Commoditizing the Home Audience
The datafication of mass media
In the twentieth century with the advent of broadcast radio and then television, marketers tracked and studied viewers’ habits, to the influence consumer behavior on a mass scale.
“It is the gradual, slight, imperceptible change in your own behavior that is the product.”
— Jaron Lanier, The Social Dilemma, 2020
Engineering consumer behavior and ignorance requires marketers to invent ways to collect data from willing test subjects.
Active Audience Participation
The home is a laboratory
In the early years of broadcast television, marketers were able to gain audience participation by appealing to the convenience of never having to leave the comforts of home. However, from the 1950s through the 80s, because of technological limitations, Nielsen and others collected and sold television consumer data to marketers by asking subjects to submit viewing activities in the form of written diary entries. Yet, collecting data from subjects who self-monitored and reported was fraught with inconsistencies and biases. Furthermore, motivated by commercialism, marketers sought to learn how to influence the behaviors of consumers who would make businesses the most money, middle-to-upper class households; therefore, sample audiences consisted mostly of White individuals.
The corporate sellout
Since television networks made money by selling ad space, programming had to appeal to the paying advertisers’ targeted demographics. By the mid-80s, networks were narrowcasting towards smaller audiences, which meant storylines were often formulaic concentrating on commonalities rather than differences, and shows could more easily be cancelled (Buzzard, 2012, p. 51). Also, product placement was a strategy deployed to influence consumers to future purchase-decision making.
New technology posed a threat to the success of advertisers
Introduced in the early 1960s, the television remote control made it easier for home viewers to change the channel and decrease the audio volume when commercial breaks occurred.
Also by the mid-80s, innovations and investments in monitoring technologies began to allow more accurate calculations of program audience size and did not require active audience participation.
The dawn of digital surveillance
The Peoplemeter
Investing in technologies
By the 1990s, Nielsen was collecting data via peoplemeters. All that was required of the test subjects using the remote control people meter device was to input the audience size number when they turned on their television set. Yet, impatience and lack of commitment often contributed to inaccurate data entry.
Although adaptions of technological innovations allowed for more accurate broadcast television consumer data, inconsistent reliability of participants remained an issue.
Examples of tested peoplemeter technologies during the 1980s and 90s
Ultrasonic motion detectors
Infrared body heat sensors
Face scanners
Wearable devices
“In a period of technological competition and rapid adaption—when peoplemeter technologies competed to be more accurate, more fail proof, more inventive—the body became itself a technology: one that, if properly disciplined and utilized in the process of commodification, could make viewers more reliable consumers.”
— Jennifer Hessler, Peoplemeter Technologies and the Biometric Turn in Audience Measurement, p. 401
Card-carry membership
The Video Store
Expanded possibilities of motion picture viewership
With the invention of the VCR player and thus VHS, the consumer controlled the speed of motion pictures by pressing command buttons (play, pause, fast-forward, rewind)— from the comfort of one their home, which made the movie-watching experience more personal. Going to the cinema or waiting for scheduled broadcast showings were no longer the only options to enjoy motions pictures. In the 1980s through the mid-2000s, the local video store provided an alternative to purchasing expensive VHS tapes that you may only view once; instead, by renting video for a small fee from the store, you could take tape home, view, and then return it after a short term.
The local video provided a service that made it affordable for more people to watch more movies, than possible from broadcast showings.
“Video store mapped the effects of affiliation thinking on video consumers’ habits and desires for exclusivity. As neighborhood stores gave way to corporate rental chains, consumers were taught to value the privileges of membership within corporate rental chains.”
— John C. Murray, The Consumer has been Added to Your Video Queue, p. 58
Success with the personalization business model
Netflix
Netflix and the datafication of mass media in the 21th century
Netflix’s delivery of personalized curation of content to its customers is more evolutionary than revolutionary. Like the marketers who used broadcast television as a channel to study viewers and advertise products, Netflix uses collected customer data to deploy behavior science and personalization to drive user engagement. However, innovations in technology makes it possible for more precise behavior tracking and the use of algorithms, powerful prediction tools, to automate recommendations, which guides users towards future decisions.
Today’s unprecedented consumer buy-in and engagement retention
Netflix’s success as a video streaming service provider can be attributed in part to it taking advantage of the concept of democratizing mass media consumption, earlier expressed by video stores, broadcast television, cinema, etc., and making it even more accessible and providing more choice to the consumer. Now, while consumers scroll through a digital content library housing thousands of titles, Netflix is simultaneously collecting behavior data to inform its algorithm how to act to keep its user engaged. Thus, consumer buy-in is often achieved because Netflix provides a convenience of assisting the user narrow their choice, and then the instant gratification of viewing the title from wherever the user is connected to the Internet.
“In crucial ways, [Netflix] operates as a vehicle of information and evaluation. Expressed visually via menu presentation, descriptive language and images, and suggestion email…the recommender system is a tool of surplus management, a focalizer of attention, and so much more.”
— Frey, Netflix Recommends, 2020, p.66
Commercial interests power the datafication of mass media. From its advent, marketers perceived broadcast television as a medium to not only advertise products and services, but analyze consumer behavior to influence future decision on a mass scale. Because television networks profit from the airtime they sell to advertisers, programming and its storytelling continues to be affected by analysis’ interpretation of audience participation measurements. Technological innovation and adaption have changed the methods of consumer data collection from analyzing self-reported handwritten diary entries samples to a more automated systems where data-fed algorithms quickly make predictions that guides consumers towards future decisions.
The Internet, which has evoked an unprecedented voluntary cooperation from consumers (Stevenson, 2018, p.75), allows Netflix and others unprecedented access to user data to deploys behavior science and personalization to drive user engagement. Whereas marketers in the second half of the twentieth century could only access sample data, which Mayer-Schönberger & Cukier (2014) note is an artifact of a period of information scarcity (p. 13). The convenience of the digital experience has created an environment of cooperative surveillance because users deem the transaction of entertainment for data collection mutually beneficial.
References
Buzzard, K. (2012). Tracking the audience: the ratings industry from analog to digital (1st ed.). Routledge. https://doi.org/10.4324/9780203149492
Frey, M. (2021). Netflix Recommends: algorithms, film choices, and the history of taste. University of California Press.
Hessler, J. (2021). Peoplemeter Technologies and the Biometric Turn in Audience Measurement. Television & New Media, 22(4), 400–419. https://doi.org/10.1177/1527476419879415
Mayer-Schönberger, V., & Cukier, K. (2014). Big data : a revolution that will transform how we live, work, and think
(First Mariner books edition.). Mariner Books, Houghton Mifflin Harcourt.
Movieclips. (2011, October, 9). Wayne's World (6/10) Movie CLIP - I Will Not Bow to Any Sponsor (1992) HD [Video]. YouTube. https://www.youtube.com/watch?v=KjB6r-HDDI0
Murray, J. C. (2019). The Consumer has Been Added to Your Video Queue. In K. Pallister (Ed.), Netflix Nostalgia: Streaming the Past on Demand (1st ed) (pp.57–74). Lexington Books/Fortress Academic.