Decisioning engines
AI-powered automated decision-making for customer engagement

What is a decisioning engine?
Businesses use decisioning engines to deliver personalized, real-time experiences to customers across channels. By leveraging a decisioning engine, marketing and CX organizations can deliver the right message or action at the right time to each customer, making their experiences more relevant, seamless, and engaging. This leads to stronger loyalty, better engagement, and improved business outcomes.
Why are decisioning engines important?
Decisioning engines are critical to unifying and scaling customer interaction management. The future of modern customer journeys relies on delivering personalization at scale across all channels and devices, when customers are most receptive to a brand message. They centralize disparate data streams, and workflows to automate content activation faster and more accurately than human labor alone.
Benefits of decisioning engines
- Personalization at scale
Decisioning engines analyze real-time data and customer interactions including customer context, past behaviors, current intent, and channel preferences to deliver personalized messages, offers, and experiences tailored to each individual. - Optimized resource allocation
Decisioning engines prioritize the most impactful actions by evaluating potential outcomes across channels and allocating resources to high-value opportunities while also reducing manual processes associated with marketing operations. - Enhanced agility and responsiveness
Decisioning engines enable marketers to respond instantly to changes in customer behavior, market trends, or competitive dynamics. By integrating data from multiple sources and leveraging AI-driven continuous learning, they provide a cohesive, evolving view of each customer.

How do decisioning engines work?
Decisioning engines analyze real-time data across channels, applying AI and machine learning to evaluate customer behaviors and preferences. They deliver personalized, context-aware decisions for marketing, sales, and service, continuously improving outcomes through adaptive learning and automation.

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