Briefs

Global telecommunication company uses KXEN to improve success of its direct marketing efforts

SAN FRANCISCO, JUNE 28, 2005 � KXEN, a global provider of predictive and descriptive analytics software, today announced the availability of KXEN Analytic Framework 3.2. With the new version, KXEN has introduced data manipulation capabilities that provide advanced users additional control over the setup of raw data for analysis. End users can now complete the entire predictive analytics process, from generating the analytic data set to model deployment, within the KXEN Analytic Framework.

The release of version 3.2 supports KXEN�s mission to bring predictive analytics to a wide audience of corporate decision makers. By automating the data preparation and modeling process, KXEN provides next generation analytics to business managers, as well as analytic professionals. An infinite amount of decisions, from HR staffing to identifying the most profitable customers to minimizing credit risk and bank fraud, can now be based on hard data, instead of gut instinct.

A large, global telecommunications company provides a recent example of the power and simplicity of KXEN, having dramatically improved its direct marketing response rates while reducing its number of customer touches. The predictive analytics capabilities afforded by KXEN have allowed the creation of models that are able to pinpoint customers with the highest probability of responding to marketing efforts, such as product offers. Marketing programs now operate more efficiently, only utilizing resources that are most likely to result in profitable programs.

The unique mathematical underpinnings of KXEN allow for not only the improvement of predictive capabilities, but to also easily integrate analytics into existing technology architecture without incorporating extensive hardware costs. As opposed to legacy data mining tools, KXEN automates the data preparation phase, which includes tasks such as missing data replacement, outlier detection and variable binning. It also shields the user from having to choose between different algorithms. As a result, predictive projects can be created and implemented much quicker than with traditional methods, while also greatly improving the accuracy of results.

The predictive analytics market is one of the few bright spots in the enterprise software market. Technology industry analyst IDC predicts that the market will grow to more than $3 billion by 2008, citing companies� growing need to extend analytics capabilities to non-technical staff, such as line of business professionals.

For more information, visit www.kxen.com