Machine Learning for Predicting and Enhancing B2B Sales Success

A machine learning-based strategy to transform B2B sales tactics is presented in this study. To find important success indicators, the model efficiently evaluates sales data, including customer interaction metrics and market trends, using Decision Trees and Random Forest classifiers. B2B companies can improve lead quality and optimize resource allocation by using this predictive model to rank sales opportunities corresponding to their probable chance of success. Through the distribution of data-driven insights to sales teams, this novel strategy promotes more effective sales cycles, increased revenue potential, and general corporate expansion.