SPSS' New Data Mining Product Will Significantly Boost CRM, Marketing & Fraud Detection; Enables Greater Productivity & Cost Efficiency

Business Wire, Jan 16, 2006

CHICAGO -- SPSS Inc. (NASDAQ:SPSS), a leading worldwide provider of predictive analytics software, today unveiled its new data mining workbench, Clementine(R) 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.

SPSS Customers and Industry Analysts Praise Clementine 10's Robust Capabilities

"Clementine 10 provides new functionality which exceeds expectations," said National Instrument's Market Analyst Dan Courtright. "The increased functionality between third-party software is a huge step in the right direction and will save National Instruments hours of work for each reporting period."

"We applaud SPSS' committed effort to take an already outstanding product to the next level," said Daniele Micci-Barreca, PhD, a principal at Elite Analytics. The Audit Division of the Texas Comptroller of Public Accounts uses SPSS and Elite Analytics, LLC, a data mining consulting service, to maximize taxpayer compliance and maintain revenue streams. "Clementine 10 represents a significant evolution toward SPSS' vision of true database-centric data mining, orchestrated through a platform which was built to support every step of the knowledge-discovery process," said Micci-Barreca.

"Clementine 10's new anomaly detection will allow revenue departments to improve tax compliance more quickly and in a more systematic way," he added.

"SPSS continues to enhance Clementine. With Clementine 10, the company is helping users boost productivity, as well as improve the ability of applications such as CRM to deliver a 360-degree view of their customers," said Current Analysis' Senior Analyst Robert Lerner. "A 360-degree view of customers is a critical, competitive necessity for both customer service and customer segregation. Clementine has been one of the strongest data mining solutions in the market, and this version is the strongest yet and should increase SPSS' position in the market."

More Specific Benefits of SPSS' Clementine 10:

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. Enhancements in Clementine 10 support increased productivity, performance, and integration.

Productivity

--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(R) Excel(R) directly from the Clementine interface and, when importing data from Excel, can specify worksheets and data ranges.

--Other enhancements include the ability to more efficiently restructure data and prepare time-series data for analysis. Users will also find improved string manipulation and pattern matching, and the capacity to work with ranges of fields.

Performance

--Clementine 10 provides in-database caching, database write-back with indexing, and optimized merging for joining tables outside of the database. Clementine's in-database mining provides outstanding performance on large-scale data.

--It also enables organizations with multiple CPUs or multi-core CPUs in their operating environment to use parallel processing during a number of data pre-processing and model building operations. This leverages their investment in high-performance hardware and increases their ability to process high volumes of data using Clementine.