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How Should We Think About Audience Power in the Digital Age?

Joseph Turow

This chapter emphasizes the workings of corporate power in people's core relationships to the emerging digital media system. Its aim is to provide a counterbalance to a perspective with a lot of traction among contemporary academics: that the best way to think about audiences in the new age is to emphasize that individual audience members are exercising unprecedented control over the creation and distribution of media products. My exploration here centers on a corporate arena that academics tend to ignore: the media-buying sector of the advertising industry. Media buying involves purchasing space or time for advertising on outlets as diverse as television networks, billboards, radio stations, websites, mobile-phone decks, and newspapers. For decades, this activity was a backwater, a service part of advertising agencies that hired liberal arts majors just out of college for the lowest-paying jobs on Madison Avenue. That has changed. During the past 20 years, media-buying firms and a wide array of satellite companies that feed them technology and data have become lucrative magnets for software engineers and financial statisticians.

What they are creating is nothing less than new ways of thinking about audiences, of trading them, and of defining success in doing that. A new ecosystem of digital-marketing companies unknown to online individuals buys and sells data about them – including inferences based on those individuals, own online creations – without their permission or knowledge. Media-buying agencies and their advertising clients increasingly apply the information to determine what commercial messages individuals should get, what discount coupons they ought to receive, and what prices they should pay for products and services. The surreptitiously constructed market-driven profiles are also central to media firms' increasing competitive need to personalize information, news and entertainment. Built into the logic of these activities is social discrimination across a widening digital landscape. The trajectory raises a new version of the concerns about media's constructions of society for society that scholars first expressed in the late nineteenth and early twentieth centuries.

Media, Audience, and Community

Nicholas Negroponte was at the leading edge of academics who predicted that the power of the individual will be huge in the digital age. In the 1990s he headed the Massachusetts Institute of Technology's Media Lab, a hothouse for computer-based inventions supported by major corporations. His bestseller Being Digital was published in 1995, just a few months after the introduction of Netscape Navigator – the web browser that began to open gates to the Internet for non-techies. Negroponte (1995, p. 5) predicted how communication technologies of the early twenty-first century would allow us to become the captains of our own attention, to focus our interests on what counts for us. “Your telephone won't ring indiscriminately,” he wrote. “It will receive, sort, and perhaps respond to your incoming calls like a well-trained English butler.”

Negroponte seems to have taken it for granted that the creators of the new media technology would tilt it toward the individual's interests rather than toward those of the commercial or governmental spheres. It also made sense to him that users of the new media technology would revel in that individualism. The idea that, in the twenty-first century, individuals would hold power over media destinies took hold. An important book to trumpet this idea positively, from economic and legal standpoints, was Yochai Benkler's The Wealth of Networks. A cover blurb by University of Virginia communication professor Siva Vaidhyanathan accurately described it as “a lucid, powerful, and optimistic account of a revolution in the making.” Underscore the word optimistic. As Benkler (2006, p. 2) saw it, the technological openness and flexibility of the Internet would allow individuals unprecedented opportunities to collaborate outside of traditional business frameworks, toward the creation of an astonishing new world. “This new freedom,” he wrote, “holds great practical promise: as a dimension of individual freedom; as a platform for better democratic participation; as a medium to foster a more critical and self-reflective culture; and, in an increasingly information-dependent global economy, as a mechanism to achieve improvements in human development everywhere.”

Paralleling Benkler's bold claims for the collaborative efficiencies and individual creativities afforded by new information platforms were assertions that the new technologies provide people with previously unheard of levels of power to follow their individual interests. Some pointed to the positive potential for that power; others to its negative implications. Cass Sunstein took a dystopic slant in Republic.com and related writings. “The most striking power provided by emerging technologies is the growing power of consumers to ‘filter’ what they see,” he stated in an often-cited line (Sunstein, 2007, p. 5). To Sunstein, the ability to customize news sites by topic, to skip unpalatable topics, and to find comfort in ideologically similar blogs meant that people can live in idea cocoons either of their own making or in the making of which they collaborate with people who agree with them – a phenomenon that Sunstein called cyber-polarization.

Henry Jenkins saw these same individual powers quite differently. In Convergence Culture (Jenkins, 2008) and in other works, his focus was on very active contemporary audiences, which often push media companies to include them in their activities across multiple platforms, from television to magazines to fan conventions. It was a celebratory view, which reveled in people's growing influence on their symbol-making environment. What concerned Jenkins was not ideological polarization, but teenagers' cluelessness about what is appropriate when confronting the liberating technologies of the digital revolution. “The world has suddenly developed a printing press for every person on the planet,” he told Singapore's Straits Times, in response to consternation manifested there about a young woman who posted nude photos of herself on her website, “but it has not prepared its culture to be responsible or imagine the consequences of suddenly becoming media makers” (see Suk-Wai, 2007).

Jenkins overreached in his assertion: there surely are places where not everyone has even the most widespread digital medium, the cell phone – places, in fact, where those who have phones cannot afford to continually charge batteries for them. His basic point, though, is quite reasonable. Digital technologies are providing more people than ever with the tools for being media makers, and so for reaching out to more people than ever. Similarly clear in the new media landscape is the proposition that individuals are captains of their own interpretations and increasingly use them as starting points to create culturally exciting or politically dangerous worlds of understanding, for themselves and others. Yet his contentions and those of others (for example, those of Shirkey, 2010) about digital powers to the people beg an important question, which the proponents of such views almost never raise: Is the new individual and group autonomy the central force that will shape the way in which US citizens and others learn about the world and realize opportunities to benefit from it? Are other factors emerging that will be as decisive, or even more so?

