Customer Decision Hub and Decisioning Overview
This domain checks whether you can explain how Pega Customer Decision Hub (CDH) turns customer context into a single next-best-action (NBA), and how that differs from traditional campaign management.
The decision pipeline
- Eligibility/applicability – is this action even allowed for this customer?
- Suitability – should it be shown, given propensity and business rules?
- Arbitration – rank the survivors and pick the winner.
- Treatment selection – present the winning action with channel-specific content.
Vocabulary you must control
- Action – the thing being offered (retention offer, upsell, service message). Actions sit under Issue → Group.
- Treatment – how the action is presented in a specific channel (web banner, email, SMS copy).
- Propensity – predicted probability of acceptance from a predictive or adaptive model.
- Value – the business worth of the action to the organisation.
- Contact policy – frequency caps and suppressions that block or delay actions.
- Decision Data Store (DDS) – stores interaction history and model data so decisions run in real time.
Worked example
A telecom wants the best retention action for a customer opening the mobile app. Applicability removes actions the customer already owns. Suitability uses the model propensity for the remaining retention actions. Contact policy blocks any retention offer already shown twice this week. Arbitration ranks what is left using propensity and value weights, and the top action's app treatment is rendered. Reasoning: each stage narrows the candidate set, and arbitration only ranks actions that survived every earlier filter.
Traps that cost marks
- Treating highest propensity as the answer; value and contact policy can outrank it.
- Confusing an action with its treatment.
- Describing CDH as batch segmentation rather than per-customer, real-time decisioning.
- Forgetting that the NBA is always decided inside a channel/direction context.