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SPSS Launches Enhanced Predictive Analytics Platform


WEBWIRE

Giving businesses more power to understand and predict individual customer behavior and optimize business process outcomes, SPSS Inc. (Nasdaq: SPSS) today unveiled new versions of its data mining, text mining, survey research and Predictive Enterprise Services™ products at its European Directions User Conference in Prague, Czech Republic.



The platform provides next-generation predictive analytics with improved integration, automation and data management -- enabling organizations to easily collect and use all available customer data, build predictive models and deliver customer behavior predictions across multiple channels. Among the benefits companies will derive are enhanced productivity across the enterprise, more accurate and consistent results and more confidence in decision making.

SPSS predictive analytics applications and solutions are used worldwide to improve critical business decisions focused on increasing customer acquisition, cross-selling, up-selling and detecting and preventing fraud and risk in industries such as finance, retail, telecommunications and the public sector.

“Organizations serving large numbers of customers across multiple channels, such as retail banks, brokers and insurance providers, are readily adopting predictive analytics to provide better customer relationship management and strengthen customer loyalty,” said Jack Noonan, SPSS president and chief executive officer. “In today’s world of multiple avenues and opportunities to reach and understand customers, predictive analytics clearly provides a core competitive advantage for every industry worldwide.”

Dorota Poniatowska-Mańczak, CIO of Bank Zachodni WBK S.A. in Poland , said, “Implementing a predictive analytics platform is essential to competing successfully in the banking industry. We selected SPSS to drive better decisions in multiple business processes, including CRM, credit risk analysis and fraud prevention and because it offers advanced user-friendly technology.”

“As a bank with a large and growing client base, our focus has been on a customer-oriented strategy, relying on interaction to understand client expectations and preferences,” added Tomasz Byczyński, CRM director of Bank Zachodni WBK S.A. “Using predictive analytics should considerably increase our ability to carry out highly tailored, effective marketing campaigns, while increasing bottom-line results.”

Key product enhancements strengthening the predictive enterprise platform include:

Enhanced Predictive Enterprise Services 3.0: o verall benefits to this release include new automation options for refreshing and evaluating models for better model accuracy; integrated reporting to help measure and monitor results; more automation options for manual, labor-intensive processes; enhanced asset management with more flexibility to customize metadata; and improved notification services for keeping business end users up-to-date on latest analytic results. For more information, please visit: http://www.spss.com/predictive_enterprise_services/new.htm.


Upgraded Data Mining Workbench-Clementine® 11.1: builds on the recent release of Clementine 11.0, which provided automatic evaluation of simultaneous models and significant performance increases with more parallel processing. Enhancements in this release include the addition of self-learning response models to increase model building speed and productivity; anonymization of data to help protect privacy of individual data records; and better integration with a broader enterprise platform to ease the deployment of production models. For more information, please see: http://www.spss.com/clementine/whats_new.htm.


Expanded Survey Research Platform-Dimensions™ 4.5: simplified survey design and enhanced data integration in combining feedback data with other customer relationship management (CRM) sources, increasing the scope and speed with which feedback can be collected and acted upon. For more information, please visit: http://www.spss.com/Dimensions/whats_new.htm.


Advanced Text Mining Product-Text Mining for Clementine® 5.0: faster modeling of unstructured data, including new sources such as RSS feeds (blogs and news feeds) and new graphics for instant, on-the-fly data analysis. Text Mining for Clementine 5.0 now also supports native multilingual text in seven languages: English, French, Spanish, German, Dutch, Italian and Portuguese. For more information, please see: http://www.spss.com/text_mining_for_clementine/whats_new.


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 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.



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