“Audience segmentation” or “audience fragmentation” is a phenomenon that describes the process of partitioning mass audiences into smaller and smaller segments. It is considered as an inevitable outcome of competition in media markets. Hence, audience segmentation is expected to be stronger in high rather than in low-competition media environments.
Models of Audience Segmentation
The phenomenon of audience segmentation has been introduced to describe changes in the concept of an audience through the transition from old to new media environments. McQuail (1997) summarizes the concept of audience segmentation by means of four models that represent different stages in the transition. For television, which has experienced the most dramatic changes, McQuail (1997) defines these models as follows. The unitary model describes the early years of television (in the 1950s), when viewers either had no ability to select a program, because there was only one channel available, or could select at most among two or three channels. All viewers shared essentially the same television experience – there was more or less a single audience for the programs of one or a few channels. The pluralism model describes a status of “limited diversification” that came with an increased supply of television content and television channels. In many countries that introduced television in the 1950s, this development started in the late 1970s and 1980s. Besides channel diversification, viewers experienced temporal diversification. In addition to prime-time television, viewers were able to watch television during the daytime, in the morning, and at night. Further, most television markets diversified locally in this phase of transition, which meant that viewers could find programs that were unique for different locations (e.g., local television news or comedy and drama shows with stories from a particular region and only available in local television markets).
In the 1980s and 1990s, the multiplication of channels in many television markets made it possible that specific (special interest) channels had specific audiences and that viewers’ selective exposure differed significantly from that of the majority of viewers (core–periphery model). At the same time, most viewers still shared a common set of a few (general interest) channels. Mainstream content like national news, popular entertainment shows, and famous movies attracted audiences of all kinds to share experiences. The core– periphery model of audience segmentation is currently the dominant one in countries with multiple channels (including cable and public service channels).
Finally, the breakup model describes a situation in which no audience (or at least no core audience) exists any more. Viewers are distributed over many different channels. There is no systematic pattern that explains viewers’ channel selection. Viewers do not share or only sporadically share viewing experiences. This model of audience segmentation has not yet been realized but may be underway. New developments such as video on demand, digital TV, digital video recording, and online television, for example, may completely eliminate traditional programming and the temporal synchronization of viewers. In this environment every viewer creates his or her own “channel” with a program schedule that fits best to individualized patterns of viewer availability.
Although television has experienced the most radical changes in the new media environment, McQuail’s four stages of audience segmentation are not limited to television. All stages can be easily transferred to other traditional mass media such as radio and print. However, applying McQuail’s models to non-traditional, interactive media, like the Internet or video games, is more difficult. While the breakup model still assumes viewers that freely select specific (but given) content that has been prepared by professional content producers, non-traditional media environments provide a platform to exchange content among multiple (professional or nonprofessional) content producers and content consumers.
In highly interactive media forms such as modern video games, for example, users generate their own content. In new-generation role-playing video games, users become immersed in virtual worlds and narratives in which they are represented by virtual characters or avatars. Usually, a virtual world has been created by a game producer and defines the rules and the theme of a video game as well as the possible depth of content generation. Beyond this, however, video-game experiences are individualized and depend highly on the players’ decisions and interactions with the virtual environment. This means that audience segmentation in this media environment addresses both the free selection of a media platform among many alternatives and the generation of, and response to, individualized content. Hence, one might add to McQuail’s four models of audience segmentation a fifth: the “individualization model.” This defines the highest possible degree of audience segmentation, and the term “audience” may even appear inappropriate in this media environment. This raises the question of how the term “audience” is actually defined, and what exactly constitutes an audience.
The Audience Concept
At the beginning of mass communication research, the term “audience” was more or less defined as the group of simultaneous receivers of messages at the end of a linear communication process (i.e., essentially an information transfer from one metacommunicator to many individual receivers). This definition mainly addressed listeners of traditional radio and television. Since then, this conceptualization has been replaced by an understanding of audiences as active participants who are resistant to influence, selective, and defined by concerns and needs, as well as depending on specific social and cultural contexts (cf. McQuail 1997, 2005; Webster & Phalen 1997). Advertisers, journalists, filmmakers, and media managers all have different perspectives on and understandings of audiences. Moreover, the linear communication process from the early definition of audience has been supplemented by interactive and transactional processes.
