political advertising research paper

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11 Political Advertising

Timothy W. Fallis is a doctoral candidate at the University of Pennsylvania’s Annenberg School for Communication, where he also earned his M.A. He has written on political advertising, political discourse, and on how religious practice is being integrated into the digital forum.

• Published: 01 May 2014
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Within the field of political communication, the study of political advertising has attempted to relate its content to posited effects. Most of this inquiry has been conducted using one or some combination of three methods: survey, experiment, and content analysis. As a result, a picture of what political advertising does and why and how it does it has emerged. This chapter synthesizes findings by suggesting that differences in spending on political advertising can affect vote choice; that advertising’s effect on vote choice are mediated by factors that include party affiliation, political knowledge and involvement, and media exposure; and that such advertising has a significant effect on the political process. “Negative” advertising is a messaging structure that affects the political process for ill and for good; it can both decrease and increase voter turnout but is misunderstood when conflated with informative “attack” and “contrast” advertising.

In the more than two centuries since the country’s first contested election, the technology of political advertising has changed, but the attack and advocacy strategies have remained much the same. Attack content vilifies; advocacy venerates. Marshaling minimal if any evidence, the makers of political propaganda identify their candidate with esteemed individuals and popular sentiments, all the while denigrating their rivals. In short, from the Republic’s earliest days, sloganeering, not substance, has been the stuff of politics in the United States (see Jamieson, 1984 ).

Within the field of political communication, the study of political advertising has attempted to relate its content to posited effects. Most of this inquiry has been conducted using one (or some combination) of three methods: survey, experiment, and content analysis. As a result, a picture of what political advertising does and why and how it does it has emerged. This chapter synthesizes findings by outlining what we know about the content of political ads and suggesting that differences in spending on political advertising can affect vote choice, advertising’s effects on vote choice are mediated by very specific factors, and that, under some circumstances, political advertising can affect electoral outcome.

The Content of Political Ads

Scholars affix varying labels to the content of political ads. Where Geer divides the ad world into appeals that raise “doubts about the opposition (i.e., negative) or [state] why the candidate is worthy of your vote (i.e., positive)” without a “middle category” ( Geer, 2006 ), Jamieson, Waldman and Sherr (2000) parse the terrain into attack, contrast, and advocacy, whereas Freedman, Wood, and Lawton (1999) segment attack into “personal” and “issue” appeals. The Jamieson, Waldman, and Sherr (2010) content analysis finds that conflating contrast with negative overstates the amount of deceptive advertising; as a result, they argue, we falsely criticize candidates when their discourse is actually informative and accountable. Geer’s content analysis, which treats as “negative” ads that Jamieson et al. would call “contrast,” finds that negative advertising often offers strong, substantive information that is useful to voters. The difference between the Jamieson et al. and Geer results is largely a result of varying definition and data sets: Jamieson et al. included 5-minute ads and excluded ads that never aired.

William Benoit’s alternative typology categorizes ads as acclaiming (emphasizing good reasons voters should lend their support), attacking (focusing on the opponent’s faults as reasons why he or she should be shunned by voters), or defending (countering the accusations leveled by the candidate’s opponent) ( Benoit, Blaney, and Pier, 1998 ). Results from this content-analytic approach to ads of the 1980 through 1996 presidential campaigns show Democrats more likely to acclaim than to attack and Republicans tending to do the opposite. Incumbents are also more likely to take advantage of their record and acclaim rather than attack, while, without a record to reference, challengers are more likely to attack than to acclaim; for all four groups, ads that defend are rare ( Benoit, 2001 ; Benoit, Blaney, and Pier, 1998 ). A content analysis of 584 spots featured in the year 2000 presidential, gubernatorial, congressional, and local elections found that 67 percent acclaimed, 32 percent attacked, and only 1 percent defended the sponsor against attack ( Airne and Benoit, 2005 ). Fearful of alienating potential supporters, candidates do not usually include obvious cues about party affiliation in political advertisements ( Vavreck, 2001 ).

Using a definition closer to Geer’s, another study that parsed political advertising into positive or negative ads (the latter defined as those “intended to make the opposing candidate look bad by attacking personal characteristic, political issues, or affiliated party”) found that negative and positive spots tend to emphasize different issues. Positive ones are more often informal in style, use a more cognitive (i.e., “ads [that] directed viewers to think, reason, and consider”) vocabulary, highlight social issues and achievement, and seek to contrast the present with a potentially brighter future. Negative and even mixed-format ads tend to focus on financial issues, evoke a more sensory than cognitive reception, and laud the past while expressing anger about the present ( Gunsch, Brownlow, Haynes, and Mabe, 2000 ).

Some argue that constructive attack ads are valuable and may encourage voters to exercise their franchise, whereas ads that merely disparage candidates or their issues or engage in what are perceived to be inaccurate or unfair assertions are perceived as unhelpful ( Jamieson, 2000 ) and may lead voters to feel that their ballot is a useless gesture and therefore to stay home ( Kahn and Kenney, 1999 ; Gronbeck, 1992 ).

An “attack” advertisement is not necessarily “negative” or “dirty,” and some argue (see Jamieson, Waldman, and Sherr, 2000 ) that conflating the terms, as many studies on political advertising do, obscures the important distinctions between legitimate and illegitimate attack. Further, it is important to note that in the presidential general election campaigns from 1952 to 1996, deception was no less likely in advocacy and self-promotional ads than it was in attack ads ( Jamieson, Waldman, and Sherr, 2000 ). Richardson (2001) also argues that because studies that examine negative advertising are conceptualizing it poorly, they ask the wrong questions: “In short, negativity has been defined in ways that are too broad … insufficiently holistic, too pejorative, and ultimately irrelevant in a constitutional framework grounded on free speech and retrospective accountability.”

Political Advertising Effects

Like political communication in general, political ads are more likely to reinforce existing beliefs than to change attitudes ( Ansolabehere and Iyengar, 1995 ). However they can affect individual voting decisions ( Valentino, Hutchings, and Williams, 2004 ) as well as vote share ( Althaus, Nardulli, and Shaw, 2002 ), and in close contests may prove decisive ( Shaw, 2006 ; Johnston, Hagen, and Jamieson, 2004 ).

Differences in Spending

Although the effect is not inevitable, spending more than an opponent tends to carry electoral advantages. Bartels, for example, finds that in five instances the Republican presidential candidates’ “popular vote margin was at least four points larger than it would have been, and in two cases—1968 and 2000—Republican candidates won close elections that they very probably would have lost had they been unable to outspend incumbent Democratic vice presidents” (2008, 122–3). Although they disagree about the size of the effect, scholars have also found that spending more on ads than an opponent translates into vote choice ( Shaw, 1999 ; Huber and Arceneaux, 2007 ; Johnston, Hagen, and Jamieson, 2004 ).

Increased spending on political advertising increases awareness of a candidate, which in the case of disparities in spending may change the outcome of an election though an increased likelihood of voting for that candidate (see for example Goldstein and Freedman, 2000 ). Johnston, Hagen, and Jamieson (2004) demonstrate voters’ responsiveness to differences in the level and content of political advertising in the 2000 presidential election and attribute Bush’s win in the electoral college in part to the fact that the “ad signal became decisively unbalanced” in the battleground in the final weeks of the campaign (13). Combining data from the Annenberg National Election Survey with a reconstruction of the 2008 presidential campaign, Kenski, Hardy, and Jamieson (2010) showed that by outspending McCain on ads, the Democrats affected pro-Obama vote intentions. In addition, the fact that the Obama campaign had enough money to pay for all of his advertising (rather than having to partly rely on the Democratic Party or other advocacy groups) allowed it to control and focus its message for maximum effect ( Franz and Ridout, 2010 ).

Duration of Effect

The suasive effect of political advertising is of limited duration. A 2006 field experiment—involving the randomized placement of $2 million of real advertising for Rick Perry’s Texas gubernatorial re-election campaign coupled with extensive daily tracking interviews—showed that TV advertising had a strong vote-shift effect within one week of audience exposure, a smaller/equivocal effect in the second week, and no effect at all by the third week ( Gerber, Gimpel, Green, and Shaw, 2011 ). Similarly using National Annenberg Election Survey data from 2000, Hill et al. (2008 ; see also Hill et al., 2013 ) showed that the effect of any specific ad on vote preference disappeared within a week with long-term effects evident only in “the most politically aware voters.” This finding suggests that a priming model, wherein the message temporarily weights the considerations that inform a voter’s response to a vote choice—rather than an online processing model, where new information affects an opinion even after the instigating information is forgotten—may account for the voter learning effects of political advertising.

The reliance on self-reports of intention to vote is a problematic aspect of research looking into the relationship between political advertising and actual ballot choices. A variety of methodologies, including surveys, focus groups, content analyses, and lab experiments, have been used in this research. However, all ask voters their intention to vote. As Vavreck (2007) points out, this is a problem for a number of reasons, among them are voters not carrying through with their stated intention, and a range of factors that may inspire respondents to respond dishonestly. This same concern casts doubt on whether we know whether political advertising is successful at accomplishing its primary goal, namely winning votes for its sponsors ( Goldstein and Ridout, 2004 ).

Effects on Turnout

Scholars differ on whether negative political advertising affects voter turnout, viewers’ political efficacy, and viewer cynicism about government. Those finding suppression of turnout include Ansolabehere, Iyengar, Simon, and Valentino (1994) , whose experimental study correlated exposure to negative ads with a weakened sense of political efficacy. They argued that such exposure creates more cynicism in government and weakens the intention to vote. Their subsequent work concluded that negative advertising suppresses turnout by driving away independents and pushing others toward party extremes ( Ansolabehere and Iyengar, 1995 ), and also confirmed that political consultants know this and deploy negative ads for this purpose (see also Diamond and Bates, 1984 ). An even larger study suggested that negative advertising results in voter suppression ( Ansolabehere, Iyengar, and Simon, 1999 ).

Other studies have arrived at a different conclusion. Although viewers report that they do not like negative political advertisements generally and dislike them more than they do positive ads (in truth, they don’t like ads at all except to the extent that they subsidize television programming [ Mittal 1994] ), some research has shown that attack spots do not decrease voter turnout. Meirick and Nisbett (2011) show that while negative ads lower viewer intention to vote for the candidate the ad supports, overall voting is not reduced. Other studies show that while negative advertising is not without effect, it does not reduce the likelihood of voting ( Wattenberg and Brians, 1999 ; Finkel and Geer, 1998 ; Goldstein, 1997 ; Clinton and Lapinski, 2004 ; Krasno and Green, 2008 ; Garramone, Atkin, Pinkleton, and Cole, 1990 ; Franz, Freedman, Goldstein, and Ridout, 2008 ).

