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Testing Batch Scoring in Siebel Analytics

If you are exposing batch scores in a Siebel operational application, use Siebel Answers to test the correctness of the logical SQL statement before deployment. Siebel Answers tests the connection between the application and Siebel Analytics. See the Siebel Analytics User Guide for instructions on directly executing logical SQL statements in Siebel Analytics Answers.

After successful testing, deploy your configuration by activating scheduled batch runs and moving the configuration from your test and preproduction system to your production system. Once deployed, diligently monitor model performance and plan for timely rescoring and retraining of models. Monitoring the deviation of predicted propensities that deviate from observed outcomes is an indication of model performance. You can also use Siebel iBots and Siebel Delivers to create even-triggered notifications of changes in model performance. For example, the wireless service provider captures actual churn behavior and compares it against predicted behavior. If an increasing number of customers with a low predicted churn propensity start churning, the provider needs to either rescore his customers or reevaluate the predictive churn model.