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essay about this that is a concise representation of revolution of media in terms of how audiences that are captured, analyzed and sold to the advertisers; particularly understanding the capture of the media and how it that has evolved with time to the present internet era.
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#Audience Manufacture in Broadcasting Essay
Article Summary
This is a concise representation of revolution of media in terms of how audiences are captured, analyzed and sold to the advertisers; particularly understanding the capture of the media and how it has evolved with time to the present internet era.
Audience manufacture calls for concise determination of size and behavior of the audience and by the use of a set of measurement procedures shaped by industry dynamics and technological usage patterns, the audience is manufactured and sold to the advertisers. The need for advertisers to understand the quantity and quality of audience they were paying for led to the evolution of audience manufacture and analysis (Bermejo 2009).
Audience manufacture dates back to the radio era where different methods of advertisement approaches were carried out over the radio. However, the mode of determining or measuring the quantity, behavior and response of the audience receiving began with the invention of advertising rating systems most of which depended on the sampling concept. Such early methods included the famous Nielsen’s metered system.
The growing need for understanding of media audience led to rise of independent third party to carry out the research. With much struggle and improvements, national representative samples were achieved at around 1940 (Bermejo 1).
Initially, the concept of dividing a program into segments which were sold to different sponsors was preferred but this later changed to spot commercials. Different methods of measuring audience exposure time were invented with the most prominent being use of questionnaires, telephone and booklets with each having its advantages and disadvantages.
This was later followed by A.C. Nielsen of audiometers which did not last for a long time due to the increased need for detailed demographics and personal viewing patterns as well as the shift from household to individual unit of audience. Audiometers could not keep up with the diminishing size and increased portability of radio receptors.
People meters provided viewing data at the individual level and thus provided more precise information for audience. Possible solutions such as satellite, cable and digital television as well as switching channels using remote controls brought yet another complexity in audience measuring techniques (Bermejo 1).
Evolution of the society brought about yet another advertisement platform with the internet technology. Internet technology provided better methods of audience analysis with techniques such as trace Log files, and use of tags both of which could provide the needed information for interaction of the audience with the internet platform.
However, they could not give details of the number of viewers or their profile for a given page. Search for a standard source of measurement took the center stage. This brought about new methods of advertisement pricing depending on cost-per-action on the platform. Internet is global in nature and thus presents a problem of precise sampling such as home or work based users. Metered panel method when integrated with other methods seems to generate acceptable audience information.
The idea of site visit is a somewhat misleading since there are far too many considerations to be factored in. Google provided part of the solution by clearly separating advertising from search results and distinguishing between organic, algorithmic or editorial search results and sponsored links (Bermejo 1).
New searching methods developed with time and different types of advertising and pricing such as frequency, location and prominence dependent models, page relevance as well as pages pay-per-placement and system AdWords programs. This has brought yet another advertisement model based on the concept of quality scores whereby the price models are based on the performance of the relative sites (Bermejo 1).