Pega Marketing Consultant key terms

The single action the system selects to present to a customer at a given moment, chosen by ranking eligible actions against predicted customer response, business value, and contextual constraints.

A hierarchical model of shapes that computes a result, such as the best action or a score, by combining data, predictions, filters, and ranking logic in a defined execution order.

A reusable building block inside a decision strategy, such as a Proposition Data shape or Filter shape, that reads or transforms data and passes results to connected downstream shapes.

The canvas where a decision strategy is authored, showing shapes, their connections, and the data flow from entry points to the final result component.

A concrete offer or treatment an organization can present, defined in a business hierarchy with properties, treatments, and eligibility rules, and ranked by a decision strategy.

The runtime instance of an action or offer that a decision strategy evaluates, carrying propensity, value, and context so it can be filtered, scored, and ranked.

The top level of the business hierarchy that names a broad customer need or business objective, such as retention or acquisition, and groups related actions under it.

The middle level of the business hierarchy, sitting under an issue and above individual actions, used to organize offers that serve the same sub-objective.

The concrete presentation of an action, such as a channel-specific creative or message variant, that determines how the offer is rendered to the customer.

A predicted probability that a customer will respond positively to a specific action, produced by a predictive model and used to weight offers during ranking.

A statistical model trained on historical outcome data to score customers on a target behavior, such as likelihood to accept or to churn.

A model that updates continuously from live customer responses, adjusting predictions as behavior changes without requiring a full offline retrain.

A configurable scoring component that combines weighted customer attributes into a numeric score, often used for eligibility, prioritization, or segmentation.

The monetary or strategic worth assigned to an action, used with propensity to compute expected value so the highest-value offer surfaces in ranking.

A ranking metric calculated by multiplying an action's propensity by its business value, allowing offers to be compared on anticipated return rather than likelihood alone.

The set of conditions an action or customer must satisfy to be considered, applied before ranking so ineligible offers never compete for selection.

Rules that determine whether a proposition applies to a specific customer context, such as segment, product holdings, or channel, evaluated during strategy execution.

A strategy component that removes propositions failing specified conditions, reducing the candidate set before scoring or ranking.

The ordering of eligible propositions by a chosen metric, such as expected value or propensity, so the top result becomes the selected next-best-action.

The process of resolving competition among actions across issues and groups, applying priorities and constraints to decide which offers win for a customer.

Rules limiting how often and through which channels a customer may be contacted, applied during arbitration to suppress over-contacted offers.

Temporary or permanent removal of an action from consideration for a customer, driven by contact limits, opt-outs, or business rules.

The customer, context, and reference data a strategy reads at runtime, supplied through data flows and page properties rather than hard-coded values.

A configuration that defines how data is loaded, transformed, and mapped into the decisioning environment so strategies can access accurate customer context.

The consolidated record of a customer's attributes, interactions, and history that strategies and models use to personalize decisions.

The stored record of past customer contacts and responses, used to train models, enforce contact limits, and inform adaptive learning.

The medium through which an action is delivered, such as web, mobile, email, or call center, often determining which treatments are available.

A runtime component that accepts a request from a channel, executes the decision strategy, and returns the selected action and treatment within the response.

The high-volume storage layer that holds decisioning data and interaction history, supporting fast reads and writes for real-time strategy execution.

The terminal component of a strategy that defines the output structure, such as the selected action, its treatment, and associated scores, returned to the caller.

A strategy operation that partitions propositions into categories, enabling separate ranking or selection logic within each partition before final comparison.

Assigning relative weight or order to actions or groups so that, when multiple offers qualify, the business-preferred option takes precedence.

A defined subset of customers sharing characteristics, used to target actions, scope strategies, and tailor decision logic to distinct populations.

A testing capability that runs a strategy against sample or historical data to compare outcomes, validate logic, and estimate business impact before deployment.

A testing pattern where a control strategy competes with alternative strategies, and results determine which approach is promoted or retired.

The end-to-end design of data ingestion, model management, strategy execution, and channel integration that delivers real-time decisions reliably at scale.

The governed process for moving strategies, models, and rule changes across development, test, and production environments with version control and validation.

A constraint or monitoring control that keeps decisions within acceptable business bounds, such as fairness checks, spend limits, or volume caps.