Behavioral Targeting Classifications Read Between The Lines
Mike Petit, cofounder of OpenAmplify, tries to convince me his company's 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. It's part of a new tool the company launched last week.
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. Well, that's according to Petit.
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.
Since the technology allows people to understand behavior, I ask Petit if the U.S. government uses it. Knowing of no known government agencies as direct clients, he says thousands of API keys are in use, no questions asked. The company, based 25 miles from the U.S. Pentagon building, might suggest some of those have been utilized by the U.S. government, but that's just an assumption on my part. Petit does admit the company has been contacted by folks at numerous homeland security agencies, which shows interest, but he has no direct conversations with anyone in the government sector.
From there the conversation shifts to the Georgia Tech search engine I wrote about last week in the Search Marketing Blog. The technology, created by a doctoral student, 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? Oh, yeah, Petit says, jumping to a conversation he had with a guy sitting next to him during a plane ride. This guy wanted to determine what type of car a salesperson might sell someone based on what medical articles he reads online. Petit says a guy who reads about Viagra might equate to someone looking for a convertible.
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, Petit says, so "if you want to see the world through rose-colored glasses, we will make sure everything is pink."