Oracle has announced the general availability of Oracle Real-Time Decisions Release 3.0. Oracle Real-Time Decisions is a decision management platform to deliver targeted recommendations during customer interaction, or wherever optimized decisions need to be made in business processes such as risk management, retention management or cross-sell/upsell.
"What's unique about Oracle Real-Time Decisions is that through a closed loop feedback mechanism it is able to learn and self-adapt to what is being observed through presentation of different messages and offers to customers. This can be applied across any customer touchpoint," Paul Rodwick, vice president of product management, Oracle Business Intelligence, tells 5 Minute Briefing. "Most commonly Oracle Real-Time Decisions has been used on websites, e-commerce or web self-service sites, or very often with inbound customer contact centers for customer service or customer sales."
Oracle Real-Time Decisions applies predictive models and business rules to optimize recommendations in real-time against specific, sometimes conflicting commercial goals, and then automatically uses a feedback loop to deliver ongoing improvements. This integrated approach yields greater returns than rules-based systems or traditional predictive model solutions, according to Oracle.
At the core of Oracle Real-Time Decisions is its Decision Framework which allows business users to implement differentiated and targeted enterprise "Decisions."
With Oracle Real-Time Decisions Release 3.0, the Decision Framework introduces a number of enhancements. To streamline application integration with companies' business processes and IT architecture, Oracle Real-Time Decisions allows "choices" and other elements participating to its Decisions to be stored and administered externally, enabling systems such as e-commerce, CRM, transactional, and others to take advantage of Real-Time Decisions functionalities without complex process reengineering.
The new release unifies real-time and batch decision logic into a centralized enterprise repository, enabling cross-channel deployments. It also adds new metrics, controls and reports that help the system gauge the degree of confidence in its self-learning predictive models, and actively prevents use of inappropriate recommendations; and allows the delivery of decisions based on numerical business data such as predicted amount spent, call duration or visit duration.
Additionally, the new release provides enhancements to Oracle Real-Time Decisions Base Application, which provides a library of pre-configured components representing the collective best practices of the most successful deployments of the product, and speeds implementation and maximizes the ROI of product implementations.
"What's interesting about Real-Time Decisions is that it goes far beyond rules-based systems where you need to specify very explicitly and carefully all the different if-then-else conditions for how to treat a different," states Rodwick. "With Oracle Real-Time Decisions, it uses rich statistical models to in effect put the decisioning process on a supercharger to be able to automatically learn, predict the right treatment and then observe through a closed loop feedback mechanism so it can do an even better job for that customer next time or for any other customer." For more information, go here.