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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 behaviour

January 14, 2008

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. Clementine 12.0, the industry’s most complete data and text analytical workbench, now delivers increased analyst productivity, deeper information insight, and advanced visualisation.

“Clementine 12.0 is the predictive analytics technology that enables organisations 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 modelling and advanced visualisation

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 organisation 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 visualisation capabilities in Clementine 12.0, including rich and improved graph interactivity and custom tabular reports driven by a powerful visual design interface, organisations 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 organisation,” 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 organisations 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 organisation 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 organisations 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 organisation’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.

Executive quote

“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 organisation,” said Matt Wroblewski, director of marketing research at Lincoln Financial Distributors, an operator of multiple insurance and investment management services.

Customer quote

Federico Cesconi, head of customer insight and retention at Cablecom, a Swiss cable television company, said: “Our organisation 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.”

About the company

About SPSS
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 organisations forward visibility for decisions made every day. By incorporating predictive analytics into their daily operations, organisations 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 more information, please visit www.spss.com.

SPSS UK’s customers include BT, Virgin Mobile, Debenhams, EDF Energy, Powergen, Saga Holiday and Alliance & Leicester.

Contact details

For press enquiries please contact:
Anna Moseley at LEWIS
Tel: +44 (0) 20 7802 2626 Fax: +44 (0) 20 7802 2627
Email: annam@lewispr.com
Website: www.lewispr.com

For enquiries about SPSS please contact:
Emma Bennett
SPSS
Tel: +44 (0) 1483 719 200 Fax: +44 (0) 1483 719 290
Email: ebennett@spss.com
Website: www.spss.com

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