Jean Paul Isson (Global Vice President of Business Intelligence and Predictive Analytics, Monster Worldwide, Inc.) and Jesse Harriott (Chief Analytics Officer, Constant Contact) know a thing or two about business analytics. With almost 40 years of experience between them, they've handled it all—from web mining solutions to business intelligence, predictive modeling to data governance, customer scoring to market segmentation.

Isson and Harriott believe now is a great time for businesses to build predictive models, with big data offering opportunities to integrate multiple types of data intelligences from a variety of sources. Here are three things they think you need to understand about predictive analytics before you start this process:

1. Business applications for predictive analytics include predicting sales and marketing customer behaviors, predicting fraudulent insurance claims, predicting military supply chain problems, predicting customer attrition, and predicting the spread of the infections, such as the H1N1 flu.
2. Predictive analytics is made up of predictive modeling and forecasting. Forecasting will help you predict how many customers you will lose to your competitors, while predictive modeling will answer why you are losing them and under what conditions.
3. Some major benefits of predictive analytics include: effective and profitable campaigns with messages and offers that are relevant to the target recipients. This enables companies to increase their response rate by identifying customers that are most likely to respond to an offer or most likely to leave for a competitor, as well as to increase  their acquisition rate, increase their retention rate, reduce marketing campaigns costs, and even, perhaps, save some lives.

Learn more from Isson and Harriott in their new book, Win with Advanced Business Analytics: Creating Business Value from Your Data, available now.