Free PEGACPDS26V1 sample questions

Correct answer: Business Levers

Business levers allow you to apply business logic to prioritize certain actions over others under specific conditions. By applying a business lever (such as a weighting factor when a high churn propensity is detected), the arbitration formula will artificially boost the priority of the retention offer over the cross-sell offer, satisfying the business requirement.

Correct answer: To establish a control group that measures the true business lift generated by the AI model compared to random selection.

In Pega CDH, a control group is a small, randomly selected audience segment that receives random actions rather than AI-optimized next best actions. This allows the organization to measure the effectiveness (lift) of the AI model by comparing the response rates of the target group against the control group.

Correct answer: ADM automatically groups highly correlated predictors together and only utilizes the best-performing predictor from that group for scoring.

To prevent issues associated with multicollinearity, Pega's Adaptive Decision Manager (ADM) automatically identifies highly correlated predictors and places them into predictor groups. During scoring, ADM only activates and uses the single best-performing predictor from each group, ignoring the others.

Correct answer: False

False. Adaptive models in Pega are self-learning. They continuously and automatically update their internal scoring algorithms in real-time as customer responses are captured, without requiring offline manual retraining by a data scientist.

Correct answers: They are effectively driving business value because they have a high rate of positive customer responses.; They are struggling to learn and may lack sufficient relevant predictors to differentiate customer behavior.

Models in the bottom-right quadrant have a high Success Rate (X-axis) but low Performance/AUC (Y-axis). Because they have a high success rate, they are generating positive responses and driving business value. However, their low AUC indicates they are not effectively differentiating between who will and will not accept the offer, essentially acting like a static rule or benefiting from a universally popular offer.

Models in the bottom-right quadrant have a high Success Rate (X-axis) but low Performance/AUC (Y-axis). Because they have a high success rate, they are generating positive responses and driving business value. However, their low AUC indicates they are not effectively differentiating between who will and will not accept the offer, essentially acting like a static rule or benefiting from a universally popular offer.

Correct answer: 'Click' should be defined as the target behavior, and 'Impression' (or 'Ignore') should be defined as the alternative behavior.

In ADM outcome mapping, the behavior you want to predict (the positive outcome) is mapped as the 'Target' behavior. The negative or non-response (such as an impression without a click, or an explicit ignore) is mapped as the 'Alternative' behavior. The model calculates the propensity of the target behavior occurring.