Indeed some argue that negative ads may increase voter turnout. Phillips, Urbany, and Reynolds (2007) agree that although viewers dislike negative ads, they increase one’s likelihood of voting for one’s preferred candidate; Freedman and Goldstein (1999) also found that negative advertising increases voter turnout (also see Wattenberg and Brians, 1999 ; Goldstein and Freedman, 2002 ). The seemingly contradictory research on the effects of negative ads on turnout may be explained by the varying definitions involved in the competing studies- or may be a function of the timing of exposure to attack. So for example, Krupnikov finds that “it is not negativity in general that has an effect on turnout—but negativity under two specific conditions: 1) negativity after a selection and 2) negativity about an individual’s selected candidate” ( Krupnikov, 2011 , 805). A meta-analysis by Allen and Burrell (2002) offered cautious support for the conclusions that “negative information produces a larger effect on opinion formation when compared to positive information, whether for a position … or a candidate… .” Two large meta-analyses report that although attack is more memorable and does tend to stimulate more knowledge, negative advertising is no more effective at yielding votes for the sponsoring party than are positive ads. Both studies found that negative advertising has no particularly deleterious effect on political systems and does not suppress turnout ( Lau, Sigelman, Heldman, and Babbitt, 1999 ; Lau, Sigelman, and Rovner, 2007 ).

Effects on Voter Cynicism

The relationship between negative advertising and cynicism is also unclear. Tedesco (2002) found that, in a 2000 Senate campaign, exposure to political attack ads expressing negative emotions predicted overall voter cynicism; those ads that intentionally elicit fear (of the opposing candidate or his party, the economy, the world) breed such cynicism especially. Other research has found that “negative” ads (defined as “a one-sided attack designed to draw attention to the target’s weaknesses such as character flaws, voting record, public misstatements, broken promises, and the like”) are indeed less useful for decision making and tend to create disgust with politics but do not affect cynicism, efficacy, or apathy ( Pinkleton, Um, and Austin, 2002 ). Others have found that “negative” advertising does not lower trust in government ( Jackson, Mondak, and Huckfeldt, 2009 ; Martinez and Delegal, 1990 ); however, viewers who already harbor lower levels of such trust do tend to be more affected by negative ads.

Voter Learning

Because political ads contain a substantial amount of issue information ( Kaid and Johnston, 1991 ), it is unsurprising that exposure to them increases voter knowledge about candidate issue positions ( Patterson and McClure, 1976 ; Just, Crigler, and Wallach, 1990 ) and prompts issue-based assessments of candidates ( Ansolabehere and Iyengar, 1995 ; Brians and Wattenberg, 1996 ). Political ads can also spread inaccurate information ( Kenski, Hardy, and Jamieson, 2010 , 281–283).

Emotional Appeals

A 1990 survey ( Perloff and Kinsey, 1992 ) of political consultants found that they believe that emotional appeals characterize the most effective political ads. Although cognition and emotion are not readily separable, the effects of political advertising are magnified when it generates an emotional response such as enthusiasm, fear, or anger. Emotion focuses attention on certain aspects of the advertisement and may affect the way the information presented in the ad is processed by the viewer ( Lang, 1991 ). A 1990 experiment by Kaid, Leland, and Whitney found that ads run by George Bush in the 1988 election helped that candidate, while the ads of his opponent Michael Dukakis largely did not; the difference was attributed to an emotional response generated by the Bush ads that the Dukakis pieces failed to elicit ( Kaid, Leland, and Whitney, 1992 ). The emotional appeals in ads are able under some circumstances to affect participation and vote choice ( Brader, 2005 ).

Contrastive Ads

A survey conducted by Jamieson (2000) found that the American electorate considers contrast ads (those wherein a candidate makes claims both favorable to his or her own candidacy and critical of his or her opponent) more responsible and useful for making voting decisions than they do attack ads, and much less of a turn-off to the political process. Comparative political advertising elicits more viewer involvement with the message, and hence more processing activity; an experimental study ( Muehling, Stoltman, and Grossbart, 1990 ) found that viewers also considered comparative ads more relevant, paid more attention to them, and were better able to elaborate on and recall them than other types of ads (see also Putrevu and Lord, 1994 ). Comparative ads also produce less criticism of the ad source (backlash), prompt more support arguments, and are viewed more favorably than attack ads ( Meirick, 2002 ). In a content analysis of presidential general election ads from 1952 through 1996, Jamieson, Waldman, and Sherr (2000) found that comparative advertising is the one most likely to contain the information needed to make informed voting decisions.

Trait Effects

Although it is impossible to completely disentangle assessments of a candidate’s character or traits from assessment of his or her stands on issues, scholars have drawn general distinctions among the types of ads dominated by one form of claim rather than the other. Trait assessments provide voters with an easily accessible heuristic allowing them to elicit predictions about the future behavior of a candidate if she or he is elected ( Hardy, forthcoming ). Ad-driven trait assessments can affect vote intention ( Johnston, Hagen, and Jamieson, 2004 ).

Issue vs. Character

Experimental data from 1989 show that political advertisements that focus on policy or governance issues rather than the personal qualities of candidates tend to create a more positive attitude toward the ad itself, the sponsor of the ad, and the issue highlighted; they also increase the likelihood of voting ( Thorson, Christ, and Caywood, 1991 ). One survey found that negative issue ads (which decry the foolishness of a position rather than advocate an alternative) broadcast on radio are judged to be fair, while negative character (sometimes called “image”) ads are considered unfair ( Shapiro and Rieger, 1992 ). In a 2000 experiment, critical news stories produced lower opinions of candidates when those stories focused on character advertising, but elicited no change when the subject was issue advertising ( Leshner, 2001 ). Another experiment found, in the 2008 presidential election, that young people reported greater feelings of political efficacy when exposed to issue-based rather than character-driven advertising ( Kaid, Fernandes, and Painter, 2011 ), although Shyles’s content analysis (1984) concluded that character content in 1980 presidential campaign ads aided voting decisions. Combining content analysis with experimental data, Schenck-Hamlin et al. found that viewers were more likely to be cynical regarding the government and more likely to hold politicians accountable in response to ads centered on candidate character than those focused on issues ( Schenck-Hamlin, Proctor, and Rumsey, 2000 ); however, another experiment suggested that issue-based attack ads can also lead to cynicism and lower perceptions of self-efficacy ( Dardis, Shen, and Edwards, 2008 ; see also Groenendyk and Valentino, 2002 ).

Agenda Setting

In so far as political advertising has an agenda-setting effect, it can frame issues and candidates in a way that suggests what viewers should think about ( McCombs and Shaw, 1972 ); by heightening the salience of specific attributes, it can also produce a second-order agenda-setting effect that shapes how viewers think about issues and candidates. Separate studies found this to be the case in both American elections ( Golan, Kiousis, and McDaniel, 2007 ) and those in Spain ( McCombs, Llamas, Lopez-Escobar, and Rey, 1997 ).

Issue Convergence and Ownership

The various issues on which opposing candidates focus over the course of a campaign tend to increasingly converge as the overall amount of money spent on the campaigns increases. Kaplan, Park, and Ridout (2006) found that candidates are rarely able to “own” particular issues to a significant degree; the need to cover a variety of issues, and the expense of doing so via political advertising may explain why the issues on which a candidate focuses in his or her own advertising are frequently not the same as those on which his or her party will concentrate.

Candidates are able to enhance their chance of winning an election with advertising that highlights issues they own. Using experimental data, Ansolabehere, Iyengar, Simon, and Valentino (1994) showed that candidates who choose to focus on issues they own are able to create more resonance for their campaigns than those who concentrate on issues only because they are featured prominently in news. Although one study has found that Democratic and challenger advertising tends to be more aligned with public priorities than the ads of Republicans or incumbents, it did not find any such difference between election winners and losers ( Hansen and Benoit, 2002 ).

Audience Variables in Effects of Political Advertisements

Negativity bias.

Humans have a negativity bias, weighing negative experiences more heavily than positive ones, holding the valence of the two constant ( Rozin and Royzman, 2001 ). Negative information carries more weight than positive information, as well ( Kellermann, 1989 ).

In general, attack is processed more quickly and recalled more readily than advocacy. The effectiveness of negative political advertising can be explained by expectancy theory (i.e., messages violate norms and expectations of language use and so are memorable for being out of the norm) ( Pfau, Parrott, and Lindquist, 1992 ). Lau, Sigelman, and Rovner (2007) also show that negative advertising is more memorable than advocacy advertising and stimulates more knowledge. Some experimental data show that negative political ads cause viewers to reflexively turn away in avoidance, exhibit and report greater physiological arousal than when exposed to more moderate ads, and better recognize the information presented ( Bradley, Angelini, and Lee, 2007 ).

Confirmation Bias

Consistent with confirmation bias, voters scrutinize advertised claims with which they disagree more critically than those that support their existing dispositions. A 1996 Budesheim, Houston, and DePaola experiment involving negative advertising showed that “although participants were sensitive to message content from both in-group [defined as those with whom they identify, are similar to them, or who belong to the same social group] and out-group sources, less stringent criteria were used when evaluating out-group political messages than when evaluating in-group political messages.” In addition, the particular content of the negative message and the strength of the justification for claiming it also affect viewers’ evaluations of the ad ( Budesheim, Houston, and DePaola, 1996 ). A study employing survey and advertising data from the 2000 presidential campaign and two 1998 gubernatorial campaigns showed that while voters’ distaste for negative advertising may affect their judgment of the campaign itself, it does not necessarily affect their judgment of the information offered by the ad, as viewers tend to separate those judgments ( Sides, Lipsitz, and Grossmann, 2010 ).

Issue and Campaign Awareness

The level of a voter’s issue and campaign awareness prior to viewing an ad will moderate its persuasive effect. The least aware are more susceptible to persuasion not only because they only pick up on the simplest part(s) of the message and do not devote analytical energy to make sense of more subtle information cues, but also because they have little context against which to compare/evaluate the presented information.

