SPSS enhances Clementine for CRM, fraud detection

SPSS has let loose the newest release of its data mining workbench, Clementine 10.

The revamped Clementine has been tweaked, not only to provide additional insight into CRM and other kinds of customer-centric data, but also to enhance fraud detection and revenue assurance applications.

Clementine incorporates new feature selection capabilities that enhance the productivity of CRM and marketing analysts, especially in scenarios such as customer acquisition, cross- and/or up-selling, and customer retention. Feature selection produces more intuitive models to improve customer insight and simplify operational deployment.

Similarly, Clementine 10 ships with a new anomaly detection feature to shore up its fraud detection and revenue assurance capabilities. Anomaly detection can simplify analysis and scoring, improve insight, and facilitate the use of these insights in operational deployments, SPSS officials say.

Elsewhere, analysts can now rank and filter attributes in a number of ways, which simplifies the model building process, officials say. Clementine 10 ships with improved Excel support, too: analysts can now export data directly to Excel from the Clementine interface; what's more, when analysts are importing data from Excel, they can specify worksheets and data ranges.

About the Author

Stephen Swoyer is a contributing editor. He can be reached at [email protected].