The basic question is certainly not new with the digital age. Since at least the late 1920s, academics have disagreed about the primacy of human agency versus the power of media industries in shaping people's views of the world. During the first quarter of the twentieth century many sociologists and political researchers began to argue for the importance of seeing the media as an institution endowed with the power to construct society for society. Sociologists John Dewey (1927), Robert Park (1922), and Charles Cooley from the University of Chicago were especially noteworthy in emphasizing that the patterned messages that mass-produced periodicals circulated among millions of people allowed for the creation of a new type of broadly shared sense of US society even if people were separated by space and class. While they tended to write optimistically about ways in which the mass media could help society maintain an informed democratic public, political theorists were revealing a dark side to the media's community-making capabilities. Academics of the 1920s, 1930s, and 1940s such as Harold Lasswell (1927), Leonard Doob (1935), Alfred McLung Lee (1937), Ralph Casey (1939), and George Seldes (1938) worried that mass media organizations were powerful definers of society's issues and interests in the service of the rich and powerful. They felt that, by letting people know how media firms operate, they could help citizens protect themselves from the undue power of those firms to set content agendas that reflected the needs of marketers and other members of the political and economic elite.

Beginning in the 1920s, the individual view also gained strong academic attention. Especially noteworthy was a raft of major quantitative studies coordinated by the Ohio State University (Charters, 1933) showing that personal background characteristics led people to interpret what they heard, saw or read from the media in their own ways. During the 1930s and 1940s researchers at Columbia University (e.g., Katz & Lazarsfeld, 1955; Lazarsfeld, Berelson, & Gaudet, 1944; Lazarsfeld & Stanton, 1941) and the US military (e.g., Hovland, Lumsdaine, & Sheffield, 1949) added evidence to the argument that media have far more limited power to change people than many in society thought. Quantitative studies that supported this “active audience” view also emphasized people's power to choose the gratifications they wanted from whatever media content they selected. In the post-World War II struggle for mainstream academic space within the communication field, the idea of individual autonomy overshadowed the institutional view. Nevertheless, a new stream of critical communication researchers inflected by Marxist perspectives (for example, Ariel Dorfman and Armand Mattelart, 1975; George Gerbner, 1972; Herbert Schiller, 1969; and Dallas Smythe, 1977) argued that individual autonomy actually paled in the face of powerful business institutions. The capitalist system, working with government, they insisted, created the broad social and cultural agendas from which audience members had the opportunity to choose their materials.

Contrasting academic insights about audience power also converged on qualitative cultural studies. From the 1940s through the 2000s, left-leaning interests in historical and textual aspects of popular culture underscored the importance of understanding the industrial production of culture if one is to lay bare the dynamics of institutional power. One can certainly see this theme in the writings of the Frankfurt School (Theodor Adorno, Leo Lowenthal, and Herbert Marcuse), of the US mass culture debaters of the 1940s and 1950s (Dwight MacDonald, Irving Howe, and David Riesman), and of British cultural-studies theorists (Raymond Williams, Stuart Hall, and David Morley) from the 1940s into the 1980s. (See Rosenberg & White, 1957, for a classic compendium of readings from the Frankfurt School and from mass culture debates; also see Hall, 1982; Morley, 1980; and Williams, 1973). Yet by the 1980s disappointment that powerful culture-producing systems wouldn't respond to demands for substantial change coincided with quite a different analysis: that the actual meaning of a media article, song, sign or video came not from its institutional creation but from its individual receiver, who could often be seen to create interpretations that resisted authority. One marker of that view was Janet Radway's (1991) description of female members in a romance-novel club. She showed how, in order to fit their own emotional desires, these women essentially rewrote formulaic stories that, on the surface, echoed a male-dominated sexual world. Another marker was Dick Hebdige's (1981) research on British punk, which explored how those who followed the lifestyles expropriated different aspects of contemporary taste in clothing and decoration in order to fashion their self-images. The work by Negroponte, Benkler, and even Sunstein fits neatly into this corpus, which a commentator (Chavez, 2009, p. 904) described as indicating the means “by which consumers may control commercial meaning.”

Scholars with an institutional perspective and an eye on the emerging digital world have pushed back against this conclusion. One line of critique, drawing from critical political economy, points to the huge corporations that control the content that people are supposedly using autonomously in the fragmenting environment. Robert McChesney is a proponent of this view in works such as Rich Media, Poor Democracy (McChesney, 2000). He finds the key challenges to civic life to be not in the self-polarizing activities of individuals but in industry consolidations and in often secretive corporate strategies (enabled by government policies) over the ever-splintering media channels. A second stream of writings dives more directly into the human-agency fray. It sees the liberatory experiences that Jenkins and others have mentioned actually as a part of the strategies for exploitation. Mark Andrejevic (2007, p. 17) highlights various forms of corporate digital surveillance, in an attempt to counter what he calls “the ongoing attempt to equate new media technologies with the promise of empowerment, individuation, and creative control.” Along related lines, Detlev Zwick, Samuel Bonsu, and Aron Darmody (2008, p. 174) argue, for example, that media executives:

Dovetailing with this view of co-optation are variations on Dallas Smythe's 1950s notion of the audience as worker. Andrejevic (2003, 2007) argues bluntly that reality shows and user-generated content that sites such as Facebook use to draw advertising are direct examples of free labor in the interest of corporate profits. Other views try to accommodate both individual interests and corporate power. Tizziana Terranova (2000, p. 33), for example, emphasizes that in blogs, Facebook, YouTube, MySpace, and so many other places in the digital economy the free labor of consumers “is simultaneously voluntarily given and unwaged, enjoyed and exploited.” José Van Dijck (2009, p. 41) pushes this understanding even further, arguing for “user agency as a complex concept involving not only his cultural role as a facilitator of civic engagement and participation, but also his economic meaning as a producer, consumer, and data provider, as well as the user's volatile position in the labour market.”

As Van Dijck's formulation points to an important mixture of elements of individual autonomy amid corporate control, it implies the possibility of comparing the two assertions about audience power on the same plane. It's an important insight because, despite an ocean of writing about audience power over the past century the viewpoints have typically drawn on virtually separate worlds of media scholarship for their evidence. The audience-autonomy realm tended to focus on social–psychological “effects” research, while the corporate power domain brought evidence from organizational and industrial practices. What is different about the digital environment is that both academics celebrating audience power and those emphasizing corporate influence over audience members have made their cases on the basis of the production and distribution of messages. Van Dijck's formulation falls short, however, in suggesting the relative importance of the individual versus the institutional position. Certainly, Andrejevic and Terranova make the case for corporate media power. The scope of their examples may not match the broad scope of autonomy that Negroponte, Benkler, and possibly Jenkins claim for individuals in the digital arena.