The amount of information that viewers glean from political advertising is mediated by how informed they were to begin with and by the degree to which they follow other media. Those who are least informed about candidates and issues before exposure to political advertising learn the most from these ads, because the issues highlighted in them become more salient ( Atkin and Heald, 1976 ). Political advertising’s effect on voting intention is also stronger for those who are least informed initially, regardless of the strength of their party affiliation or whether they are politically independent ( Franz and Ridout, 2007 ; Surlin and Gordon, 1977 ). In addition, one study found that viewers who tend to pay more attention to television newscasts are more strongly affected by political advertising, although newspaper reading reduces the impact of negative advertising that is seen on TV ( Faber, Tims, and Schmitt, 1993 ). Because political ads tend to be clustered around local newscasts and the likelihood that their inaccuracies will be corrected there is slight, local news viewing has been associated with increased belief in repeatedly aired distortions featured in political ads aired in adjoining space ( Jamieson and Gottfried, 2010 ). Viewers are more likely to recall political advertising by candidates they support, though in one study one-third of viewers couldn’t recall anything whatsoever about political ads they may have seen; recall is more related to attitude than television exposure or demographics ( Faber and Storey, 1984 ).

Need for Cognition

Since the most aware have a higher level of information demand or “need for cognition” ( Cacioppo, Petty, Feinstein, and Jarvis, 1996 ), they will learn the most from ads; but with a larger body of knowledge, they will be little swayed by each new input ( Patterson and McClure, 1976 ; Valentino, Hutchings, and Williams, 2004 ). Those with a high awareness of politics are more likely to understand and retain information but less likely to change their minds as a result ( Delli Carpini and Keeter, 1996 ). Since the most aware have already made up their minds, messages consistent with an opinion reinforce it while contrary messages are resisted ( Kaid and Tedesco, 1999 ). The RAS (receive, accept, sample) model predicts that the most aware will learn the most from ads but will change their minds the least, while the least aware will learn the least but change their minds the most ( Zaller, 1992 ).

Political Efficacy and Party Identification

Whether a viewer will find the assertions offered in political advertisements believable depends on his or her political involvement, sense of personal political efficacy, and party affiliation. Voters who are more involved in following the political process may be less likely to believe ads than are those who are less so. Viewers who perceive they have some influence on the political process (political efficacy) and are more satisfied with government are more likely to accept ads at face value, and the content of any particular ad is more likely to be believed if it is offered by the viewer’s own party rather than by the opposition ( O’Cass, 2005 ). The fact that campaign rhetoric within a party tends to be consistent, regardless of other campaign restraints, helps make one’s party a trustworthy source of information ( Spiliotes and Vavreck, 2002 ). Those with lower levels of trust in government and politicians are more affected by negative ads than those with higher levels of trust ( Martinez and Delegal, 1990 ).

Attack ads can be effective against the target if there is no response; however, a strong response may turn viewer emotions back against the ad sponsor ( Sonner, 1998 ). Consistent with research that indicates public disapproval of negative ads generally, Roddy and Garramone (1988) found that viewers prefer that responses to attack be positive; nevertheless, a counterattack is more effective in discrediting the original attacker. Messages in attack advertising that are backed by a credible source can be effective in damaging the electability of an attacked candidate, but if the allegation is denied by another credible source, the effect of the attack can be nullified; if that denial is accompanied by a counterattack, the attacked candidate may come off better than before the exchange began ( Calantone and Warshaw, 1985 ). Pfau and Kenski (1990) agree that candidates must defend against negative messages but find that inoculation strategies against anticipated attacks are more effective than ad hoc responses.

Negative advertising can have a third-person effect. Viewers deny that negative advertising about someone they support will affect them but do posit a probable effect on others; by contrast, they report that negative advertising about someone they do not support affects them but hypothesize that it would probably not affect others ( Cheng and Riffe, 2008 ; Cohen and Davis, 1991 ; Shen, Dardis, and Edwards, 2011 ). When viewers become convinced that they must get to the polls and counteract the ballots of their gullible neighbors, the third-person effect can lead to increased voting ( Golan, Banning, and Lundy, 2008 ).

Under some conditions, negative political advertising can damage the sponsoring candidate more than the intended target. Scholars have found that viewers find negative advertising distasteful and tend to attach that distaste to the candidate or party sponsoring (or intended to benefit from) the ad ( Garramone, 1984 ; Hill, 1989 ; Jasperson and Fan, 2002 ; Kahn and Geer, 1994 ; Pinkleton, 1998 ); they especially don’t care for ads that use inflammatory language, attack a candidate’s personal life, or are misleading ( Jamieson, 2000 ). This effect can be muted by party allegiance ( Bowen, 1994 ; Robideaux, 2004 ) and party loyalty ( Sorescu and Gelb, 2000 ), the perceived credibility of the information source cited in the attack ( Calantone and Warshaw, 1985 ), and whether the ad includes insult or is more substantive ( Roese and Sande, 1993 ). The chance of a backlash from negative advertising can be significantly reduced by using a contrastive approach rather than outright attack ( Pinkleton, 1997 ).

Unanswered Questions

Experimental research on the impact of political ads has had difficulty mimicking the actual campaign environment in which multiple channels carry complementary advertising content and in which competing ads contain responses, re-framings and counter-attacks. The rolling cross sectional surveys that have identified ad effects ( Johnston, Hagen, and Jamieson, 2004 ; Kenski, Hardy, and Jamieson, 2010 ) have had the benefit of across time analysis of the competing message environment, but despite their inclusion of television buys in 2000 and television, cable and radio in 2008 failed to track Internet advertising content in either and had no way of confirming actual exposure to messages aired in the survey respondent’s media market. The rise of micro-targeted messaging through mobile devices increases the difficulty of tracking the actual content to which subgroups of persuasible voters are exposed.

Although its effects are mediated by party affiliation, political knowledge, political involvement, and media exposure, political advertising can affect voting. In addition to persuading viewers to vote for a specific candidate or issue, political ads can also have agenda-setting and third-person effects that can indirectly affect voter intention. Because political advertising is a potent tool for influencing voter choice, differences in the amount of money alternative campaigns have available to pay for such ads can affect outcome. Although viewers don’t report that they like negative or attack advertising, it can nevertheless be effective in shaping voting decisions; however, this effect may be the opposite of what the ad sponsor intended. Negative ads do seem to affect cynicism regarding government and can reduce voter turnout under specific conditions, but they do not significantly affect overall voter turnout. Political advertisements need to elicit both emotional and cognitive responses in order to move votes. Print and broadcast news abet the power of political ads by legitimizing the format and giving the ads free airplay.

Despite the criticism that political advertising receives for manipulating voters, it does underscore the existence of choices in a system of government and assert that they are consequential.

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The effects of targeted political advertising on user privacy concerns and digital product acceptance: A preference-based approach

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• Published: 01 September 2023
• Volume 33 , article number  46 , ( 2023 )

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• Katharina Baum   ORCID: orcid.org/0000-0003-0378-2936 1 ,
• Olga Abramova   ORCID: orcid.org/0000-0001-5481-9036 2 ,
• Stefan Meißner 3 &
• Hanna Krasnova 1  

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Online businesses are increasingly relying on targeted advertisements as a revenue stream, which might lead to privacy concerns and hinder product adoption. Therefore, it is crucial for online companies to understand which types of targeted advertisements consumers will accept. In recent years, users have been increasingly targeted by political advertisements, which has caused adverse reactions in media and society. Nonetheless, few studies experimentally investigate user privacy concerns and their role in acceptance decisions in response to targeted political advertisements. To fill this gap, we explore the magnitude of privacy concerns towards targeted political ads compared to “traditional” targeting in the product context. Surprisingly, we find no notable differences in privacy concerns between these data use purposes. In the next step, user preferences over ad types are elicited with the help of a discrete choice experiment in the mobile app adoption context. Our findings suggest that while targeted political advertising is somewhat less desirable than targeted product advertising, the odds of choosing an app are statistically insignificant between two data use purposes. Together, these results contribute to a better understanding of users’ privacy concerns and preferences in the context of targeted political advertising online.

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Introduction

Online companies commonly serve advertisements to their customers as a revenue strategy (Kim & Kim, 2017 ). In recent years, advances in computing technologies have enabled companies to collect and process large amounts of user data to make these advertisements increasingly personalized (Zhu et al. 2023 ; Bleier & Eisenbeiss, 2015 ). By analyzing user data, online advertising can be targeted to customers’ demographics, preferences, and interests, making the ads more effective and, therefore, more attractive to advertisers (Acquisti et al.,  2016 ; Farahat & Bailey, 2012 ). Research has also shown that users may find targeted advertising more useful (Bleier & Eisenbeiss,  2015 ). However, in some cases, users may perceive targeted advertising as intrusive and express heightened privacy concerns (Boerman et al.,  2017 ), which could hinder product adoption and lead to consumer backlash (Zhu et al.,  2023 ; Chen et al.,  2019 ). Hence, it is crucial for online businesses to understand the type of targeted advertising that users will accept.

The dichotomy between perceiving personalized advertisement as useful on the one hand and privacy intrusive on the other has been termed the personalization-privacy paradox (Sutanto et al.,  2013 ). So far, research in this area has mostly focused on user attitudes toward commercial advertising (Chiasson et al., 2018 ; Bleier & Eisenbeiss, 2015 ; Walrave et al.,  2018 ). However, users are increasingly targeted online with highly personalized advertising for political campaigns as well. At the same time, little is known about how customers react to the use of their data for political advertising in terms of their privacy concerns and their product adoption intentions.

With spending on online political campaigning having skyrocketed in recent years (Spenkuch & Toniatti, 2018 ), making up a third of the ad spending of the 2022 U.S. midterm elections (Statista, 2023 ) as well as almost the entire budget of the “Vote Leave” campaign prior to the Brexit referendum in 2016 (Wong, 2018 ) the topic of targeted political online advertising is a hotly debated issue in media and society (Zuiderveen Borgesius et al.,  2018 ). Some scholars regard the use of personal data as a threat to democracy (Persily, 2017 ), the free exchange of political ideas (Tucker et al.,  2018 ), and voter polarization (Sunstein, 2018 ). Public media has voiced similar concerns, stating that targeted political advertising “might work too well” by presenting recipients with individually tailored election promises (Wong, 2018 ; Fowler, 2020 ). Further, the practice of targeting political ads to voters has been acknowledged as “unethical” (Graham-Harrison et al.,  2018 ) and “immoral” (Vidler, 2018 ). Overall, the intensity of the discussion on political targeting online seems to indicate that privacy concerns about the use of personal data for political ads are significant and possibly greater than privacy concerns about targeting in product ads Footnote 1 .

