SPSS Inc. a provider of predictive analytics, will enable organizations to transform their Web data into deeper customer intelligence with the launch of Predictive Web Analytics. Unlike other Web analytics solutions that only deliver simple metrics like number of visits, Predictive Web Analytics provides deep historical and predictive insights and drives actions that help maximize customer value and returns from Web investments.

SPSS Inc.'s Predictive Web Analytics solution integrates the company's new NetGenesis 6.0 Web analytics platform with the predictive modeling capabilities of its Clementine 7.0 data mining workbench. The combination of these powerful technologies enables Predictive Web Analytics to move beyond traditional, simplistic metrics such as page counts, unique visitors and referral information, to deliver insights that can be used to directly affect customer relationships.

Organizations worldwide have made significant investments in their Web assets, but there is a disparity between the critical analysis needed to make the most effective decisions and the rudimentary Web metrics that are most commonly used. Predictive Web Analytics bridges this Web metrics gap by providing meaningful historical and predictive Web metrics, enabling companies to quantify the return on investment (ROI) of complex Web initiatives by identifying opportunities that lead to increased sales and satisfied customers.

"An organization's Web site is a viable business channel and rich source of customer data that needs to be turned into usable customer intelligence," said Kurt Schlegel, program director at META Group. "Unfortunately, many large organizations have short changed initial attempts to analyze their Web sites by providing only low end functionality. We expect enterprise analytic teams will devote more resources to bolster Web analytic efforts, providing more insightful customer profiling and predictive analysis."

NetGenesis 6.0 provides a new, more scalable platform for understanding and measuring the progress of Web initiatives, establishing new standards for scalability, flexibility, reliability and accuracy. A completely rearchitected importer enhances NetGenesis 6.0's log file processing efficiency and enables advanced Web Mining. By supplying a comprehensive view of online customer activity necessary to make accurate predictions, NetGenesis 6.0 provides a uniquely powerful platform of historical Web data, conducive for pervasive predictive analysis.

Clementine predictive modeling adds a proven data mining engine to NetGenesis Web analytics, supplies the ability to detect patterns in large volumes of Web data and predicts the best way to serve Web customers. Clementine takes advantage of the strong foundation of customer behavior data available in the NetGenesis eDataMart to perform advanced predictive analysis and provide the results of that analysis back within the customizable NetGenesis reporting environment. The browser-based reporting interface provides decision-makers throughout an organization with access to historical and predictive customer intelligence.

Using the combination of Clementine and NetGenesis 6.0, Predictive Web Analytics provides four essential analytical capabilities – segmentation of visitors based on their behavior, detection of content and product affinities, automatic identification of the most significant paths taken through a Web site and prediction of visitors' propensity – for example, to purchase, to view particular content or to churn.

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