Behavioral Targeting Classifications Read Between The Lines

Understanding consumer intent and knowing how to meet consumer needs seem like the perfect combination to determine the type of ad to serve up in any given scenario. It could become the key that unlocks nirvana for companies tapping behavioral targeting.
A new technology not only provides information on Web site visitors based on how they might think and feel about any given topic, but also their intention, whether or not they will buy or sell, and when. OpenAmplify recently launched Ampliverse, which allows companies to create taxonomies that classify Web content based on their requirements. Knowing who, when, where and why help answer questions on what ads to serve where. While it might be easy to determine the person with a positive view about BMWs should see an ad, it's more complicated to assign a classification and respond to the request for an ad position somewhere on the publisher's site -- which could offer about 600 spaces suitable to run an ad for a car.
Making a classification is just as important as understanding the content. It helps to increase the accuracy of behavioral targeting decisions. Different classification opinions for products and services make it more difficult.
Another technology is the Georgia Tech search engine created by a doctoral student which relies, in part, on machines helping Web sites learn dialect and other vernacular to improve search experiences and performance when language for queries might become unclear or unorthodox.
So, what about integrating the technology in Ampliverse? Let’s say you wanted to determine what type of car a salesperson might sell someone based on what medical articles he reads online. Using taxonomies not only tells the API the content to serve up, but it describes the type of convertible to sell him. Both the understanding and classification provides the flexibility to define a universe. This technology is still young but it has a lot of promise.