Software

SPSS� New Data Mining Product Will Significantly Boost CRM, Marketing & Fraud Detection

Enables Greater Productivity & Cost Efficiency

CHICAGO, Ill. (USA), January 16, 2006 � SPSS Inc. (NASDAQ: SPSS), a leading worldwide provider of predictive analytics software, today unveiled its new data mining workbench, Clementine�10, that will provide a substantial boost for customer relations management (CRM), marketing, fraud detection and revenue assurance applications.

Clementine 10 offers extensive new features to enable much greater productivity and cost efficiency for the full range of data mining applications and the entire data mining process, from business insight to integration with business processes and operational systems.

Organizations harnessing SPSS� Clementine 10 will find a wealth of specific new benefits. Fraud detection and revenue assurance applications will gain from �anomaly detection,� which will simplify the analysis process, provide deeper insight, and enable the use of these results in operational deployment.

Analytical CRM and marketing applications, such as customer acquisition, cross-/up-selling and customer retention, will be enhanced through Clementine 10�s �feature selection.� This will produce simpler, more intuitive models more easily, providing improved customer insight and simplifying operational deployment. Predictive power will be maximized by Clementine�s 360-degree view of the customer, incorporating information from databases, text documents, surveys and Web site behavior.

Benefits of SPSS� Clementine 10 include:

• With SPSS� Clementine 10, data mining applications can be managed and processes automated at an enterprise level, providing the most up-to-date results in a secure, auditable environment, through the addition of SPSS Predictive Enterprise Services.

• The new anomaly detection algorithm simplifies both analysis and scoring, helping data miners uncover unusual events or behavior rapidly, at any time. This will be of particular importance to organizations involved in fraud detection, revenue assurance, tax compliance, medical research and public safety.

• New feature selection capabilities enable data miners to quickly identify the most- and least-important data attributes for a given analysis, simplifying predictive modeling in CRM and marketing applications. Analysts can also rank and filter attributes in several different ways for improved focus in model building.

• Users can export data to Microsoft� Excel� directly from the Clementine interface and, when importing data from Excel, can specify worksheets and data ranges.