Developers PeopleSoft Inc., Siebel Systems Inc. and SAS Institute Inc. are each readying predictive analytics software that looks to broaden the audience for such products, from the typical cadre of statistical analysts to mainstream business users.
Specifically, the products are designed to help users of sales, customer service and marketing applications make better decisions on customer dealings through analysis of more forward-looking customer data. Such professionals have typically relied on historically focused data.
PeopleSoft, of Pleasanton, Calif., this week will announce its Predictive Analytics Solution for CRM (customer relationship management), which includes predefined templates for customer churn and marketing campaign response.
Separately, Siebel is developing its own predictive analytics technology that will be introduced in Version 7.5.3 of the San Mateo, Calif., companys namesake CRM applications, next month. In Version 7.7 of the suite, planned for a winter release, the company will add vertical-specific predictive analytics templates for financial services, retail and communications, officials said.
Siebel will continue its predictive analytics partnership with SPSS Inc. and rework its development relationship with SAS, the officials said.
For its part, SAS, whose roots are in data mining, this week will roll out a product called Interaction Management, which is the Cary, N.C., companys effort to make its analytical software more accessible to business users. The new application packages best practices culled from SAS analytics implementations and can trigger marketing activities based on customer behavior, officials said.
Despite the new products, enterprises may not be ready to make the jump into predictive analytics.
“Our road map is pretty well-defined and full,” said Jim Hooton, director of sales systems in the global IS department of Storage Technology Corp., of Louisville, Colo. Hooton said that while StorageTek is interested in the Siebel analytics module, it has no plans to add the new predictive capabilities for at least 12 months.