But not only the media are concerned about targeted political advertisements. Similar developments are taking place in the European and US legal contexts. The General Data Protection Regulation (GDPR) introduced in the European Union prohibits the use of data for purposes other than those originally stated in the consent form (GDPR, 2016 ). In addition, UK politicians and human rights organizations call for greater transparency in the use of personal data for targeted political advertising (Galaski, 2022 , Hern, 2018 ). In Germany, data collected for political purposes must fulfill stricter requirements than data collected for commercial use (Kruschinski & Haller, 2017 ). Moreover, regulation in the United States tightens the requirements for political advertisers, but not other advertisers, to target consumers online (Lapowsky, 2018 ).

However, research findings on users’ acceptance of these advertisements remain limited. First empirical evidence shows that these developments might reflect public opinion. While 62% of U.S. respondents indicate that using data to present targeted political advertising is unacceptable, only 47% say the same about product ads (Smith, 2018 ). Moreover, public opinion polls show that the majority of Americans would prefer social media platforms to stop showing political ads (Auxier, 2020 ). Taken together, these observations suggest that (1) the use purpose of data collected for targeting might influence privacy concerns, and (2) attitudes towards political targeting might be more negative than towards targeting for other purposes. Nonetheless, it remains unclear whether people actually have greater privacy concerns when it comes to using their information for political purposes compared to other types of targeted marketing.

Research that examined consumer attitudes toward targeted advertising through the lens of the personalization-privacy paradox suggests that the acceptance of personalization depends on several contextual factors such as communication channel (Zhu et al.,  2023 ), being primed to think about privacy (John et al.,  2011 ) or perceived control over one’s information (Xu et al. 2012 ). We suggest data use purpose might be an additional contextual factor that could impact how much data users are willing to share for personalized advertisements. So far, only a few studies have investigated the role of use purpose of data collection in personal data valuation and privacy concerns (Zhu et al.,  2023 ; Sheng et al., 2008 ). Preliminary research suggests that the purpose for which data is collected is crucial to consumers, with political entities being viewed more negatively as recipients of personal data than commercial entities (Tan et al.,  2018 ; Kozyreva et al.,  2021 ). This is particularly relevant in the context of the GDPR legislation, which strictly requires companies to specify the purpose of data collection and prohibits other uses (GDPR, 2016 ). To the best of our knowledge, no experimental study so far has systematically studied user acceptance of data collection for political advertisements as opposed to product advertisements. In this vein, our paper sheds light on the neglected aspects of targeted political advertising: the effects of use purpose of data collection on user privacy concerns and acceptance of digital products. Specifically, we address the following research question:

RQ1: Are privacy concerns greater when data is collected for political advertising than when it is collected for product advertising?

Past studies show that stated privacy concerns and actual privacy behaviors are not always correlated (Dinev et al.,  2015 ; Baruh et al.,  2017 ; Yu et al.,  2020 ). In fact, users frequently act contrary to their privacy concerns when faced with real-life decisions (Acquisti et al., 2015 ). Therefore, this study examines users’ acceptance of targeted political advertisements beyond privacy concerns and includes people’s choice behavior. We further ask:

RQ2: How does the intention to adopt differ between products that process user data for targeted political advertising and targeted product advertising?

Our contribution is twofold: First, we add to the existing IS privacy literature by investigating the relevance of use purpose in the study of user privacy concerns through the lens of the personalization-privacy paradox (Belanger & Crossler, 2011 ; Sutanto et al.,  2013 ). While previous research has looked at various determinants of privacy concerns with online products, such as anonymity (Schomakers et al.,  2020 ), transparency (Betzing et al.,  2020 ), or social cues and trust (Zalmanson et al.,  2022 ), data use purpose has received limited attention so far. Second, our results can assist online businesses in understanding acceptable data collection practices from the viewpoint of their users. Specifically, in study 1, we directly elicit and compare user privacy concerns about the use of different personal data items for political and product targeting. This enables us to address whether concerns about their personal data depend on these two different use purposes. In study 2, we apply the Discrete Choice Experiment (DCE) methodology (Derikx et al.,  2016 ; Ebbers et al.,  2021 ) to elicit users’ stated preferences over targeted ad types in a choice scenario that approximates a real-life situation more closely than the setting in study 1. Indeed, the DCE approach allows for a better understanding of whether the use of user information for targeted political advertising has a substantial impact on the choice behavior of consumers and is, therefore, of high importance for practitioners.

Both studies were pre-registered at the Center for Open Science and Data. Instructions are available in the repository linked to the project. Footnote 2

Theoretical background

Privacy concerns and targeted advertisement: the personalization-privacy paradox.

Adopting the definition of privacy concerns by Hong and Thong ( 2013 , p. 267) as “the degree to which an Internet user is concerned about website practices related to the collection and use of his or her personal information,” we draw on the literature on the personalization-privacy paradox to understand how these concerns might differ between targeted political and targeted product advertising. The personalization-privacy paradox suggests that while users tend to have greater privacy concerns about advertising when it is targeted, they also see value in it (Angst & Agarwal, 2009 ; Sutanto et al. 2013 ). So far, most of this research has focused on the “traditional” marketing context, in which targeted ads are used to improve the reach and effectiveness of online product marketing (Acquisti et al.,  2016 ; Farahat & Bailey, 2012 ) as well as consumer perceptions regarding specific products, services, or brands (Boerman et al.,  2017 ). In these commercial contexts, consumers have been shown to perceive personalized advertisements as more useful (Bleier & Eisenbeiss, 2015 ), direct more attention toward such ads, exhibit a greater intention to forward them (Walrave et al.,  2018 ), and are more likely to click on them (Aguirre et al.,  2015 ). Consequently, this elevates the effectiveness of the message in terms of product purchase intentions (Tucker, 2014 ) and positive attitudes toward the promoted brand (Walrave et al.,  2018 ). For example, Hirsh et al. ( 2012 ) show that personality-based targeting increases the acceptance and effect of the message to the consumer. Similarly, advertising based on users’ interests has been shown to lead to a higher acceptance and success rate (De Keyzer et al.,  2015 ; Tucker, 2014 ) as well as click-through rates (Boerman et al.,  2017 ).

At the same time, while users see value in targeting, most people do not wish to receive ads that are targeted to their interests (Boerman et al.,  2017 ) or online activities (Chiasson et al., 2018 ). As such, these privacy concerns are rooted in practices of collecting and using personal data (Moore et al. 2015 ), forwarding it to third parties (Sutanto et al.,  2013 ), and tracking individuals over several websites (Antón et al., 2010 ). For example, users have been shown to oppose targeting that is based solely on the analysis of their individual data as compared to aggregate data (Dolin et al.,  2018 ). They are also more reluctant to share information with websites that show targeted ads when it makes them personally identifiable (e.g., phone number, address, social security number, exact current location) and when it includes financial details than when it includes only basic demographic information (e.g., country, gender, age) (Chiasson at al., 2018 ; Leon et al.,  2013 ). Potential reasons why users might be opposed to their data being used for targeting advertisements to them include them becoming aware of the attempted persuasion, making them feel manipulated (Bleier & Eisenbeiss, 2015 ), and being deprived of their freedom of choice (Tucker, 2012 ). Further, targeted advertising increases perceived intrusiveness (van Doorn & Hoekstra, 2013 ). Together, these results suggest that despite the potential relevance of targeted ads for users, privacy concerns are central to understanding user acceptance and attitudes toward them (Sutanto et al.,  2013 ).

To date, only a small number of studies have examined the acceptance of personalized advertisements in the political context. Surveys report on differences in acceptance of targeted product advertisements and targeted political advertisements. For example, 62% of US respondents regard the use of their data to show them targeted political advertising as unacceptable, while only 47% state the same about commercial ads (Smith, 2018 ). Further, a survey study among participants from the USA, UK, and Germany shows that acceptance of target political advertisements is lower than acceptance of target product advertisements (Kozyreva et al.,  2021 ). Moreover, 54% of surveyed Americans state that social media platforms should not be allowed to show any political advertisements (Auxier, 2020 ). Together, these results suggest that privacy concerns between targeted product and targeted political advertisements might differ. Theoretical reasons for this will be discussed in the next sections.

Context as a determinant of privacy attitudes

Past literature has established that privacy concerns vary with contextual factors (Acquisti et al.,  2015 ; Zhu et al.,  2023 ). Hence, whether a person accepts the personalization of advertising messages in exchange for providing personal data may depend on the situation. Recently, researchers have emphasized the importance of systematically studying context when examining consumers’ privacy attitudes, adopting the perspective that privacy is a malleable state of being intertwined with its context (Zhu et al.,  2023 ; Xu & Zang, 2022 ; Zu & Kanjanamekanant, 2021 ). Through this lens, an individual’s privacy preferences are not the result of a fixed set of rules that weigh the costs and benefits of data disclosure, but rather, they are highly volatile and subject to change depending on factors such as social norms, emotions, and heuristics (Acquisti et al.,  2015 ). The reasons for this may lie in the nature of the privacy decision-making itself: Privacy harms are often intangible and accompanied by information asymmetries and, therefore, not easily understood by consumers (Acquisti et al.,  2015 ). Further, even when aware of the risks and benefits of data disclosure, people might still have malleable privacy preferences as people, in general, have difficulties deciding how much they like products or services (Slovic, 1995 ), with privacy being no exception (Acquisti et al.,  2015 ). In addition, individuals might experience cognitive distortions when assessing the benefits and costs of privacy decisions (Acquisti et al.,  2013 ). All of these factors contribute to a high level of uncertainty when forming privacy concerns or engaging in decisions that involve privacy trade-offs (Acquisti et al.,  2015 ). Research has shown that in situations that are highly uncertain, individuals turn to contextual cues for guidance, which makes privacy concerns a function of their context (Xu & Zhang, 2022 ). Hence, an individual might display extreme privacy concerns in one setting, but slight changes in the environment could result in a substantial relaxation of these concerns. In the realm of privacy research, a context is characterized by factors that shape all situational opportunities and constraints, such as the type of information used, the entities involved, or how the data is processed (Nissenbaum, 2009 ; Xu & Zhang, 2022 ).