The following pages sketch a counterpoint that does have overarching implications. The thesis is that new media-buying activities are the fundamental vehicles through which corporate influences erode individual autonomy in the digital-media age. None of this denies the spaces for individual and group initiative that Negroponte, Benkler, Jenkins, Sunstein, and others identify in the new environment. The fundamental logic of the emerging media-buying system, though, privileges institutional power. It aims to constrain individuals' everyday media contexts, as well as to channel audience choices and initiatives toward the goals of marketers and of publishers – that is, the creators and distributors of content.

The Transformation of Media Buying

Advertising lies at the core of much of the media, and it is the force that sustains much of the content on the web, including many – if not most – bloggers. At base, advertising involves payment for media attempts to persuade people to purchase or otherwise support a product or service. Most people likely think of advertising in terms of its most visible manifestation: the persuasive message. Yet the definition suggests two sets of activities in addition to the creation of the ad. One, which is part of marketing research, entails evaluating whether and how the message worked. The other, traditionally called media planning and buying, revolves around the provision of funds to pay for placement of the notice. Before the 1980s, advertising practitioners considered media buying and planning as rather straightforward, unexciting components of a standard (“full-service”) agency's offerings to clients. During the US broadcast television era (roughly, 1948–1988) the media-buying process became so predictable for national advertisers that many outsiders considered buying print space and broadcast time for clients a paint-by-numbers activity. They understood that a large part of the overall agency revenues typically came from the (then standard) 15% commission garnered from what clients spent to place their commercial messages. But they also knew that most of the work was conducted by low-paid recent college graduates who poured over boring television ratings and periodical circulation data in conjunction with advertising charges to determine the key measure of an ad vehicle's efficiency: CPM (cost per mil), the price for reaching 1,000 members of the target audience via that outlet.

In the 1960s and 1970s media-buying independents (those disconnected from advertising agencies) emerged in Europe and North America. The clients of these firms were not the blue-chip advertisers that full-service agencies on both sides of the pond coveted. Independents tended to attract direct-marketing companies that created their print ads or TV commercials themselves and needed an intermediary to buy space or time for them. Beginning in the mid-1970s, though, major advertisers in the UK began to accept that standalone buying firms sometimes had more expertise than buying units of full-service agencies. In 1988, advertising-agency entrepreneurs Maurice and Charles Saatchi bought the dominant independent buying firm and merged it with the media-buying activities of their three UK ad agencies into one standalone subsidiary, Zenith Media, with huge billings. A major rationale for media-buying agencies of Zenith's size was that it would help clients face two critical developments efficiently. One was the ongoing fragmentation of electronic media as commercially supported cable, satellite, and radio channels proliferated in Europe, the US, and other parts of the world. A large buying firm, advocates said, would have the staff and computer facilities to analyze the best media mix for each client's products in this intimidating new arena. The other development was the growth of huge conglomerates (Time Warner, Disney-ABC, News Corporation, Viacom-CBS) that owned many advertising platforms in different media industries and could potentially raise the price of time and space. Supporters of large media-buying firms contended that their hundreds of millions of dollars from multiple clients could act as a counterweight to the media firms' clout during bargaining over prices and placements.

Zenith marked a focus on standalone media-buying divisions – a focus placed by the agency-holding companies that were beginning to emerge in the UK, France, and the US. Driving the holding companies' growth was the notion that dominance in all parts of the industry could be achieved by buying a number of full-service ad agencies with worldwide networks, great creative boutiques, and allied businesses such as public relations outfits. The first agency-holding company, Interpublic, was actually founded in 1960; but the notion did not catch on until the 1980s. The 1990s saw enormous struggles for position and control over agency conglomerates, as well as over their media-buying divisions. The four dominant worldwide holding companies that exist today emerged by the early 2000s: Omnicom and Interpublic, based in New York; WPP (originally Wire and Plastic Products Plc.), based in London; and Publicis (which had absorbed the Satchis' holdings), sited in Paris. In addition to these were two firms with French pedigree, which held a particular claim to fame as buying authorities: Aegis, based by then in London; and Havas, based in Suresnes, France. These six were eventually quite successful at dominating the territory. According to a research firm that keeps track of buying-firm developments, they spent $224 billion advertising dollars worldwide in 2009 (RECMA, 2010). That year the six firms controlled about 45% of purchasing in the US advertising market; in most European countries the share reached 80% (RECMA, 2010).

The 2000s marked a period when the major buying firms began, with their quantitative audience-targeting models, to earnestly exploit the rise of the commercial Internet as a testing ground for the coming age of ubiquitous digital media. Although advertising “online” appeared during the 1980s on computer dialup services such as Prodigy, the business was marginal and ad agencies didn't consider that it had mainstream possibilities. The growth of commercial advertising on the World Wide Web with the introduction of the Netscape browser in 1994 pointed to a venue for marketers to reach millions of audience members. The second half of the 1990s marked a transition period during which publishers and various partners refined three technologies that would become the basis for the audience-marketing logic that took flight in the next decade: the banner, the interactive link, and the cookie.

