitates the early identification of potential non-renewals and contributes to optimising the management of its products and the planning of the most appropriate actions.