Numerous studies have demonstrated that privacy concerns are context dependent. For example, the privacy concerns of individuals will be different if their data is processed in the cloud or on a client-side basis (Kobsa et al.,  2016 ). Further, users express heightened privacy concerns when the data for personalization originates from third parties other than the website they are visiting at that moment (John et al.,  2018 ; Zhu & Kanjanamekanant, 2021 ). In addition, counterintuitively, people are less willing to disclose their data on professional websites versus unprofessional-looking ones (John et al.,  2011 ). Exogenous changes in the context that alter the default settings also impact privacy behavior: When Facebook changed its visibility settings such that publicly displaying a user’s high school became the default, a stark increase in people doing so was observed (Stutzman et al.,  2013 ). In sum, these results show that the acceptance of targeted advertising depends on different contextual cues, and the purpose of data collection for either product or political advertisements is potentially one of them.

Data use purpose as a contextual factor

Extending the findings on the context as a determinant of privacy attitudes, we propose that users’ privacy concerns might differ depending on whether their data is being used in the context of target political or targeted product advertisements. However, only a few studies so far have investigated the use purpose of personal data as a contextual factor potentially determining privacy valuation. This is of high practical relevance, however, since the GDPR and international privacy guidelines by the OECD stipulate that companies make any use purpose salient to consumers during data collection (purpose specification principle) and generally use personal data only for purposes compatible with this purpose (purpose limitation principle).

Extant research suggests that personal data use purpose alters people’s acceptance of personalized advertisements. For example, Sheng et al. ( 2008 ) show that people express greater privacy concerns when services are personalized for the purpose of nonemergency information versus emergency alerts like natural disasters. More recently, Zhu et al. ( 2023 ) found that participants perceived personalized advertisements as less privacy-preserving when their data was being used for advertisements in private versus in the work context. Further, studies show that when data is collected for the purpose of secondary use by third parties, users express greater privacy concerns (Potoglou et al.,  2013 ; Preibusch, 2015 ). When measuring the valuation of personal data depending on the recipient who uses the data, Tan et al. ( 2018 ) found that participants are less likely to sell their personal data to a political party than to an advertising network. Surprisingly, when it comes to health-related information, people are more willing to disclose it to the public and certain third parties than to friends and family (Prasad et al.,  2012 ). Kozyreva et al. ( 2021 ) report that survey participants find the use of private data for commercial purposes more acceptable than for political purposes. However, responses could have been subject to demand effects, as participants stated attitudes towards political as well as product ads.

Together, past studies have examined people’s attitudes toward data use purpose in the domains of emergency situations (Sheng et al.,  2008 ), work versus private messages (Zhu et al.,  2023 ), third-party usage (Potoglou et al.,  2013 ; Preibusch, 2015 ), and being sold to political parties (Tan et al.,  2018 ), supporting the notion that the purpose for which personal data is used plays a significant role in users’ privacy attitudes and decision-making process. So far, most studies that compared attitudes toward targeted political and targeted product advertisements are observational (Kozyreva et al., 2021; Smith, 2018). Therefore, research remains limited, calling for more experimental studies in this context. Against this background, we experimentally explore the extent of users’ privacy concerns and their attitudes toward targeted political ads compared to targeted product ads.

Research overview

We conduct two studies that test for differences in users’ privacy concerns and product adoption intention between targeted political advertisements and targeted product advertisements. In study 1, a vignette experiment, 300 participants revealed their privacy concerns toward a digital service that either used their data for targeted political or targeted product advertisements. In study 2, 297 respondents stated their intention to adopt an app that showed them either targeted political or targeted product advertisements in a discrete choice experiment.

Study 1: Vignette experiment

In light of sparse research evidence and given the public discussion of online political advertising, understanding if consumers perceive use purpose differently is highly important for multiple stakeholders, including internet companies and legislators. Indeed, Bode and Jones ( 2018 ) show empirically that privacy concerns and public support for stronger privacy regulation are closely intertwined and that effective legislative action has to address the most pressing concerns of constituents. Further, Angst and Agarwal ( 2009 ) have argued that understanding users’ privacy concerns is imperative to understanding their adoption of services. Hence, in study 1, we contribute to understanding purpose-dependent privacy concerns. Specifically, we test whether users have stronger privacy concerns when they are informed that their data is used for targeted political advertising compared to targeted commercial advertising. This research question is related to works by Kozyreva et al. ( 2021 ), Tan et al. ( 2018 ), and Chiasson et al. ( 2018 ), who find that concern for sensitive data is related to its use.

Methods and participants

We used a between-subject design in the form of vignettes. This type of design allows for the measurement of perceptions in a reliable and valid way and has been widely used in IS research (Dennis et al.,  2012 ; Siponen & Vance, 2010 ). In both conditions, participants were presented with a fictional video streaming platform that collects users' personal data in order to target different ads (see Table  1 ). In treatment 1, participants were presented with a situation in which the data was collected to target product advertisements. In treatment 2, the data was used to target advertisements for a politician or political campaign. Hence, participants were only presented with one of the possible purposes for which their data is used to mitigate concerns over experimenter demand effects (Charness et al.,  2012 ). One hundred fifty-one participants were randomly assigned to treatment 1, and 149 participants to treatment 2. The instructions that were presented to participants are available in Table  1 .

The item list was constructed based on previous research on privacy concerns with regard to certain data items (Melicher et al.,  2016 ). Participants indicated their concern if a specific given item on the list was used to personalize an advertisement to them. Participants could indicate their level of concern on a 5-point scale with 1 = unconcerned to 5 = very concerned (Krasnova et al.,  2013 ). Moreover, the option “cannot judge” has been added to complete the range of possible answers. In total, 16 items were presented (Leon et al.,  2013 ). An overview of the items is in Table 2 . The order of items was randomized. We also collected data about age, education, gender, social media use, and the use of an ad-blocker. Running balancing checks for the two treatments revealed no statistically significant differences for any demographic categories between the two groups. This suggests a balanced assignment to treatments.

We recruited 300 mTurk workers. That sample size gave us sufficient power to pick up a small effect of 0.3 standard deviations with 80% power. The survey that mTurk-participants completed took slightly more than 7 minutes (mean= 7 min 27 s, median= 6 min 21 s). Data was collected using Qualtrics (Peer et al.,  2012 ). To avoid selection bias, we gave no information about the purpose of the study on mTurk. Workers were, on average, 34.7 years old. 39.2% of the participants were female. 44.0% held a Bachelor’s degree. 98.2% of participants reported being active social media users, and 91.7% reported sharing information on social media at least very rarely. However, only 10.8% of participants reported doing so daily or multiple times a day.

We performed a two-sided independent samples t -test to check for differences between the level of concern in the targeted product and the targeted political ads condition. The t -tests were run for all 16 items on the list. Four “cannot judge” responses ( N  = 1 for religious views, N  = 2 for political views, and N  = 1 for browsing) were excluded. Our results (Table  2 ) indicate that participants are equally concerned about targeted political advertising vs. targeted product advertising. None of the differences across the 16 items we tested is significantly different from 0 at conventional significance levels.

We find no evidence for increased privacy concerns when personal data is used for targeted political advertising compared to targeted product advertising. As such, these findings counter the assumption that the purpose of data collection, specifically the usage of user information for political purposes, is an important determinant of privacy concerns in the specific case we investigated. Nevertheless, past research questions the external validity of privacy concerns elicited in surveys (Woodruff et al.,  2014 ). Further, these findings do not allow us to draw wide-ranging conclusions regarding user preferences. Indeed, the setting of study 1 did not allow us to see if specific user concerns regarding different types of targeting have a differential impact on user acceptance preferences/decisions. In fact, it could be that while observed levels of concern do not differ between the use for targeted political and product ads, user willingness to adopt a product that uses personal data for targeted political advertising is lower. On the other hand, one may also argue that these hypothetical differences in behavioral impact might be driven by stronger opinions regarding political advertising in general and might not be related to information usage per se (targeting). To disentangle these effects, study 2 was conducted.

Study 2: Discrete choice experiment

In study 2, we further explore our initial research question with a DCE commonly employed to reveal user preferences (e.g., Ebbers et al.,  2021 ; Abramova, 2022 ). Specifically, we investigate whether there are any differences in user preferences regarding the use of their information for targeted political and targeted product ads. By applying a DCE, we are able to (i) measure user preferences over targeted advertising in the political vs. commercial (product) domain, as well as (ii) explore user preferences over targeted vs. non-targeted ads in both contexts.

Methodology

The DCE approach is based on a combination of two elements: (1) discrete choice analysis to model preferences and (2) stated preference methods to gather the required data for eliciting these preferences (Kjaer, 2005 ; Street & Burgess, 2007 ; Viney et al.,  2002 ). Stated preference methods allow researchers to specify consumer preferences in hypothetical but close-to-the-truth scenarios. It helps to disentangle the influence of discrete attributes in the choices made by respondents and derive the valuation of these attributes. Due to its consistency with the economic demand theory, DCE is preferred over other conjoint methods, which are purely mathematical (Louviere et al.,  2010 ). Another element of DCE, discrete choice analysis, is rooted in the Random Utility Theory (RUT) (Manski, 1977 ; McFadden, 1973 ), which considers a rational individual who chooses between several alternatives consistently and maximizes his/her own utility. In line with the economic theory of value, goods in a DCE are perceived as a bundle of attributes because “these characteristics give rise to utility” (Lancaster, 1966 , p. 163). Consequently, the utility of a good is the sum of the utilities of its individual attributes. The probability that a particular alternative is chosen depends on the estimated utility discrepancy among alternatives caused by differences in utility for each attribute. Moreover, it is possible to estimate a consumer’s marginal willingness to pay (WTP) for a change in the level of an attribute, assuming that the vector of attributes includes costs (Kjaer, 2005 ).

Model specification

We focused on a fictional scenario of a mobile streaming app, “Hi.tube.” To increase the attractiveness of the app and thereby create a balanced trade-off between ads as the (negative) attribute of interest and other characteristics (Krasnova et al.,  2014 ; Rose & Bliemer, 2007 ), the app description stated that it would employ a novel data compression technology that reduces mobile data usage. The app was presented in the following way “ Please read the following text presenting you an app called “HI.tube.” It works for Android as well as Apple iOS. This is what the app does: HI.tube is a streaming app which allows you to watch videos on a large number of topics (similar to YouTube, Netflix, or Showbox). Wherever you are, whether on the way to work, waiting in a long queue or relaxing at home sofa, with Hi.tube you will never be bored! With Hi.tube you can upload your own videos, or watch videos other users created. You can engage with our growing Hi.tube community by following other users, commenting or liking videos, and messaging them. Another advantage of Hi.tube is a new method of data compression which significantly reduces mobile Internet usage and is therefore optimal while commuting! Enjoy millions of videos, channels and playlists in high-quality – always and everywhere using the minimum of mobile Internet! ”.

