It is understood that predictive analytics and data mining are particularly the hot topics in today’s times as they have been used in marketing analytics and research for over 30 years. Marketing mix models have used econometric algorithms were developed during the ‘80s and the ‘90s and while other statistical approaches, such as cluster analysis for segmentation analysis, were already being used at the time. Digital analytics has gotten more predictive, giving more importance on what might happen in the future, as opposed to just describing on past happenings. Businesses have made significant investments in getting digital data into environments where it is possible to have leverage predictive analytics. Data scientists are also being exposd to more digital data as businesses are becoming digital. Predictive analytics is evolving into prescriptive analytics, a mash up between the worlds of predictive analytics, and simulation and optimization, which have traditionally been used to understand the best course of action given a series of constraints. Though these techniques, such as linear programming and Monte Carlo simulation, have their applications in marketing analytics, they’re deployed far more extensively in areas, including supply chain and logistics. So whereas descriptive analytics address what happened and predictive analytics address what might happen, prescriptive analytics answers the question, “What should I do?” In the marketing world, descriptive analytics would convey that a user has been converted. Predictive analytics will tell an analyst that a user would be likely be turned into a conversion. Prescriptive analytics would tell an analyst that a user would likely become a conversion and what appropriate intervention strategy would be, basing on objectives and constraints at the current. Only a few companies are at the stage where they’re deploying prescriptive analytics across the enterprise and for the foreseeable future, and it is presumed that it what will define those who are able to be analytical competitors.