Digital Connexxions Corp. announced that the United States Patent and Trademark Office has granted Patent Number 6,466,975 for its innovative predictive marketing technology.
“We are immensely proud of our invention, as it is one of the first marketing applications that uses artificial intelligence technology to learn the subscriber’s preferences real time and dynamically presents the most relevant promotion and offer,” said John Ching, CTO of Digital Connexxions. “Using advanced machine learning algorithms in combination with our proprietary high-performance rules engine, we dynamically create a virtual profile of the subscriber based on historical information in the subscriber database, third-party demographics data, as well as transactional data we collect in real time. Based on collected response data, the system automatically generates knowledge represented in expert system rules to enhance the effectiveness of a marketing campaign. The A. I. engine actually learns and becomes smarter at predicting what the subscriber will want to do next, with each additional interaction. We are excited that we are able to successfully commercialize the technology that ultimately benefits our clients.”
Currently, this technology is being integrated with Digital Connexxions’ flagship product SubscriberWorx, which is used by many major publishers and list managers to successfully manage their subscriber lists. Over $5 million dollars have been invested in the research and development of this patented predictive marketing technology thus far.
The central component of this technology is the A.I. engine. Each request to the engine involves a two part dynamic decision, one to select the rule(s) to be applied, and second to select the dynamic content according to the best rules. For example, Barbara is a subscriber matching the profile of a high- income individual. A marketer may use a simple web-based UI to define a promotional rule that states: “IF wealthy and female then offer diamond earrings.” When Barbara is included in a targeted campaign, the A.I. engine would determine that Barbara is female and wealthy and therefore should receive the diamond earrings promotion. Moreover, with the dynamic rule optimization feature that is revolutionary in the Digital Connexxions’ predictive marketing technology, if subsequent analysis of the response data shows that the original rule produced a poor clickthrough rate compared to another rule for individuals matching that virtual profile, then the better rule would dynamically be weighted higher and in subsequent campaigns Barbara may be offered the “chocolate truffles” promotion instead.
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