Conducting a DCE involves three key stages: (1) model specification; (2) experimental design, and; (3) questionnaire development (Rose & Bliemer, 2007 ). In the model specification stage, the selection of attributes and levels was based on the pretest with 50 mTurk workers. It revealed that the most important characteristics of the “Hi.tube” app, in descending order, include being ad-free, offering unlimited streaming, and enabling background play when the mobile device is locked. The average perceived usefulness of an app (Krasnova et al.,  2014 ) was moderately high (mean = 2.94 on a 5-point Likert scale). Following findings on critical features behind the app adoption from the pretest, the following attributes were included in the main experiment, namely (1) the advertisement plan of an app, (2) price as a monetary cost, and finally (3) streaming limit (to vary perceived benefit of an app). The levels for the attributes were chosen as follows (see Table  3 ):

Advertising plan

is the attribute in the focus of our analysis and simultaneously the most important one to users. Levels were designed with the aim of answering our research questions. Ad free was set as the baseline level. The other levels varied in terms of ad domain (political versus commercial (product) and targeting (no targeting versus targeting). An additional level of targeted ads for local events was introduced to decrease choices in the fractional factorial design from 90 to 36. Examples were chosen such that for each ad domain, the viewed video and induced interest remained fixed, but only the resulting ad varied. For the political ad, the bi-partisan topic of food taxes was chosen in order to mitigate the effects of political affiliation.

Following our pretest, the maximum willingness to pay for the app without ads, unlimited streaming, and background play was $3.00 USD (median). Hence, we decided to set price levels to $0.00 USD (free), $1.00 USD, and $3.00 USD.

Streaming limit:

Unlimited streaming was rated as the second most important feature of the app in the pretest. Unlimited streaming was therefore set as the upper bound. One and 3-h daily access were chosen for the other levels considering the app was presented as being useful for commuting. Average daily commuting times to work are approximately 50 min (US Census Bureau, 2021 ).

Table  3 gives an overview of attributes and levels as presented to respondents.

Experimental design and questionnaire creation

Upon accessing the survey, respondents were presented with a detailed description of the video streaming app, its functionality, and its value proposition, as described above. Next, the main features of the HI.tube app, i.e., attributes and their corresponding levels, were presented as shown in Table  3 . Acknowledging that not all users may clearly understand the specificity of different advertisement plans, we provided examples of how a particular ad type works and made respondents spend at least 1 minute on the page. Next, 12 choice sets (the sequence of the presentation was randomized) were presented for evaluation by the respondents. The number of choice sets was derived via the D-efficient design, resulting in 12 choice sets per person, with each choice set consisting of 3 alternatives (see Fig.  1 ). Specifically, in each choice set, respondents were asked to choose one app that they would install (“Which option do you prefer?”) with possible answers A, B, or C, and a “no choice” option (“None of them”) to cover situations where none of the presented streaming apps was acceptable for a respondent. Finally, we asked respondents several questions about their demographics, privacy concerns, and attitudes towards targeted and untargeted advertisements, experienced misuse of their personal data online, and degree of political involvement.

An image of the mock-ups that were presented to the participants

We recruited 297 mTurk workers. During recruitment, workers who took part in study 1 or in the pretest were excluded. To check for fatigue and other confounds, a manipulation check was incorporated, with the 12th choice card including an alternative that was strictly dominant. Participants who did not pass this manipulation check or always chose the “no choice” option were excluded from further analysis ( N  = 33). The average duration of filling out the survey was slightly more than 12 min (mean = 12 min 17 s; median = 10 min 13 s). Participants who completed the survey in less than 5 min were excluded from the analysis ( N  = 2).

In total, 262 responses were used in the final analysis. This number surpasses the minimum sample size recommended in Orme ( 2006 ), which is 83 for our model. To avoid selection bias, we gave no information about the purpose of the study on mTurk. 50.7% of our sample were female, and 50.3% were male, 42% held a Bachelor’s degree. Participants were, on average, 38.5 years old. Providing evidence for favorable attitudes towards the Hi.tube app among respondents, the average perceived usefulness of the app reached 5.20 (SD = 1.31) assessed on a 7-point scale (Krasnova et al.,  2014 ). Respondents reported being moderately engaged in politics (mean = 5.01, SD = 1.32) on a 7-point scale (Zhang & Bartol,  2010 ). Moreover, reported privacy concerns can be classified as moderate to high (mean = 5.22, SD = 1.42), measured on a 7-point scale (Krasnova et al.,  2009 ).

Model estimates and marginal willingness to pay

The data were analyzed using a mixed logit model, considered the most promising state of the art available when working with choice-based data since a random error term adjusts for individual-specific variations in preferences (Hauber et al.,  2016 ). In our case, the utility function of a participant \(i\) choosing an app alternative \(j\) in a choice set \(t\) looks as:

 where \(\mu\)  is the error component with the normal distribution with zero mean and standard deviation \(\sigma _{\mu}\) which varied across app alternatives \(j\) and respondent \(i\) and accounted for the correlations between observations obtained from the same respondent. The error component ε assumed to follow the Gumbell distribution with mean = 0 and accounted for differences between respondents, app alternatives and choice sets. Normal mixing distribution for price was assumed, and all attributes except price were dummy-coded (Table 4 , mixed logit).

Goodness-of-fit (GoF) measures provide evidence that the proposed model fits the data well. Our estimation results illustrate that all attributes included in our model are important for potential consumers. For example, the unlimited streaming plan ( \(\beta = 2.59, p<0.001\) ) and the price of the app ( \(\beta = -2.46, p < 0.001\) ) substantially determine decision-making. The coefficients for different advertisement plans are negative and significant, indicating users’ perception of advertising as an adverse feature. Coefficients can be interpreted as follows: on average, for a level change in one attribute (e.g., 3 h per day streaming) compared to the reference level (i.e., 1 h per day streaming), the odds of choosing a product with this attribute level (i.e., 3 h per day streaming) over a product with an attribute at the reference level increase by a factor of exp( \(\beta\) ) (i.e., exp (0.93) = 2.53 meaning 153% increase), while holding other variables constant. Given this, our results suggest that, on average, the odds of choosing an app with untargeted product ads over a no-ads app decrease by 66% (i.e., a factor of exp(− 1.09) ≈ 0.34) while holding other variables constant. Integrating targeted product ads into an app decreases the odds of choosing this product by 77% (i.e., exp(− 1.45) ≈ 0.23). The odds of choosing a product with untargeted political ads over an ad-free alternative decrease by 78%. Approximately 85% decrease in chances of being chosen is observed for an app with targeted political ads compared to an ad-free product.

After estimating the effect of various attribute levels on the user’s utility, we also computed the marginal willingness to pay (MWTP) for a change in the attribute level according to the following formula (Kjaer, 2005 , Ryan et al.,  2007 ):

Negative MWTP values can thus be interpreted as a required reduction in price to offset the downgrade to the inferior feature (Table  4 ).

Here it is important to note that in the absence of an alternative for a coefficient comparison test suitable for the mixed model and integrated in SAS, inferences on the differences between attribute levels were made on the basis of direct comparisons of MWTP for specific attribute levels and market share simulations. First, as expected, we observe that respondents show negative attitudes towards targeting, favoring untargeted over targeted ads for both political ( \(MWTPuntarg=-\$0.61\) vs. \(MWTPtarg=-\$0.77\) ) and product ( \(MWTPuntarg=-\$0.44\) vs. \(MWTPtarg=-\$0.59\) ) contexts. Second, differences in preferences are observed concerning the purpose of data use. Compared to the “no ads” scenario, users would ask for a $0.59 discount to accept an app that uses their data for the targeted product ads. Targeted political ads are viewed as slightly more undesirable by respondents and would require a $0.77 compensation.

Market simulations

To further explore differences in user concerns regarding targeted political ads and targeted product ads, we simulated consumer choices for certain app alternatives. Market shares were extrapolated via the mixed logit model, where initial estimates served as a starting point (see Table  4 ). To explore the effect of the type of targeted ads, we ran a series of simulations comparing three different apps. All apps offered unlimited streaming, yet only (1) is ad-free while, (2) contains targeted product ads, and (3) contains targeted political ads. Throughout all simulations, (2) and (3) remain free for users, whereas the price for (1) varies between free, $0.99, and $2.99. Moreover, the option “no choice” is available. Results are presented in Fig.  2 a.

Results of the market simulations based on participants’ preferences

The results of the simulations suggest that when all three options are free, 64% of respondents prefer an ad-free version, 20% select the option with targeted product ads, and 16% choose the option with targeted political ads. Increasing the price of the ad-free option to $0.99 and $2.99 strongly influences choices, rendering the ad-free version highly undesirable. More importantly, market shares of app versions with targeted ads increase respectively: when the price of an ad-free app reaches $2.99, the market share of an app with targeted product advertising reaches 46%, while the market share of the app with targeted political advertising follows closely, reaching 38%.

In the second simulation (Fig. 2 b, two apps were contrasted: a free app with unlimited streaming and targeted product ads vs. a free app with unlimited streaming and targeted political ads. We observe that while the app with targeted product ads will dominate the market with a market share of 54% vs. 44% for the option with targeted political ads, this dominance is very unstable due to users’ extreme price sensitivity. Once the alternative with targeted product advertising is priced at $0.99, its market share decreases to 25%, and the overwhelming majority (72%) switches to the free app with targeted political advertising.

Together, these findings cautiously suggest that while targeted political advertising is perceived as somewhat less desirable by respondents, their usage does not consequentially deter users from choosing such an app, with user preferences being highly volatile.

Robustness check: Alternative model and additional evidence

The analysis using a mixed logit model provides evidence for comparably small differences in users’ preferences towards targeted product ads and targeted political ads, with the latter being perceived as more negative. Although observable, these differences do not appear to be particularly pronounced. Hence, as a robustness check, we have computed conditional logit model estimates (Table  4 , conditional logit). As such, this approach does not account for the individual heterogeneity between respondents (and therefore is inferior to mixed logit modeling) but allows us to easily integrate a check for coefficients’ equality in SAS. In this case, the utility function of a participant choosing an app alternative in a choice set looks as:

The core findings remained the same, pointing to the estimated effects being insensitive to changes in model specifications.

