Closed-loop Recommendation Engines: Analyst Insight report on Oracle Real-Time Decisions (RTD)
By Mike.Hallett@Oracle-BI&EPM on Nov 29, 2011
In November 2011, Helena Schwenk of MWD Advisors, published her analysis on Oracle Real-Time Decisions. She summarizes as follows: "In contrast to other popular approaches to implementing predictive analytics, RTD focuses on learning from each interaction and using these insights to adjust what is presented, offered or displayed to a customer. Likewise its capabilities for optimising decisions within the context of specific business goals and a report-driven framework for assessing the performance of models and decisions make it a strong contender for organisations that want to continuously improve decision making as part of a customer experience marketing, e-commerce optimisation and operational process efficiency initiative."
This is an outstanding report to share with a prospect or client as it goes into great detail about the product and its capabilities. It also highlights the differences in Oracle's Real-Time Decisions product vs. other closed loop recommendation engines.
I encourage you to share this report with your clients and prospects. It can be downloaded directly from here - MWD Advisors Vendor Profile: Oracle Real-Time Decisions. (expires in November 2012)
"At the core of RTD lies a learning engine that combines business rules and adaptive predictive models to deliver recommendations to operational systems while simultaneously learning from experiences."
"While closed-loop recommendation engines are becoming more prevalent... there are a number of features that distinguish RTD:
- It makes its decisions in the context of the business objectives, such as maximising customer revenue or reducing service costs
- Its support for operational integration offers organisations some flexibility in how they implement the offering."