The banner and the advertising-oriented link seem to have emerged together on October 26, 1994, when the popular online technology magazine Wired began to sell pictorial banners in large quantities on its new website Hotwired.¹ Soon thereafter Netscape employees Lou Montulli and John Giannadrea revolutionized advertising by creating the cookie, a small text file that a website could place on a visitor's computer. They were responding to online retailers complaints that they couldn't handle customers' multiple purchasing requests (Schwartz, 2001). Every click designed to put an item in a virtual shopping cart would appear to the online store as if it were made by a different individual. Consequently, a person would not be able to buy more than one thing at a time. Montulli and Giannadrea made the cookie with an identification code for the visitor and codes detailing the clicks that the person had carried out during the visit. The next time the person's computer accessed the website, tags on the browser would recognize the cookie. Note that the cookie could not by itself distinguish between two separate people using the same computer. That was the result of Montulli and Giannadrea's decision to have the cookie work without asking the computer user to accept or contribute information to it. There was an ominous downside to that seamless approach: by not making the computer user's permission a requirement for dropping the cookie, the two programmers were building a lack of openness at the center of the consumer's digital transactions with marketers.

During the 1990s and into the 2000s, marketing technologists developed other methods for following individuals through the digital environment. A web beacon (or tracking pixel) is a graphic on a web page or in an email message that often activates a program in order to monitor the activity of visitors – for example, what they read and for how long. A Flash cookie (technically, a locally shared object) is a collection of cookie-like data stored as a file in a user's Adobe Flash computer software; marketers sometime use it so that the data will not be lost when standard cookies are deleted. The development of the banner ad, the link, the cookie, the web beacon, and the Flash cookie helped digital divisions of media-buying firms and their technology partners to refine their digital trade through the 2000s to make it central to marketers considering advertising online. The essential approach was to emphasize that the new medium allowed for the quantitative measurability of audience activities in ways that would yield a much more accurate understanding of a client's return on investment (ROI) of its ad monies than had been possible with analog advertising vehicles such as newspapers, magazines, radio, television, and outdoor boards. Moreover, media buyers contended, it was now possible to go beyond measuring the responses of panels or samples of audiences, as had been the norm in the analog world. Now it was possible to note and store the responses of individuals via their click-like behaviors – for example, by using the mouse to activate a link, by moving a mouse to activate tracking pixels on an ad, or by pressing a button to change a channel or to choose a product on a television screen.

Initially the emphasis on quantitative measurement served a direct-marketing model of advertising. The goal was to provoke a sale or an action that would conceivably lead to a sale. The rapid rise of Google search as an advertising powerhouse, which began around 2001, was a result of an auction-based pay-per-click (PPC) revenue system that reflected this approach. Google initially carried its PPC model to the contextual advertising system that it established with sites throughout the web and in its Gmail service. In a contextual advertising network, when an advertiser bids for a keyword, the network's computers find a web page from the network's roster of sites that reflects the keyword. On the basis of the relevant context, the network serves the ad. If the visitor to the site clicks on the ad, the advertiser pays the agreed-upon amount and the network shares it with the website. Both in the advertising search and in the contextual advertising businesses, the percentage of visitors who click might be 1% or less. But, with hundreds of millions of visits, Google could still make significant amounts of money with the PPC model.

While Google executives extolled this direct-selling approach as the purest example of web results in action, many web-content providers didn't have anything like the numbers of visits enjoyed by a search engine such as Google or by a “portal” such as Yahoo. These smaller publishers preferred to sell display advertising on a “cost per thousand impressions” basis that paralleled the tradition of newspapers, magazines, television, and other analog media. The logic was that ads for companies that sell cars, financial services, and movies may not need to yield a click action to have an impact on a person's image of the product and on future purchase decisions. But this forgoing of the direct-click payment model of advertising sales didn't mean that media buyers were giving up on their insistence that the web was a more measurable platform than traditional media. Instead, media buyers and publishers advanced new ideas of how to think of the success of image ads that could be measured even as they paid on a CPM basis. Some of the notions centered on “engagement” – time spent on, or interest in, the page with the ad was an indication of the opportunity to see with it. A different way to think of the measurability of an image ad's success was to look at whether viewing an advertisement at one point led to the purchase of a product at another point – either on the web or off it. This definition of success – call it the long click – became an important reason for following individuals' activities across media, and ultimately from online media to offline retailers such as supermarkets and car dealers.

In all these cases, fierce competition for dollars led publishers to garner visitors' characteristics and to sell that information along with their engagement possibilities. Keeping people's names and email addresses off limits (and calling it anonymity), some sold segments with demographic information such as age, sex, geographic area, income and employment status they got from registration or bought from data firms. The ability to use cookies and, later, web beacons to tag audience members and to track what they viewed allowed publishers to create and offer up segments of inferred interests to advertisers, who might in turn infer purchasing interests from those segments. Advertising networks were doing the same thing, though across websites, and they and data-collection firms often “matched” their cookies with the cookies of other tracking firms, to enhance the ability of advertisers to target very specific types of individuals – and often even very specific (though still anonymous) individuals. By the late 2000s, audience-data exchanges owned by Google, Yahoo, Microsoft, Interpublic and other major players facilitated the auction of individuals with particular characteristics, often in real time. That is, it is now possible to buy the right to deliver an ad to a person with a specific profile at the precise moment at which that person loads a web page. In fact, through cookie-matching activities, an advertiser can actually buy the right to reach, on an exchange, someone whom the advertiser knew from previous contacts and was now tracking around the web.

Through these processes the audience became a focus of reconstruction for marketers and content firms. A variety of organizations emerged to help marketers find the specific audiences and audience members they wanted at the lowest prices possible, while a variety of others emerged to help publishers provide those audiences but keep prices relatively high. Media-buying firms struggled to find their place as advertising networks and media-buying platforms threatened to usurp buyers' key functions of planning the best roster on which to advertise and of bargaining for the best price. The ecosystem became denser as the amount of money advertisers spent online expanded dramatically, from around $9 billion in 2003 to around $34 billion in 2008 (Veronis Suhler Stevenson, 2009, Table 11.8). A chart circulating within the trade during 2010 (Kawaja, 2010) depicted 22 types of organizations between advertisers and publishers (see Figure 9.1). In addition to agencies with media-buying divisions (WPP, Publicis, Havas), it listed categories such as ad exchanges (Doubleclick, AdECN), ad networks (AOL, Google, Microsoft), yield optimizers (Rubicon, PubMatic), ad servers (DoubleClick, Atlas), data qualifiers (DoubleVerify), analytic specialists (Omniture, Coremerics), and research operations (comScore, Nielsen, Quantcast). All the companies represented in these categories have the following operations as their core aims: assembling data about the audience (or consumers, visitors, targets, or users, as audience members are variously called); trading the data about them; trading access to the audience members; creating specialized display ads and videos for the targets; serving specialized ads to the targets; and/or evaluating the success of those activities.

