Creating an adaptive model

Create an adaptive model to predict customer behavior. Refer to your Adaptive Model rule in a strategy to use the propensity that the model returns. When you run the strategy, adaptive models are created automatically for each unique combination of model identifiers in the Adaptive Model rule instance.
  1. In the navigation pane of Prediction Studio, click Models.
  2. In the header of the Models work area, click New > Adaptive model.
  3. In the Create adaptive model dialog box, enter the model Name and select the Business issue.
  4. In the Positive outcome section, enter the customer responses to the behavior you want to predict:
    • To select an available positive outcome for the model, place the cursor in the empty field and, press Down Arrow, and click the outcome you want to use.
    • To define a new positive outcome for the model, enter the outcome that you want to use.
    For example:  Use Accept to indicate that a customer accepted an offer.
  5. In the Negative outcome section, enter which customer responses represent the alternative outcome you want to predict:
    • To select an available negative outcome for the model, place the cursor in the empty field, press the Down Arrow key, and click the outcome you want to use.
    • To define a new negative outcome for the model, enter the outcome you want to use.
    For example:  Use Reject to indicate that a customer refused an offer.
  6. In the Save model section, select the applicable class of the model by performing the following actions:
    1. In the Apply to field, press Down Arrow, and select application class of the model.
    2. In the new fields that appear, select a development branch and a ruleset.
  7. Confirm the new adaptive model settings by clicking Create.
What to do next:  Configure your adaptive model to meet your business objectives by adding a list of candidate predictors. See Adding adaptive model predictors.

It is recommended that you add an extensive list of candidate predictors for your adaptive model instances to learn from. In the course of the learning process, adaptive models automatically select the best-performing predictors, which become active. The remaining predictors become inactive.

For more information, see About Adaptive Model rules.