For the conditional logit model, the statistical significance of the difference between two coefficients can be tested using the Wald test (see Table  5 ). The pairwise comparison suggests significant differences between targeted vs. untargeted advertisements for both product ( \(Ho: {\beta }_{\mathrm{Targ Product Ads }}= {\beta }_{\mathrm{Untarg Product Ads}}\) , Wald statistic = 5.63, Pr > ChiSq = 0.018) and political advertising plans ( \(Ho: {\beta }_{\mathrm{Targ Political Ads }}= {\beta }_{\mathrm{Untarg Political Ads}}\) , Wald statistic = 3.99, Pr > ChiSq = 0.046). At the same time, we find no significant differences with regard to the advertising plan type for both targeted ( \(Ho: {\beta }_{\mathrm{Targ Product Ads }}= {\beta }_{\mathrm{Targ Political Ads}}\) , Wald statistic = 2.31, Pr > ChiSq = 0.129) and untargeted ( \(Ho: {\beta }_{\mathrm{Untarg Product Ads} }= {\beta }_{\mathrm{Untarg Political Ads}}\) , Wald statistic = 1.92, Pr > ChiSq = 0.166) ads.

Summarizing, the analysis of the conditional logit model suggests that both targeted product and targeted political ads are judged as more negative than respective untargeted ads. Further, while users appear to show slight preferences towards targeted product ads compared to targeted political ads based on MWTP or choice simulations (see Table  4 , conditional logit), these differences are not statistically significant. As such, these findings corroborate our results of study 1.

Discussion, contributions, and limitations

Two studies reported in this paper explore users’ privacy concerns and preferences regarding the use of their data either for the targeted product or political ads. Interestingly, despite heated, mainly negative, media discussions surrounding the use of personal data for political targeting, we find that respondents in study 1 do not exhibit a higher level of privacy concern regarding targeted political advertising than targeted product advertising. We, therefore, negate RQ1 (Are privacy concerns greater when data is collected for political advertising than when it is collected for product advertising?).

Study 2 tested preferences over ad types in the form of real choice behavior when installing a fictional streaming app. Overall, the experiment shows that an average participant performs the traditional privacy calculus, weighing app-specific benefits against personalized ads and monetary costs (e.g., Betzing et al. 2020 ; Xu et al. 2011 ). Based on a conditional logit model analysis, we show that both targeted product ads and targeted political ads are judged more negatively than respective untargeted ads. Further, findings from our main analysis (mixed logit model) suggest that while targeted political advertising is perceived as somewhat less desirable by respondents, their usage does not consequentially deter users from choosing such an app. Moreover, these preferences are highly volatile once the price of a competing app changes. Further, statistical tests conducted with a conditional logit model find no significant differences between user preferences towards targeted ads in both domains. Together, addressing RQ2 (How does the intention to adopt differ between products that process user data for targeted political advertising and targeted product advertising?), our results suggest that people are opposed to targeting in general. Although our respondents were slightly more reluctant to use an app with political ads than for product ads (both targeted and untargeted), the difference is statistically insignificant.

Theoretical implications

Our findings contribute to the IS literature in several ways. First, our study adds to the literature on the personalization-privacy paradox (Angst & Agarwal, 2009 ; Sutanto et al.,  2013 ) by shedding light on the data use purpose as a contextual factor driving privacy concerns. Several studies have documented that the use purpose as a contextual factor impacts privacy preferences (Sheng et al., 2008 ; Potoglou et al.,  2013 ; Preibusch, 2015 ; Tan et al.,  2018 ; Zhu et al.,  2023 ). For example, a recent study by Zhu et al. ( 2023 ) found that communication channel, device, and business vs. private purpose predicted users’ perceived privacy concerns. Results show that users were less concerned when their Facebook messenger data were used to display targeted ads for a business trip accommodation compared to targeted ads for a family tour package. Focusing on other data use purposes (targeted product vs. targeted political ads), we report insignificant differences in the effects on privacy concerns when asked directly in a vignette survey (study 1) and indirectly in a stated choice experiment (study 2).

Second, we extend the literature on advertising personalization (Acquisti et al.,  2016 ; Farahat & Bailey, 2012 , Werner et al.,  2022 ) by showing that users accept targeted political advertising to the same extent as targeted commercial advertising but hold slightly less favorable views about targeted than untargeted ads in general. While earlier studies indicate that people prefer personalization in some cases (Ebbers et al.,  2021 ) and show that personalized advertisement significantly increases website stickiness (Werner et al.,  2022 ), we corroborate studies that show that users respond less positively to advertisements when personally identifiable information is used for targeting (e.g., Sutanto et al.,  2013 ; Ho & Bodoff, 2014 ; Tsekouras et al.,  2016 ; Balan & Mathew, 2022 ).

Third, we show that targeted political advertising is another area where people’s stated preferences in surveys (Kozyreva et al.,  2021 ) diverge from revealed choice behavior. While participants claim they dislike political targeting in surveys (Kozyreva et al.,  2021 ), our DCE results show that when faced with a decision scenario, they do not differentiate between targeted political and targeted product advertisements.

Finally, this paper broadly enriches privacy research in e-commerce and precisely the “E-commerce benefits and consumer privacy” theme in the taxonomy of Bandara et al. ( 2019 ). We experimentally verified the relevance of the privacy calculus lens for an average user (Dinev et al., 2015 ): our respondents were sensitive to the benefits of a digital product (streaming limit) as well as to monetary (price) and non-monetary costs (ads). While Betzing et al. ( 2020 ) report that transparently disclosed privacy policies insignificantly affect acceptance rates of consent to the use of personal data, we show that a disclosed ad plan (e.g., using data for targeted political purposes) significantly affected the probability of choosing an offer. Still, the sensitivity towards various advertisement plans was relatively low compared to price.

Practical implications

Our findings inform online businesses about acceptable data collection practices from a user perspective. Study 1 (Table 2 ) ranges a comprehensive list of data items based on how much they drive privacy concerns. By understanding what information users find acceptable to share and being transparent about data usage upfront, online businesses can establish trust and credibility with their users, to increase user engagement and loyalty.

Next, this paper suggests that people informed about how their data will be used (e.g., for targeted marketing or political ad campaigns) tend to find data collection for various purposes equally acceptable or non-acceptable. Policymakers can benefit from these findings to shape regulations and assess the effectiveness of already existing policies related to data collection practices like the GDPR, emphasizing the importance of transparency and disclosure requirements for businesses rather than focusing solely on the purpose of data collection. Suppliers of digital products can provide clear and concise disclosure about data usage, not being afraid that this information would drop acceptance.

Limitations

Our study has several limitations. In the absence of an alternative for the coefficient comparison test suitable for the mixed model in SAS, inferences on the differences between attribute levels were made based on direct comparisons of MWTP for specific attribute levels and market share simulations. Hence, the conditional logit model provided additional insights concerning the statistical significance of observed differences. This approach, however, does not account for the individual heterogeneity between respondents and is, therefore, inferior to mixed logit modeling. Further, one potentially important limitation of the DCE is the assumption of rationality, thus calling for control for behavioral biases.

As another limitation, we relied on two US mTurk samples for our study. Samples from online panels such as mTurk offer important advantages over student samples, as they are more diverse and more closely reflect the overall population (Buhrmester et al., 2011 ). However, while the effects observed in mTurk samples typically replicate in general population samples (Chandler et al.,  2019 ; Coppock et al.,  2018 ), mTurkers are still demographically different from the general US population, with samples being younger, more liberal, and better educated (Chandler et al.,  2019 ). This is also true for both of our samples. Further, 98% of the participants in our samples say they use social media, which is a higher rate than observed in the general population (Auxier, 2020 ). However, since our research question addresses a topic relevant to internet and social media users, we consider this sample adequate for our purposes. As previous research shows that mTurk-workers might be more sensitive about unanonymized data than a representative US sample (Kang et al.,  2014 ), we would expect our results to replicate in a general population sample since their privacy concerns could be even lower. Although we took precautions to ensure data quality (Buhrmester et al.,  2011 ), further research is needed to show if our results hold for other samples like general population samples. Further, a cross-cultural comparison with European attitudes could be informative to provide a deeper understanding of users’ concerns. In addition, adding different examples of targeted political advertising that also address the specific nature of negative political advertising could potentially be of interest. In this paper, we deliberately avoided those examples to mitigate the potential effects of partisanship, yet future research could loosen this restriction. Together, these limitations offer exciting venues for future research.

A vast majority of digital products rely heavily on personal data, simultaneously posing a threat to the users’ privacy. We respond to the heated public debate around employing user data for politically targeted advertisements and the European Union’s General Data Protection Regulation (GDPR), which advocates for users' rights to be informed about the purpose of their data use. A vignette survey and a discrete choice experiment show that targeted political vs. product advertisements result in insignificant differences in privacy concerns and preferences for digital products. We confirm significant user preference for untargeted ads over targeted ads regardless of domain. While publicly displayed preferences towards political targeting in ads are very negative, revealed choices point to insignificant differences compared to targeting for commercial purposes.

While “traditional” targeted online ads can be used to promote products, services, brands, and/or companies, in this study we refer to these commercial uses as “product ads” to simplify the presentation.

Available here: https://osf.io/3knuv/?view_only=2e7b28a8fce04e85a5034d7e6a2108a8 .

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Acknowledgements

This article is an extended version of the ECIS paper ( https://aisel.aisnet.org/ecis2019_rp/77/ ). The authors would like to thank Prof. Dr. Shahriar Akter, who served as Associate Editor, and two anonymous reviewers for their constructive comments.

Open Access funding enabled and organized by Projekt DEAL. This work has been partially funded by the Federal Ministry of Education and Research of Germany (BMBF) under grant no. 16DII131 and grant no. 16DII116 (“Deutsches Internet-Institut”).

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Deep data — and big money — are driving a new era in political advertising

TV ads shaped by social science-based testing can have a powerful impact on voter attitudes, new research finds. But that comes with challenges for U.S. democracy.

By Edward Lempinen

Novel new experiments are helping to hone political advertisements for maximum impact, according to new research co-authored at UC Berkeley. A good ad, versus an average ad, can be powerful enough to swing the outcome of an election, the study says.

In the rarefied realm of political campaigns, every election brings complex challenges to the experts who shape a candidate’s advertising strategy. Their standard practice has been to show prospective ads to a small focus group, get feedback, and then follow their instincts to choose the best ads.

