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Real-Time Scoring with Siebel Data Mining

In real-time deployment scenarios, model input values are fed into a predictive model to produce a score in real time. The predictive model is executed on demand by a Siebel operational application. The choice between deploying a predictive model for real-time or batch scoring depends on your business requirements. Some factors to consider include the following:

• Level of criticality of having access to real-time versus batch scores
• Volatility of the data feeding into the model
• Volatility of model scores

NOTE:  Currently, the real-time deployment option is available only on configurations that run Siebel Analytics on a Windows platform. Future releases of Siebel Data Mining will support additional platforms.

Scenario for Deploying Real-Time Scoring

This topic gives two examples of how you may deploy real-time scoring. You may use it differently, depending on your business model.

• A company wants to drive intelligent decisioning in real time at the customer touchpoint, such as churn prediction in the Siebel Call Center. In this case, the user of the application triggers the execution of a predictive model as he or she updates or enters new customer information relevant to the predictive model.
• Customer information can change without an organization's immediate involvement and knowledge. In this case, a company might want to deploy a workflow process that detects changes in customer information. This workflow process triggers the execution of a predictive model and, depending on the resulting score, initiates corresponding action steps. These steps might include countermeasures such as offering rebates or gifts to potential churners.

This chapter assumes that you are following the first scenario. For details on configuring Siebel Workflow processes as mentioned in the second scenario, see Siebel Business Process Designer Administration Guide.