Data Mining to Profile Tv Viewers

Mining thousands of viewing choices and millions of patterns, advertisers and TV networks identify household characteristics, tastes, and desires to create and deliver custom targeted advertising. THE emergence of the digital personal video recorder (PVR) is likely to coincide with profound changes in television viewing, as viewers use the technology to time-shift their viewing and skim over or eliminate " in stream " commercials. This trend represents a significant threat to television advertisers and service providers, jeopardizing the traditional means by which advertising finances so-called free programming. Indeed, due to the rapid mass-market acceptance of PVRs, Forrester Research has predicted the viewing of television commercials could decrease by 20% in just a few years. Forrester analyst Joshua Bernoff suggests this is because the PVR " degrades the value of advertising, " predicting the eventual disappearance of an important social element of the television viewing model, that is, " television in which you sit through the commercials is about to be replaced " [6]. Advertisers and service providers must adapt to these changes, as well as to the opportunities, engendered by the PVR. For example, because PVRs are programmable, they can record and transmit household viewing patterns. Data mining techniques can then be used to predict a household's characteristics from its viewing choices, and customized advertising relevant to that type of household can be sent through its PVR. Such targeted advertising is more likely to be viewed and influence purchasing behavior than its non-targeted counterpart; it is also more likely to be more efficient because fewer placements are needed to achieve the same number of exposures to the desired demographic group. From the viewer's perspective, efficient delivery of advertising subsidizes delivery of programming while reducing advertising obtrusiveness. To deliver targeted advertising, TV networks must be able to identify the members of target groups in a way that is accurate, unobtrusive, and auditable. Toward these ends, we have developed a data mining viewer profiling system—the Advertising Delivery System (ADS)—to identify the demographic and psychographic (behavioral) characteristics of viewers based on their viewing patterns. Our research is based on the premise " you are what you watch, " or individuals' viewing habits tend to reveal their most personal characteristics, tastes,