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SPSS Inc. Launches Predictive Web Analytics™ Solution to Help Organizations Maximize Online Customer Value
Source: www.spss.com
Copyright SPSS, Inc. 2004

Integration of NetGenesis® Web analytics and Clementine® predictive modeling delivers advanced insights into organizations’ online business

CHICAGO, 05/19/03 — SPSS Inc. (Nasdaq: SPSS), the leading provider of predictive analytics, today announced the immediate availability of Predictive Web Analytics™, a solution that enables organizations to transform their Web data into deeper customer intelligence. Unlike traditional Web metrics, Predictive Web Analytics provides meaningful historical and predictive insights, driving actions that maximize customer value and increase returns from Web investments.

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

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. By providing historical and predictive Web metrics, Predictive Web Analytics identifies opportunities that increase sales and improve customer satisfaction, enabling companies to quantify the return on investment (ROI) of complex Web initiatives.

“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."

FT.com, the online partner of The Financial Times and the world’s leading business Web site, is among the first to leverage Predictive Web Analytics to better understand its visitors. The online publication is using the solution to develop targeted marketing messages that will encourage increased site usage, retain existing customers and help anticipate customer behavior in terms of subscription renewal.

“By leveraging Predictive Web Analytics to understand our visitor usage patterns, we can develop targeted marketing messages resulting in increased site usage among our customers,” said Chris Catchpole, head of database services at The Financial Times. “This sophisticated level of analysis will also provide us with a deeper understanding of visitor objectives -- insights that we would not be able to gain with a conventional, stats-based measurement approach.”

NetGenesis 6.0 provides an enterprise platform for understanding and measuring the progress of Web initiatives. It helps establish a new standard for scalability, flexibility, reliability, and accuracy. A completely re-architected importer enhances NetGenesis 6.0’s data processing efficiency and facilitates advanced Web Mining. By supplying a comprehensive view of historical online customer activity, NetGenesis 6.0 provides the platform necessary to make accurate predictions.

Clementine predictive modeling adds a proven data mining engine to NetGenesis Web analytics. It supplies the ability to detect patterns in large volumes of Web data and predict the best way to serve Web customers. Clementine also leverages the customer behavior foundation available in the NetGenesis eDataMart™, presenting advanced predictive analysis within a customizable reporting environment. The reporting interface provides decision makers throughout an organization with access to historical and predictive customer intelligence.

“For years, organizations have used SPSS predictive analytics to capitalize on high volume customer data from a range of offline channels,” said Colin Shearer, vice president of customer analytics at SPSS Inc. “We developed Predictive Web Analytics so that organizations could have that same level of insight into their online business. Predictive Web Analytics allows organizations to maximize the value of their Web channel by creating a 360-degree customer view that drives profitable multi-channel relationships."