Media Buying and the Exercise of Power

That advertisers can now buy the right to serve messages to, say, 26-year-old Southern US fans of the film The Princess Bride may seem like a trivial concern. But this capability, highlighted in press articles about digital privacy (see, e.g., Angwin, 2010), only scratches the surface of what firms can learn about individuals – and about what they can do with what they learn. Here are sketches of three ways in which the maturing digital-industry logic increasingly encourages profiling people without their knowledge, shares these profiles across marketers and websites, and narrows audience options regarding not just advertising but prices, news, and entertainment.

(1) Individual marketers construct a flow of information and inferences about individuals and increasingly tailor ads and offers to them. The impulse guiding this approach is encapsulated in a Powerpoint deck that Publicis' MediaVest buying operation presented to its clients during 2010. Headlined “Why We Are Betting on Ad Exchanges,” the first slide offered the basic explanation for MediaVest's decision to put its energies into the new approach to advertising spending: “Key benefit: Buy only the impressions that match.” Two columns of text then elaborated the point, which was also illustrated by a series of pictures descending with them. One column highlighted the key chain of thinking about ad exchanges: “Insight/Media/Technology/No Waste.” The other column elaborated on the flow of reasoning in the following way: “Leverage our own data to create audience segments → Access millions of consumers through open ad impressions → Exchange allows all impressions to be ‘filtered’ → Buy only the impressions that match our segment.” The slide suggested that marketers would be able to reach only the people who count to them. MediaVest would create target segments on the basis of its clients' data about best customers. It would then bid, in the exchanges, for the right to reach people who fit those profiles. They would get the client's messages, and the audience reached would be free of “waste” – the term used for the population the client didn't care to reach.

Figure 9.1 Display LUMAscape © LUMA Partners LLC 2011.

The approach is by no means confined to MediaVest. It is becoming a standard operating procedure among media buyers in the big six firms, as well as in many of their smaller competitors. Marketers are increasingly using databases to predict whether they should consider particular Americans as targets or as waste. Those considered waste are ignored or shunted to other products, which the marketers deem more relevant for them. Those considered targets are further evaluated according to demographics, beliefs and lifestyle data about them that companies store and trade. They receive different messages and possibly discounts, depending on the profiles.

Advertisers and publishers point out that much of the cookie-connected information they use is “anonymous” – that is, not linked at the moment of use to the person's name, postal address, or email address. Yet, if a company can follow an individual's behavior in the digital environment – and that includes the mobile phone and, potentially, the television set – its claim that the person is anonymous is meaningless. That is particularly true when firms intermittently add offline information to the online data and then simply strip the name and address, to make it anonymous.

For Ford Motor Company, there is no question that targeted personalization – sometimes anonymous, sometimes not – is central to marketing strategy. Reflecting this idea, Andy Pratkin, the digital director of WPP's Team Detroit agency, noted in an interview that his fundamental concern in reaching customers is with knowing how his prospective targets learn, how their perceptions are formed. He added: “If we can fit into that dynamic, we can fit into her” (Pratkin, 2010). Pratkin argued that the digital environment allows for an individual to be followed along a gauntlet of brand-related mind-sets, from awareness to initial attitude to various attitude shifts. “It's kind of like dating,” he said. Consider just two of the ways in which Team Detroit cultivated online audiences for the Ford Motor Company's advertisements during 2010:

• It purchased ads on many automotive sites and planted Ford cookies and beacons in the computers of visitors to the pages where the ads appeared. The technology allowed Ford to serve individuals different messages and photos, depending on what their clicks suggested to Ford about where they were in the car-purchase funnel. “We do a fair amount of tagging,” said Andy Pratkin (2010).

  If people are exposed to our ad, we study their behavior, and if they come to our site, then we retarget them and try to entice them back [. . .] If you go to [the] Kelly Blue Book [website], we serve an ad. We'll know if you didn't do anything. Next time, we'll serve you a different ad. You go to our site, and if you do something and you go off our site [to one of Ford's advertising networks], we serve you other ads.

  The technology often assembled the advertising automatically, on the fly, to match what cookie data said about the person's car-searching routines with the previous commercial messages that had been served to the individual.

• In other Internet buys, Team Detroit varied its ads to people on the basis of their ages, incomes, geographic locations, and various social behaviors, as well as on the basis of inferences from categories based on these data (“soccer moms,” for example) that suggested they would purchase particular vehicles or would be persuaded in certain ways. In addition, the agency presented ads to the friends of people on Facebook who fit profiles of being in the market for particular types of cars. “On Facebook, you take friends into account,” said creative executive vice president Scott Lang in an interview (2010). “So-and-so liked this; you will too. People find that creepy in the beginning, but [. . .] they slowly get used to it.”

While Ford uses data and digital-targeting aggressively, Next Jump goes even further. This smaller but influential firm runs employee discount and reward programs on behalf of 90,000 corporations, organizations and club-like organizations (often called affinity groups) that reach more than 100 million consumers. The low profile results from Next Jump's desire to stand in the background, as a facilitator of deals. The capability it offers prospective clients on its modest website is certainly familiar in the digital age: “Create your own targeted ads on the Next Jump network [. . .] Promote your offers to interested users [. . .] Track marketing performance through insightful analytics [. . .] Discover and reward your most influential customers” (Next Jump, 2010).

