Closed-loop Recommendation Engines: Analyst Insight report on Oracle Real-Time Decisions (RTD)
- by Mike.Hallett(at)Oracle-BI&EPM
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)
Highlights:
"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."
