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CRM/DRM: Infrastructure for the Celestial Jukebox
Unformatted Document Text:  traditional marketing techniques, such as circulation figures, ratings, and other audience-constructing techniques to measure their success against competitors. However, methods for retrieving quantitative data , such as subscription figures, telephone surveys, and user diaries, are expensive, imprecise, and subject to errors and bias. More recently, producers have increasingly focused on the quality, as well as quantity, of audiences by measuring their consumption habits, lifestyles, and psychological characteristics. Psychographic research, based on the Values and Lifestyles Program (VALS) typologies developed by SRI International of Menlo Park, California, represents such an attempt to further define and segment audiences. In addition to providing demographic information about consumers, VALS delineates audience "clusters," based on attitudes, behaviors, and consumer tastes. Such techniques relies heavily on "ascription," a statistical method in which probability is applied to available data to supply unavailable information. This method leads critics to accuse psychographic researchers of "making up numbers” (Beville, 1988). The typologies used in clustering, such as "old-fashioned" or "other directed," are arbitrary labels that may not accurately represent the data. These methods have been further supplemented by active surveillance measures such as people meters, yet media producers remain hampered by a lack of real-time information about their target audiences. Distinguishing real demand from false readings of “quiet consumers” is an ongoing problem in the absence of a continuous stream of information from the marketplace. Furthermore, the concept of a "fixed" audience is highly suspect. Ang (1991) notes that the audience's composition is shifting and tentative; the need to "capture" this audience fuels producer speculation on audience behavior, which in turn creates a greater emphasis on more "accurate" and detailed scrutiny. Advanced research, which seeks to bring the audience under microscopic view, reveals that it is constantly dissolving and reforming. Audiences are never fully captured; instead, they are pursued through accumulating more information. Research confirms that audiences are constantly aggregates of indicators, fueling the need for more and more data. In the absence of a real-time surveillance system, audience measurement can make control more difficult. However, the interactive nature of the Internet allows producers and distributors to count “hits” and monitor consumer transactions in real-time, creating streams of detailed information about online user behaviors that also may be further enriched and merged, traded, and sold as commodities in their own right. The data mining and analytic functions of customer relationship management software provide e- commerce companies with marketing knowledge required for managing customer databases. However, while intellectual property laws have been strengthened, the ultimate goal of cultural producers and distributors -- predicting consumer behavior-- remains elusive in e-commerce, just as it has for traditional sales channels. Personalization systems are descriptive, rather than predictive. They cannot tell why a

Authors: Burkart, Patrick. and McCourt, Tom.
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traditional marketing techniques, such as circulation figures, ratings, and other audience-constructing
techniques to measure their success against competitors. However, methods for retrieving quantitative
data , such as subscription figures, telephone surveys, and user diaries, are expensive, imprecise, and
subject to errors and bias.
More recently, producers have increasingly focused on the quality, as well as quantity, of audiences by
measuring their consumption habits, lifestyles, and psychological characteristics. Psychographic
research, based on the Values and Lifestyles Program (VALS) typologies developed by SRI International
of Menlo Park, California, represents such an attempt to further define and segment audiences. In
addition to providing demographic information about consumers, VALS delineates audience "clusters,"
based on attitudes, behaviors, and consumer tastes. Such techniques relies heavily on "ascription," a
statistical method in which probability is applied to available data to supply unavailable information. This
method leads critics to accuse psychographic researchers of "making up numbers” (Beville, 1988). The
typologies used in clustering, such as "old-fashioned" or "other directed," are arbitrary labels that may not
accurately represent the data.
These methods have been further supplemented by active surveillance measures such as people meters,
yet media producers remain hampered by a lack of real-time information about their target audiences.
Distinguishing real demand from false readings of “quiet consumers” is an ongoing problem in the
absence of a continuous stream of information from the marketplace. Furthermore, the concept of a
"fixed" audience is highly suspect. Ang (1991) notes that the audience's composition is shifting and
tentative; the need to "capture" this audience fuels producer speculation on audience behavior, which in
turn creates a greater emphasis on more "accurate" and detailed scrutiny. Advanced research, which
seeks to bring the audience under microscopic view, reveals that it is constantly dissolving and reforming.
Audiences are never fully captured; instead, they are pursued through accumulating more information.
Research confirms that audiences are constantly aggregates of indicators, fueling the need for more and
more data. In the absence of a real-time surveillance system, audience measurement can make control
more difficult. However, the interactive nature of the Internet allows producers and distributors to count
“hits” and monitor consumer transactions in real-time, creating streams of detailed information about
online user behaviors that also may be further enriched and merged, traded, and sold as commodities in
their own right.
The data mining and analytic functions of customer relationship management software provide e-
commerce companies with marketing knowledge required for managing customer databases. However,
while intellectual property laws have been strengthened, the ultimate goal of cultural producers and
distributors -- predicting consumer behavior-- remains elusive in e-commerce, just as it has for traditional
sales channels. Personalization systems are descriptive, rather than predictive. They cannot tell why a


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