How Next Jump does that is the secret sauce that founder and CEO (chief executive officer) Charlie Kim says augurs a new future for advertising. The business is based on the proposition that the best way to advertise is to present lower prices specifically to individuals about whom statistical calculations suggest that they would be the best customers to reach with a deal. According to Kim, Next Jump's conversion rate on product offers (that is, the ratio of offers to purchases) is 11 to 1, compared to 1,000 to 1 or worse, which goes for typical Internet ad-conversion rates. But not every advertiser can get the data to target individuals so carefully. What Next Jump has done was to insinuate itself directly into the fabrics of Fortune 500 companies and other larger firms by running the online purchasing programs that those firms set up as perks for their employees. Those firms pay Next Jump for its work on a “per employee” basis, but Next Jump seems to derive a lot more money from the fees merchants pay every time someone buys a product.

Next Jump therefore has a vested interest in increasing its purchases. Because the company operates discount programs for roughly one third of all US corporate employees, “it is considered a non-traditional benefits provider and gets updated weekly on the employment status of 30 million workers (who also happen to be consumers). It gets part of the employee record, including things like name, address, employment status, home and work address, marital status, and sometimes even job title or salary grade” (Schonfeld, 2010). To that information and to inferences about it (such as salary grade), Next Jump adds transactional data from the firms it deals with, as well as from credit companies. It then overlays all that with information it collects through the firms' human relations departments and through employees about what people want and what they will pay for. With all that knowledge, Next Jump can make predictions about who should get what product email offer at what price. It also generates a “UserRank” score for every employee, on the basis of how many purchases a person has made and how much he or she has spent.

“Shopping and advertising has [sic] always been the same to us,” Kim noted in 2010. His goal is to separate consumers to the extent that the conversion rate (which in 2008 was 100 to 1) will get down to 3 to 1. He sees it as a statistical issue. Of his 225 employees, 150 are engineers. One analyst of the company noted the extension of his work: “If Kim keeps perfecting his shopping algorithms, you may never shop the same way again – and you won't even know that you are doing anything differently” (Schonfeld, 2010).

(2) Marketers, data providers, and websites create widening profilesfor people that may affect the choices they receive from marketers at various locations. The individual-level data that Next Jump uses in setting differential-pricing activities for its clients do not seem to leave its servers. Increasingly, though, the blending of conclusions about consumers' online behavior with gathered (or purchased) information about them doesn't stop at particular brands. To the contrary, the business of discriminating digitally is leading many marketers to a small number of firms that sell various sorts of information about online customers and potential customers. These agencies, in turn, get their data from a small number of primary sources. The data collectors match what they know about people online with information they buy offline. They then anonymize the cookies; the same data may be associated with the (anonymous) person in many cookies used throughout the web.

It is through the use of these cross-pollinating organizations that narrowed options and social discrimination widen their impact. The period during which the profiles exist is widening as well. Individual cookies may have a life of days only, because the people they track delete them from their computers. Digital publishers and marketers have, however, developed various techniques to keep a growing amount of information about anonymous individuals even after their standard cookies have disappeared. These approaches, plus the matching of cookies to share information gleaned in different ways, mean that the profiles that publishers and marketers increasingly share broadly exist for an increasing amount of time.

Acxiom, a top US marketing-communication agency, is a good place to begin exploring the building blocks of information and how they travel across advertisers. The company says that it help clients “acquire, retain, and grow loyal (and profitable) relationships” in the digital media as well, especially via email, banner, search, website optimization, and mobile (Acxiom, 2008). Acxiom's cross-advertiser reach is prodigious. It says the client list includes 9 of the top 10 automotive companies, 12 of the top 15 credit card issuers, 7 of the top 10 retail banks, 9 of the top 10 telecom/media companies, 7 of the top 10 retailers, 9 of the top 10 automotive manufacturers, 6 of the top 8 brokerage firms, 3 of the top 5 pharmaceutical manufacturers, 2 of the top 5 life/health insurance providers, 8 of the top 10 property and casualty insurers, 2 of the top 3 lodging companies, and 2 of the top 3 gaming companies (Acxiom, 2010). Acxiom's use and analysis of customer data is central to serving these clients. Not only does it help them analyze the information they hold about their individual customers, it offers lots more individual information from a variety of public and private databases in order to help them discover the value of each person and the selling proposition that would be best for him or her.

A role the company emphasizes throughout its website involves helping a client decide which consumers are not worth targeting. This is called “contact suppression,” a practice based on making assessments about the “risk profile” of individuals for certain industries. Here is how Tom Mangan, the firm's senior vice president of consulting services, described Acxiom's contributions at a shareholders meeting (Acxiom, 2008):

The facts and generalizations that Acxiom imputes to individuals have the potential to travel broadly, as they are used by clients in different industries, for different advertising campaigns and pricing offers, across different analog and digital media. Many other firms gather online and offline data about individuals, often with the help of publishers who sell data about their audiences. The data firms aggregate this information about individuals into digital cookies and license their use to marketers. For example:

