SPSS Inc., a leading provider of predictive analytics, announced the immediate availability of Web Mining for Clementine, an add-on module to its Clementine data mining workbench and addition to its predictive Web analytics offerings. Unlike simple Web metrics, Web Mining for Clementine enables organizations to transform their Web data into deeper customer intelligence by providing meaningful historical and predictive insights.

"Web Mining for Clementine sets a new standard for Web analysis by bringing together the leading technologies for both data mining and Web analytics – along with the more than 35 years SPSS has in analytical experiences," says Colin Shearer, vice president of customer analytics at SPSS Inc. "We developed this product so that organizations can maximize the value of all their business channels, including the Web, and truly gain a cross- channel, 360 degree view of the customer."

Web Mining for Clementine simplifies the preparation of raw Web data – technical information that was not designed with analysis in mind – through a Web mining source node that is integrated within the Clementine visual workflow. The Web mining source node, which automatically transforms raw data into focused online business events, is driven by NetGenesis Web analytics technology.

The Web mining node efficiently processes only the data needed to create an accurate, business-focused view of online behavior. Accurate user identification, business event mapping, visit sessions and data cleansing help ensure that decision makers draw reliable conclusions about current conditions and future events.

Capitalizing on Clementine's scalability, interactive visualization and its ability to integrate with other data sources, Web Mining for Clementine enables online business decision makers to take more effective action by automatically discovering user segments; detecting pages significant to online business goals by making sense of the important chains of activity; understanding product and content affinities and predicting user propensity to convert, buy or churn.

Web Mining for Clementine includes an application template that implements best practice Web mining methods. This application template can be used both as a prepackaged Web mining application and as a reference source for analysts developing their own analysis. This template is provided in the form of Clementine streams, which means that analysts can easily examine the methods used and reuse them for new applications. The template includes several modules to address key online business problems, including search engine optimization, user and visit segmentation, Web site activity and user behavior analysis, home page activity, activity sequence analysis and propensity analysis.

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