This document discusses how machine learning can help companies move beyond basic targeting and accelerate sales. It provides examples of how machine learning has helped companies improve product propensity modeling to identify prospects likely to need their products, and response propensity modeling to ensure marketing dollars are spent on prospects most likely to respond. The document also outlines considerations for applying machine learning, such as the need for quality input data and human intervention to determine the right algorithms and data sources.