• eXelate is a leading targeting exchange firm with the motto “MAKING BIG DATA WORK FOR ONLINE ADVERTISERS” (eXelate, 2012). It determines a consumer's age, sex, ethnicity, marital status, and profession by partnering with websites to scour website registration data. It also tracks consumer activities online to note, for example, which consumers are in the market to buy a car or are fitness buffs, on the basis of their Internet searches and of the sites they frequent. It sells these packages of information about individuals as cookie data, so advertisers can target them.
• Rapleaf is a firm claiming to help marketers “customize your customers' experience.” To do that, it gleans data from individual users of blogs, Internet forums, and social networks such as Facebook and Twitter. It uses ad exchanges to sell the ability to reach those individual cookies. The company says that it has “data on 900+ million records, 400+ million consumers, [and] 52+ billion friend connections” (Rapleaf, 2010).
• 33across analyzes people's comments, activities, backgrounds, and connections on social networks in order to pull out those who fit profiles that advertisers want to reach. The firm finds people who directly fit all the advertisers' criteria. It also carries out statistical analyses of those people and of the firms' customers, to find “lookalikes” who would seem to be good prospects. In addition, 33across offers its clients “high degree interest” connections. These are individuals who are attractive because they are friends or friends of friends of active shoppers (and so might already be influenced) and have many friends themselves (so they may influence others). People who fall into different attractive profiles would see different campaigns with potentially different products and offers.
• Lotame's deals with a “multitude of social networks” and other publisher sites lead it to collect “over 240 billion monthly [. . .] interests, actions and attributes” in order to “create precise audiences and derive insights from our superior knowledge of human behavior” (Lotame, 2010). For the individuals it comes across with, the firm monitors and stores information about demographics (age, gender, geography, household income, and education level), interests (declared to the site and undeclared), actions (what people create, rate, send, share, upload, comment, edit, watch, “and more”), media use (online – which can include videos, widgets, music, forums, blogs, and photos), recency and frequency (how often and when individuals express interests and/or actions), interactions (how people interact with content and ads, including clicks, time spent, and videos completed), and sentiment and exposure (what individuals say, what they read, when and how they say and read it). This interrogation of people's creative activities in the digital realm leads the company to interact with particular individuals in a way that is “based on what they talk about, the sentiment they've expressed in discussions, or the content or conversations they've read or participated in.” It also leads Lotame to tailor display ads and commercials for the targeted individuals. In turn, the firm monitors the results and adds its analysis to the data, in order to further “learn what demographics, interests, attributes, and actions drive a campaign's success based on goals” (Lotame, 2010). This process continues with new data, new people, and new advertisers.

(3) In tune with the personalization in advertising, publishers are beginning to personalize editorial matter based on profiles they create and profiles they can purchase. One incentive publishers have for personalization is to make their material stand out to advertisers, at a time when media buyers think less of the place where they are posting the ad than of their ability to purchase impressions of the right type of individual – or even of the exact individual – wherever that person shows up in the digital universe. Publishing executives reason that, if they serve tailored content to visitors, then people will stay longer, view more commercial messages, and even be prompted to click on more ads, because of the relevance that both ads and editorial matter combine to create, increasingly in real time. Edwin Wong, director of market research for Yahoo Search, suggested another reason for content personalization in an interview. He said it allows the media firms and their advertisers to learn increasing amounts about individuals' interests and their responses to those interests. That, in turn, could inform the creation of profiles that advertisers would use to encourage clicks and other engagements (Wong, 2010).

Despite media buyers' enthusiasm for tailored editorial matter, a number of logjams have hindered its implementation. Executives from major news companies said in interviews that until recently their firms have been loath to personalize their presentations for audiences, in a long-held belief that the best content “is based on serendipity,” as a Time Inc executive put it. He also suggested a worry that personalization could harm the company by startling people about the knowledge firms have about them. “If I saw that the magazine editor said, ‘Kirk, we know you're in debt up to your eyeballs. Here are articles that can help you,’ I might well freak out” (McDonald, 2010).

As competition heats up, however, that belief is changing. Time Inc and other firms are searching for ways to justify the quiet customization of news on the basis of their generalizations about a person's interests and background. In the meantime, smaller firms have already started experimenting. A firm called The Daily Me personalizes news and sports presentations on the online sites of more than a dozen newspapers. Gerald Hauser, its founder and CEO, presented an actual example: a Boston Globe reader visits the Dallas Morning News site because of an article noted on a blog or search engine. Both the Globe and Morning News are Daily Me clients, and so its cookie notes the anonymous individual at the Morning News site. Because The Daily Me's cookie contains the information that the person read a lot about soccer on the Globe sports section, it tells the Dallas Morning News to serve him soccer stories. Moreover, when an ad is served along with the story, its text and photos are arranged instantly to include soccer terminology and photos as part of the advertising pitch. A basketball fan receiving an ad for the same product will get language and photos that call out to people with hoop interests (Hauser, 2011).

While it seems likely that text- and photo-based personalization will develop quickly now that it has strong publisher rationale and advertiser support, personalized audiovisual content is likely to be harder to implement because of cost. It is already possible today to change aspects of television programming and games on the basis of social backgrounds. Visible World can change the look of characters and products in programs on the fly, according to data in a household's set-top box. Knowledgeable observers note, however, that the cost of carrying out even these basic personalization activities on television in the near future will be too steep for advertisers to support them. In-game personalization of this sort – based on demographic and behavioral conclusions about the player – is also a technical possibility (it already exists with ads), but it is still not a major talking point among producers or marketers. Much more likely is the presence, in the next few years, of an “intelligent navigator” keyed to the characteristics of the person or household. An intelligent navigator is a guide that will appear on a person's television set when it connects to the vast viewing lode offered from Internet programming. This so-called Internet-protocol television (IPTV) will allow the reception of thousands of individual shows at any time. The flood of options will encourage software that suggests a priority of possibilities for a household or for particular individuals in the household.

A major attraction for a “navigator” firm will be the opportunity to make money from commercials at the side of the listings. The navigation firm will likely charge substantially for marketers to plug into the profiles it develops about individuals on the basis of their viewing of programs and commercials. Advertisers will also pay a premium to intelligent-navigator firms to serve interactive ads to big-screen home television sets on the basis of the knowledge of individuals that the advertisers gathered on other websites, and perhaps in stores. A partnership between Visible World and Interpublic's Cadreon advertising exchange seems to be preparing for just this scenario. In 2010 Cadreon tracked and identified web users who appeared to be researching new car purchases on the web. It then used Visible World's personalization platform on cable TV systems to place appropriate commercials in front of those same individuals. Cadreon's goal, as it moves forward, is to increase the ability to personalize commercials on the strength of inferences made from more and more data. CEO Brendan Moorcroft told AdWeek that Visible World “brings an infrastructure for ad serving to TV not unlike what Atlas or DoubleClick do” for the Internet. “It allows us to apply intelligence for TV buying like you do for the Internet.” And if it were unclear to observers that people's reputations behind the screen would be the drivers of commercial messages, he added: “For the first time you'll see real scale [in the targeted space] with hundreds of ads seen by millions of people, all determined by algorithms and data as opposed to human instinct” (McClellan, 2010).

