SPSS Receives Frost & Sullivan Product Innovation Award

"The scope of predictive analytics is broadening as enterprises seek to leverage these capabilities across all CRM initiatives including customer acquisition, growth, retention, and servicing, across departments and customer touch-points," says Frost & Sullivan Research Analyst Ashwin Iyer.

For example, in the financial services industry where risk management and fraud detection are increasingly considered as CRM functions, predictive CRM analytics becomes vital. In the case of the telecommunications industry, predictive CRM analytics is central to customer churn management, a critical industry pain-point. Cross-sell/upsell, especially at the time of inbound customer communication, is another leading predictive CRM analytics application.

SPSS, traditionally best known for its statistical and data mining tools, has built up on this strength to emerge as a leading provider of predictive analytics applications. The company offers both pre-packaged applications and tools that can be used to build custom applications for CRM analytics.

The pre-packaged applications comprise PredictiveMarketing for outbound campaign optimization, PredictiveCallCenter for cross-sell/upsell at the time of inbound calls, and Predictive Text Analytics for text mining. The recently launched Predictive Text Analytics application has been one of the fastest growing areas for SPSS.

For enterprises looking to build customized applications for predictive CRM analytics, SPSS offers Clementine, a business process driven data mining workbench. SPSS also offers a Web analytics application NetGenesis, for predictive Web analytics.

Most data mining applications analyze information residing in databases that support CRM applications, and are not designed to extract customer intelligence from unstructured data sources such as call center agent notes, customer e-mails, and other customer communications. Organizations that recognize the value in mining such unstructured data and integrate intelligence derived from all such sources stand to gain considerable competitive advantage.

"What is more important than analytical techniques and algorithms is the issue of application flexibility and ease of integration, and it is particularly true of predictive CRM analytics due to the level of sophistication involved," notes Iyer.

A striking characteristic of SPSS' products is non-intrusiveness into existing systems and processes. SPSS software integrates easily with operational CRM systems of other leading vendors. Ease of technology and process integration is an aspect where SPSS scores over SAS, and this will continue to be a key competitive advantage for SPSS.

SPSS presents a strong business case for enterprises seeking to leverage existing CRM investments by embedding predictive analytics. Several of the world's largest financial services, telecommunications, and insurance companies have derived convincing return on investment (ROI) from SPSS' predictive CRM analytics solutions. Further, Frost & Sullivan believes that SPSS stands to increase its market share in the CRM analytics market in 2005.