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Enabling predefined Interaction History predictors for existing adaptive models

Suggest edit Updated on March 11, 2021

Apply historical interactions data to improve adaptive model predictions of future customer behavior, by enabling an additional set of potential predictors based on a predefined Interaction History summary.

For each distinct combination of SubjectID, SubjectType, Channel, Direction, and Outcome, the additional set of predictors contains pxLastGroupID, pxLastOutcomeTime.DaySince, and pxCountOfHistoricalOutcomes.

The aggregated predictors are enabled by default for every new adaptive model, without any additional setup. For existing adaptive models, you can enable them manually.

Note: The maximum number of IH predictors that is defined in prconfig/alerts/IHPredictorsThreshold is 300. When that threshold is exceeded, Pega Platform returns the PEGA0105 alert.
  1. In the navigation pane of Prediction Studio, click Models.
  2. Open an adaptive model that you want to edit.
  3. On the Predictors tab, click IH Summaries.
  4. For the Predictors based on interaction history summaries are option, select Enabled.
Result: The adaptive model uses the IH Summary for making predictions.What to do next: Set pyIHSummary as materialized.
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