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Defining an adaptive model

Updated on July 5, 2022

Predict customer behavior and adjust your marketing strategy by configuring an adaptive model.

  • Creating an adaptive model

    Create an adaptive model to predict business outcomes or customer behavior, for example, the probability of successful case completion or a customer's propensity to click a web banner.

  • Adding adaptive model predictors

    When creating an adaptive model, select a wide range of fields that can potentially act as predictors. In the course of the learning process, adaptive models automatically select the best-performing predictors, which become active. The remaining predictors become inactive. Predictors are input fields for adaptive models.

  • Defining outcome values in an adaptive model

    Define the possible outcome values in an adaptive model to associate them with positive or negative behavior. The values defined for positive and negative outcome should coincide with the outcome definition as configured in the data flow that runs the strategy with the adaptive models that are configured by the Adaptive Model rule.

  • Configuring settings for adaptive models

    Configure the update frequency and specify other settings that control how an adaptive model operates.

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