Predictive Analytics

Often used in analytical customer relationship management (CRM), predictive analytics makes use of statistics and data mining of relevant data in order to predict future events. These predictions are calculations of the odds in which a particular event will occur in the future (they are not absolute).

Business will generally use the results of predictive analysis to manage the risk or opportunity when dealing with customers or transactions. The analyses tell the businessee how the customer might react to certain circumstances, helping to lead the business down a path that is most likely to provide the customer with the greatest satisfaction.

Customer decisions are the driving factor in predictive analytics. One example is a comsumer’s credit score, which is used to predict how likely he is to be able to pay off the given loan in a period of time. The credit score model uses a number of historical factors related to the consumer, and encompasses all of the analytical data into a simple, easy to analyze credit score. Other areas where predictive analytics are used are healthcare, insurance, travel, telecom, retail, and pharmaceuticals.