The rarified world of predictive analytics is becoming more mainstream as the types of companies using it and the variety of tools available grows.
Predictive analytics encompasses a variety of disciplines such as statistics, mathematical modeling, machine learning, and data mining to help companies answer the age-old question "what's going to happen?"
The growth of predictive analytics is being driven by big data and new sources of consumer information such as web activity, e-mail, social and mobile media data. Rather than just looking at past performance, predictive models seek out esoteric data patterns and perform calculations during live transactions.
One of the hot new trends is persuasion modeling, which is used to predict the factors that influence consumer behavior. Those influencers are then used to craft marketing campaigns, web pages, and social media posts to drive consumer decision-making toward a particular outcome, says Eric Siegel, author of "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die."
Predictive analytics is also being used in healthcare to improve patient outcomes. One of the most intriguing projects underway is the Durkheim Project, which aims to identify the risk factors in military suicides. The suicide rate among U.S. veterans is twice that of the general population with some 22 veterans committing suicide every day.
The Durkheim Project is being conducted by the U.S Department of Veterans Affairs and the Dartmouth University Geisel School of Medicine. Researchers analyze veterans' social media activity to identify suicide risk factors. The project is opt-in only and adheres to federal health privacy rules.
The project uses predictive analytics from Patterns and Predictions of Portsmouth, NH, and text mining technologies from Attivio, which is based in Newton, Mass. Funding for the technology was provided by DARPA. The project consists of a database of 100,000 veterans and millions of social media posts, says Rik Tamm-Daniels, VP of Technology with Attivio.
The Attivio Active Intelligence Engine can glean insights from any source of human-created information, says Tamm-Daniels, ranging from documents, online conversations and web click logs, to customer service reports and social media.
Currently, project researchers are only allowed to observe and document veterans' behavior but it's hoped that in the next phase of the project, some form of proactive intervention will be allowed.
Improved outcomes, more relevant insights and more rapid innovation are driving the adoption of analytics technologies.
The market for analytics software and services is predicted to reach $50 billion by 2016, according to IDC. The top providers of analytics software are IBM, SAS, SAP, Oracle, and Tibco. But there are a growing number of specialized applications and cloud services coming to market.
Toovio Software, for instance uses predictive modeling to enable companies to make real-time offers to customers. The Minneapolis-based company developed a machine-learning algorithm to determine which offers are working and which are not to improve conversion rates on digital promotions.
Actian Corp. of Redwood City, Calif., recently announced its DataCloud platform, which gives customers tools to integrate their various data sources, perform analytics on that data and then automate the desired business activity.
Analytics are evolving from a means to understand past performance to a window into real-time business performance. And while it's not possible to model every factor driving consumers' behavior, the tools are becoming more sophisticated and better able to influence business outcomes.