The Long Click, Reputation, and Audience Power

The Cadreon case is an example of the way in which targeting and personalization technologies developed for the World Wide Web are migrating to other media arenas. Brick and mortar retailers are beginning to build digital media into the very heart of their sales activities. Supermarkets are involved in various experiments in which knowledge of the shopper's identity (via a frequent-shopper card, for example) activates a “smart” shopping cart, which displays discounts and ads that are based upon profiles of the person's shopping history (see, e.g., Turow, 2006). Location-aware applications built in people's mobile devices are encouraging a different sort of profiling, this time in the interest of presenting individuals with discounts or other prizes for visiting nearby restaurants or other stores (Clifford, 2010).

Because of the industry thinking that enshrines the long click as an ideal measure of success, the link connecting the traditionally offline and online, as well as the domestic, the outdoor, and the in-store is becoming a reality. Already research firms such as comScore and Nielsen are using their huge panels to track the impact of a person's encounter with an online ad on that person's purchase activities. They sell to marketers data about the types of people who are likely to complete the long click. Some firms are forgoing this statistical analysis in order to trace all the individuals who come into contact with them. A major auto manufacturer has developed tools to track the ways particular interactions with its ads lead to particular ways those people interact with the firm's sites and, in turn, predict whether they come into the dealership and with what result. The predictive profiles associated with different individuals affect the ways the auto company interacts with them online and in the brick and mortar store.²

When stories such as these make it into the public eye, the discourse inevitably turns on their implications for privacy. Advocacy organizations, members of Congress, editorial writers, and members of the public have excoriated companies that track behavior in ways that are not transparent. Social battles around the meaning of personal, the helpfulness of privacy policies and icons, the utility of opt-in and opt-out choices, and the value of transparency versus regulation take up much of the discourse. Almost ignored in the literature are the implications of tracking and personalization for the different views of the world that individuals receive from marketers and from the publisher. The process of tailoring content has begun only recently, but it is growing quickly. As the preceding pages suggest, tailored advertising and discount coupons have taken the lead, but the lessons from that are now starting to be applied to information, news, and entertainment as well. Moreover, these personalized engines of content may well spread, with their personalized profiles, across digital devices and domestic, outdoor, and in-store venues. The upshot: people may well be surrounded by a symbolic environment created from categories about them that a wide range of marketers and publishers share but about which the individuals constructed through those data have no knowledge.

In considering the future of digital targeting, it is useful to draw a distinction between profiles and reputations. Profiles are descriptions of individuals that lack comparative rankings of desirability. Marketers and publishers then map their sense of attraction to them. If, for example, marketers want 18–24-year-old women who like vampire movies, they will consider profiles of women aged 35–50 unattractive. Nothing in the information about the 35–50-year-old women, however, makes them inherently unattractive. As the Next Jump and auto-dealer examples suggest, though, a next logical step in digital marketing is to build comparative evaluations of individuals into clusters of descriptions that are based on actions such as their statistical record of spending money, of giving back a product, and of telling friends about products. With such an approach, profiles become reputations. That is, they become clusters of data that have, built into them, a sense of the comparative utility of individuals to marketers (and, by extension, to media firms) along a range of commercially driven dimensions and contexts.

The movement of the advertising industry from profiles to reputations seems clear in the media-buying system's logic, as this is expressed through executives' discussions, their companies' behaviors, and the personalization technologies that are emerging. The concern here is not with whether the evaluation, separation, and trading of individuals in an iterative way actually increases the advertisers' bottom line. It is with the impact of the advertisers' patronage demands and with the technologies through which they are expressed to audiences and in the media in the twenty-first century. One consequence of media buying is that data firms and marketing agencies have learned to use the creative activities of independent bloggers and of social-media participants in order to concoct marketing categories for the purposes of social discrimination. Ironically, what writers correctly extol as examples of individual initiatives are also a part of the efforts through which the digital media system is preparing to present different people with different opportunities and world views across a broad gamut of platforms. David Croteau pointed out in 2006 that we know little about the impact of user-generated content on the new media landscape (Croteau, 2006, p. 340). To this observation it should be added that we know little – and we theorize little – about the impact of the institutional forces surreptitiously shaping the landscapes on which user-generated activities take place. How, when, and with what impact do the two layers of the digital world interconnect? It is a question that warrants systematic research.

Early twentieth-century sociologists from the Chicago School would undoubtedly see the market-driven social discriminations of the contemporary advertising industry as derailing their belief that media can encourage greater opportunities for democratic argumentation across broad populations. Dewey, Cooley, and Park might find some hope in the observation that the breadth, depth, nature, and consistency of the discriminatory processes will depend to some extent on the resistance that marketers and publishers perceive from advocacy organizations, legislators, and citizens. Unfortunately, public and academic discussions about the long-term implications of advertisers' new approaches to audiences are hard to find. For members of the Chicago School, democratic discussion about such critical topics that define society would best be based on universal education and access to information. One reason is that the media-buying system is difficult for outsiders to understand and its activities are largely and quite purposefully hidden from view. Nevertheless, because the interconnections of media buying, digital-content production, and audience construction raise major social issues at the core of the twenty-first century's central media system, this is a topic that academics should help pull into the spotlight.

NOTES

1 Without evidence, a Wikipedia entry notes that the website Global Network Navigator (GNN) sold the first clickable web ad – later called a banner – on its home page in 1993 to a law firm with a Silicon Valley office. It claims that the Hotwired site was the first to sell clickable ads in large quantities. See “Web Banner,” Wikipedia (English edition), accessed January 31, 2010.

2 The interviewee wanted himself and his firm to be anonymous.

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FURTHER READING

Gerbner, G., Gross, L., Signiorelli, N., Morgan, M., & Jackson-Beeck, M. J. (1979). The demonstration of power. Journal of Communication, 29(3), September, 177–196.

Sunstein, C. R. (2001). Republic.com. Princeton, NJ: Princeton University Press.