Even simultaneous reception of messages no longer applies to contemporary definitions of audiences. Like radio stations and networks, which claim to reach specified audiences by aggregating listener and viewing ratings across time, new media forms may accumulate large audiences over time. The definition and use of the term “audience” require neither a temporal nor a directional restriction. As McQuail (1997, 143) puts it: “It is not just that the mass audience had fragmented physically as a result of multiplication and abundance of media outlets . . . , but that the meanings of ‘audience’ have multiplied.”
Another concept that is closely related to audience segmentation is that of audience polarization (Webster & Phalen 1997). Audience polarization is defined as the tendency of individuals to move to the extremes of either consuming or avoiding some class of media content. Classes of media content can be defined solely by content (e.g., program genres) or by content and structures that are used to deliver content (e.g., TV channels).
For example: audience segmentation posits that in a multi-channel TV environment, overall market shares of channels become increasingly smaller. However, audience segmentation does not explain whether low market shares result from everyone spending a smaller amount of time watching a particular channel or whether some subset of the audience is spending less time watching single channels and more time watching other particular channels. The more audience segments differ in composition between channels, the higher the extent of audience polarization. Or to put it in statistical terms: the more homogeneous audiences are within channels and the more heterogeneous audiences are between channels, the higher the extent of audience polarization. Similar heterogeneous audiences across channels would be an indication of low audience polarization.
Audience polarization helps to understand the social implications of the new media environment. For example, if fewer and fewer people share media experiences, one may consider audience polarization as a threat to cultural (or national) identities (cf. Katz 1996).
Empirical Evidence of Audience Segmentation and Polarization
In a recent study, Webster (2005) re-examined empirically the phenomenon of audience segmentation and polarization. He concludes that audience segmentation is well underway and has been rather underestimated than overestimated. In the United States, for example, the three big nationwide networks (ABC, CBS, and NBC) together rarely reach average audience shares of higher than 20 percent nowadays. Moreover, audience segmentation is occurring everywhere in multi-channel TV environments. In addition to audience segmentation, there is empirical evidence for a modest audience polarization. This tendency, however, is still mainly driven by the structure of the media environment itself. Many TV channels, for example, are still not available to all audiences.
On a methodological level, audience segmentation can be studied by using standard audience research methods such as survey and diary techniques. In most multi-channel TV environments so-called “people-meters” are well established. These record electronically who watched which channel at what time. The combination of media usage data with the stated preferences, needs, and opinions of people can be used to better understand the compositions of audience segments. Statistical cluster and classification procedures are frequently applied for this purpose.
- Chan, E., & Vorderer, P. (2006). Massively multiplayer online games. In P. Vorderer & J. Bryant (eds.), Playing video games: Motives, responses, and consequences. Mahwah, NJ: Lawrence Erlbaum, pp. 77– 90.
- Katz, E. (1996). And deliver us from segmentation. Annals of the American Academy of Political and Social Science, 546, 22 –33.
- McQuail, D. (1997). Audience analysis. London: Sage.
- McQuail, D. (2005). McQuail’s mass communication theory, 5th edn. London: Sage.
- Webster, J. G. (2005). Beneath the veneer of segmentation: Television audience polarization in a multichannel world. Journal of Communication, 55(2), 366 –382.
- Webster, J. G., & Phalen, P. F. (1997). The mass audience: Rediscovering the dominant model. Mahwah, NJ: Lawrence Erlbaum.
- Webster, J. G., Phalen, P. F., & Lichty, L. W. (2006). Rating analysis: The theory and practice of audience research, 3rd edn. Mahwah, NJ: Lawrence Erlbaum.
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