SPSS Boosts the Power of Predictive Analytics with New Data Mining Workbench

New Predictive Text Mining Combines Structured and Unstructured Information to Provide a Complete View of Customer Behavior

SPSS Inc. (Nasdaq: SPSS), the leader in predictive analytics software, today unveiled Clementine® 12.0 and Text Mining for Clementine 12.0, the latest release of its market-leading data and text mining technology. Clementine12.0, the industry’s most complete data and text analytical workbench, now delivers increased analyst productivity, deeper information insight, and advanced visualization.

“Clementine 12.0 is the predictive analytics technology that enables organizations to become a Predictive Enterprise,” said Bob Dutcher, vice president, product marketing at SPSS. “With the new version, our customers can extract even deeper insight from data and text, delivering greater return on all of their data assets. SPSS continues to lead the predictive analytics market by giving our customers the tools and solutions to unlock the value within their enterprise data, improve business processes and make more informed decisions.”

Intelligent Modeling and Advanced Visualization

Clementine 12.0 offers faster and greater return on analytical investment through automated modeling, which quickly identifies the best analytic models and combines multiple predictions for the most accurate results. This gives an organization an unprecedented level of insight and prediction from their data to better solve a wide array of challenging business problems – including customer churn, campaign effectiveness, customer value, marketing cost, fraud and risk analysis.

With new advanced visualization capabilities in Clementine 12.0, including rich and improved graph interactivity and custom tabular reports driven by a powerful visual design interface, organizations can now widely distribute and communicate results to speed smarter, more proactive decisions.

“Clementine 12.0 gives our business users and analysts the most comprehensive solution to gain deeper insights into our customer behavior to increase sales, profitability, and productivity for our organization,” said Matt Wroblewski, director of marketing research at Lincoln Financial Distributors, an operator of multiple insurance and investment management services. “The new features have helped us better assess the value of different groups of customers and more effectively target at-risk profitable customers for retention efforts. The model comparison feature has made our users more productive by allowing them to execute and compare multiple models simultaneously.”

Predictive Text Mining

Text Mining for Clementine 12.0 gives organizations a unique advantage to extract key concepts, sentiments and relationships in different languages from textual or ‘unstructured’ data, such as email, blogs, RSS feeds and surveys. Users can easily extract additional insight and predictive power from these channels to draw more reliable conclusions and take more effective action – transforming Clementine 12.0 into a fully integrated data and text mining solution.

Federico Cesconi, head of customer insight and retention at Cablecom, a Swiss cable television company, said, “Our organization has been able to better understand and quantify reasons for customer churn through the use of SPSS predictive text mining software. We’ve uncovered concepts and relationships in text that would be too costly—or even impossible—to detect by any other methods.”

Deep Integration

Clementine 12.0 is also integrated with SPSS Predictive Enterprise Services™, an enterprise-level predictive platform that enables the effective and widespread use of predictive analytics, allowing organizations to easily manage analytical results, automate analytical processes and deliver predictions and insight into business processes wherever needed. Additionally, Clementine 12.0 also brings an enhanced integration with Dimensions, SPSS’ leading survey software, making it easier than ever for customers to integrate attitudinal data into customer analysis.

SPSS works with its partners to provide complementary predictive analytics technology and services to enhance and extend the overall investment of an organization’s IT infrastructure. The new extension framework in Clementine 12.0 makes it even more open for integration with other software applications, such as IBM DB2 Warehouse 9.5 for in-database mining and BusinessObjects™ XI platform to extend the value of a business intelligence solution.

Availability

Clementine 12.0 and Text Mining for Clementine 12.0 shipped in Q4 2007, and are available from SPSS by calling 800.543.2185.

For more information on Clementine 12.0, please visithttp://www.spss.com/clementine/whats_new.htm. For more information on Text Mining for Clementine 12.0, please download Nucleus Research’s “Guidebook: SPSS Text Mining” Report at http://www.spss.com/pdfs/Guidebook%20--%20SPSS%20Text%20Mining.pdf.



About SPSS Inc.

SPSS Inc. (Nasdaq: SPSS) is a leading global provider of predictive analytics software and solutions. The company’s predictive analytics technology improves business processes by giving organizations forward visibility for decisions made every day. By incorporating predictive analytics into their daily operations, organizations become Predictive Enterprises — able to direct and automate decisions to meet business goals and achieve a measurable competitive advantage. More than 250,000 public sector, academic and commercial customers rely on SPSS technology to help increase revenue, reduce costs and detect and prevent fraud. Founded in 1968, SPSS is headquartered in Chicago, Illinois. For additional information, please visit www.spss.com.

SafeHarborStatement

In addition to historical information, this press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934, including without limitation, statements regarding the Company’s expectations, beliefs, intentions or future strategies that are signified by the words “expects,” “anticipates,” “intends,” “believes,” “estimates” or similar language. All forward-looking statements included in this document are based on information available to the Company on the date hereof. The Company cautions investors that its business and financial performance and the matters described in these forward-looking statements are subject to substantial risks and uncertainties. Because of these risks and uncertainties, some of which may not be currently ascertainable and many of which are beyond the Company’s control, actual results could differ materially from those expressed in or implied by the forward-looking statements. The potential risks and uncertainties that could cause results to differ materially include, but are not limited to: the Company’s ability to predict revenue, the Company’s ability to respond to rapid technological changes, a potential loss of relationships with third parties from whom the Company licenses certain software, fluctuations in currency exchange rates, the impact of new accounting pronouncements, increased competition and risks associated with product performance and market acceptance of new products. A detailed discussion of other risk factors that affect the Company’s business is contained in the Company’s Annual Reports on Form 10-K, particularly under the heading “Risk Factors.” The Company does not intend to update these forward-looking statements to reflect actual future events.