Mitch Eisen, CIO of Real Magnet, will outline the current state of predictive analytics for marketing and provide some real world examples of how it can help at the upcoming Mid-Atlantic Marketing Summit.

Predictive analytics is an area of statistics that deals with extracting information from data and using it to predict trends and behavior patterns. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

The core of predictive analytics relies on capturing relationships between explanatory variables and the predicted variables from past occurrences, and exploiting them to predict the unknown outcome. It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions.

Gartner offers a predictive analytics definition describing the concept as any approach to data mining that contains the following key elements:

• Emphasizing prediction, rather than description, classification, or clustering
• Rapid analysis, with measurements in hours or days, rather than the traditional approach to data mining
• Emphasizing business relevance of the resulting insights
• Ease of use, making data and tools easily accessible by business users

Predictive analytics emerged from a desire to turn raw data into informative insights that can be used not merely to understand past patterns and trends, but provide a model for accurately predicting future outcomes.