But according to a new study co-authored at UC Berkeley, even experienced consultants don’t reliably know what works, and the impact of their television ads is unpredictable. As a result, the researchers say, campaigns today are investing millions of dollars in rigorous, science-based experiments on how potential voters’ attitudes and behavior change in response to specific ads.

Broockman, in an interview, said ads developed with these new content-shaping systems can “easily double the effectiveness of their advertising spending” — and be enough to swing the outcome of a close election.

At the same time, the dramatic evolution in such persuasion tools has “important implications for American elections and democracy,” the authors write. “Because experimentation allows campaigns to increase the effectiveness of their advertising spending, experimentation increases the influence of money in elections, with benefits that redound principally to the best-funded campaigns.”

The new research — “How experiments help campaigns persuade voters: evidence from a large archive of campaigns’ own experiments” — was published online in the American Political Science Review on Feb. 9, 2024. The study follows another article co-authored by Broockman, released last fall, which found that campaign experts generally “have poor intuitions about how to persuade.”

Old-school political ads: art, science — and guesswork?

In the interview, Broockman described political communication practices that have been standard in recent decades. Experts would produce an advertisement, using their experience to guide key decisions. For example: Focus on policy, or the candidate’s personality? Use a celebrity messenger, or the voices of common folk? Use positive messaging, or go negative?

They would then assemble a focus group of 10 or 15 people who might represent that target audience — union members, perhaps, or suburban soccer moms or young voters. They would show that ad to the focus group, get reactions, then tweak the ad based on the response.

The process relied heavily on the experts’ gut instincts.

For their study, Broockman and his co-authors reached an agreement with Swayable , one of the firms that offers “creative testing” of political content before it is released to the public.

The company provided access to data on 617 advertisements prepared by 51 political campaigns in 2018 and 2020, including the 2020 presidential campaign. The researchers knew that all of the ads were for Democratic candidates, but the data otherwise did not reveal the candidates’ identities. In all, more than a half-million potential voters reviewed the ads for Swayable.

What Broockman and his colleagues found is that most of the old assumptions about effective campaign communication did not hold up to scrutiny.

The problem, he said, is that in any election year, the context of any individual race is constantly changing. The issues change, or the mood of the voters changes. Candidates’ attacks and defenses change based on the prominent issues, the climate or on sudden, one-time developments.

“Is it better to focus on the candidate’s policies or personality?” Broockman asked. “Is it better to have a testimonial, or not? What we’re finding — from the big picture to the stuff in the weeds — is that there is no answer. Because the answer basically changes all the time.”

The authors used Swayable data to develop a complex, full-page table showing how dozens of different factors registered on voters’ attitudes and voting decisions. The results were striking.

For example, in the 2018 races for U.S. House and Senate seats, ads focusing on issues were highly effective. Two years later, though, as President Donald Trump was challenged by Democrat Joe Biden, issue-based ads didn’t have the same effect on voters’ decisions in the presidential race or in congressional races.

Having a woman as the “messenger” in ads had a significant impact on voter attitudes and voting decisions in the 2020 Trump-Biden match, but wasn’t important in down-ballot contests. Ads that were “pushy” were effective in the presidential vote, but again, not in the down-ballot races.

A better ad can win a close race

The old approach seems almost quaint compared to the high-speed, data-driven experimentation now emerging.

Data-driven analysis done by Swayable and other companies is valuable because it can tease out even subtle impacts from advertising and do it quickly enough to have an almost immediate impact on the race.

Broockman offered an illustration: A campaign team develops a batch of ads, then takes them to specialty firms, such as Swayable, for evaluation. The firms assemble thousands of viewers to watch each iteration, and often within 24 hours, these social science experiments can discern which of the ads has the most power to persuade.

If factors in the 2018 and 2020 elections were shifting and inconsistent, then social science experimentation to sharpen persuasion campaigns has enormous value. “Choosing an above-average ad over a below-average ad could still easily determine the outcome of a close election,” the authors wrote.

That’s why they emphasized that the emerging tools amplify the effect of money on the political system. “Campaigns may increasingly have success at finding ads that persuade,” they argued, “but the benefits of this technology accrue principally to the campaigns with the financial resources to deploy the ads they select at the greatest scale.”

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Computer Science > Computation and Language

Title: analyzing online political advertisements.

Abstract: Online political advertising is a central aspect of modern election campaigning for influencing public opinion. Computational analysis of political ads is of utmost importance in political science to understand the characteristics of digital campaigning. It is also important in computational linguistics to study features of political discourse and communication on a large scale. In this work, we present the first computational study on online political ads with the aim to (1) infer the political ideology of an ad sponsor; and (2) identify whether the sponsor is an official political party or a third-party organization. We develop two new large datasets for the two tasks consisting of ads from the U.S.. Evaluation results show that our approach that combines textual and visual information from pre-trained neural models outperforms a state-of-the-art method for generic commercial ad classification. Finally, we provide an in-depth analysis of the limitations of our best-performing models and linguistic analysis to study the characteristics of political ads discourse.

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Expert Commentary

Negative political ads and their effect on voters: Updated collection of research

2016 updated review of scholarship and resources related to negative campaign advertising and its effects.

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway and John Wihbey, The Journalist's Resource September 25, 2016

This <a target="_blank" href="https://journalistsresource.org/politics-and-government/negative-political-ads-effects-voters-research-roundup/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

Many people have a visceral reaction to political attack ads on TV: Not much will prompt a faster change of the channel. But they are difficult to escape during election season and the 2016 presidential election season won’t be much different. Political ads became  much more negative over the course of the 2012 presidential campaign. Erika Franklin Fowler, an assistant professor of government, has noted that 2012 may be remembered for its record-setting negativity . Fowler directs t he Wesleyan Media Project , which monitors and analyzes televised campaign ads and found that three-quarters of ads aired during the last presidential race “appealed to anger.”

The 2016 presidential election already has become a nasty one, however. A September 2016 report  from the Wesleyan Media Project shows that 53 percent of ads that aired over the previous month were negative — compared to 48 percent of ads that ran during a comparable period of the 2012 campaign. The report notes that Hillary Clinton and Donald Trump have taken different approaches with their advertising: “Just over 60 percent of Clinton’s ads have attacked Trump while 31 percent have been positive, focusing on Clinton. Trump, on the other hand, has by and large used contrast ads, which both promote himself and attack Clinton. He has aired no positive ads.”

Journalists writing about the 2016 race can find a searchable and shareable archive of 2016 primary election ads through the  Political TV Ad Archive , an initiative funded by a Knight News Challenge grant.

The Wesleyan Media Project compiled the following chart to show how political advertising has become distinctly more negative over the past few election cycles:

In a May 2013 post for “The Monkey Cage,” a leading political science blog, John Sides of George Washington and Lynn Vavreck of UCLA summarize their research on the 2012 campaign. With regard to advertising, they conclude that ads mattered but only in “very circumscribed ways” and the “effect of ads appeared to decay quickly.” Further, they assert that “back-loading — airing ads close to the election — was actually more effective than front-loading — airing ads early in the campaign — if the goal was to influence voters on Election Day.”

Of course, the apparent rising volume and intensity of negative ads may reflect legal changes in how campaigns are funded in a post- Citizens United landscape. A related 2013 study in The Forum by Michael Franz of Bowdoin, “Interest Groups in Electoral Politics: 2012 in Context, ” provides additional analysis and data relating to the role of outside groups in the most recent ad wars. In another May 2013 post for “The Monkey Cage,” Franz examines data suggesting that the type and potentially lower quality of ads by outside groups may have played a role in the election. The Romney campaign’s “reliance on outside spending put a significant burden on those groups to produce and air ads that could resonate with voters. They may have done so — we need more research on this — but they may have also produced ads that were far less effective at mobilizing or persuading voters.”

From a historical perspective, it is worth considering, too, that increased news media focus on negative advertising itself has helped accelerate this trend , creating a vicious cycle of attack politics driven by political consultants and journalists.

With its FlackCheck.org site, the Annenberg Public Policy Center at the University of Pennsylvania aims to help the public recognize flaws in arguments, including those made in political ads. See some of the typical video techniques of political deception and misdirection:

Political scientists have long been studying the effects of negative ad campaigns on voter opinion, and many analysts focused on how campaign 2012 was affected. But scholars have complicated the simplistic view that negative ads “work” as a general rule. During the 2012 campaign, the Washington Post wrote about five commonly held “myths” about campaign ads , while the New York Times analyzed the specific circumstances when ads matter and their design and effects . At a deeper level, such ads may work to both “shrink and polarize the electorate,” as the political scientists Shanto Iyengar of Stanford and Stephen Ansolabehere of Harvard have long pointed out .

Aggregated below are some of the more recent and/or influential academic studies on the topic:

“Attacks Without Consequence? Candidates, Parties, Groups, and the Changing Face of Negative Advertising” Dowling, Conor M.; Wichowsky, Amber. American Journal of Political Science , 2015, Vol. 59. doi: 10.1111/ajps.12094.

Abstract: “Prior work finds that voters punish candidates for sponsoring attack ads. What remains unknown is the extent to which a negative ad is more effective if it is sponsored by a party or an independent group instead. We conducted three experiments in which we randomly assigned participants to view a negative ad that was identical except for its sponsor. We find that candidates can benefit from having a party or group ‘do their dirty work,’ but particularly if a group does, and that the most likely explanation for why this is the case is that many voters simply do not connect candidates to the ads sponsored by parties and groups. We also find that in some circumstances, a group-sponsored attack ad produces less polarization than one sponsored by a party. We conclude by discussing the implications our research has for current debates about the proper role of independent groups in electoral politics.”

“Liar, Liar, Pants on Fire: How Fact-Checking Influences Citizens’ Reactions to Negative Advertising” Fridkin, Kim; Kenney, Patrick J.; Wintersieck, Amanda. Political Communication , 2015, Vol. 32. doi: 10.1080/10584609.2014.914613.

Abstract: “Electoral campaigns are dynamic and an important change in recent elections is the growth of fact-checking; the assessment of the truthfulness of political advertisements by news media organizations and watchdog groups. In this article, we examine the role that fact-checks play in shaping citizens’ views of negative commercials and political candidates. We rely on an Internet survey experiment where we vary people’s exposure to negative advertisements and a follow-up fact-check article (i.e., no fact-check, accurate fact-check, inaccurate fact-check). The results of our experiment show that fact-checks influence people’s assessments of the accuracy, usefulness, and tone of negative political ads. Furthermore, sophisticated citizens and citizens with low tolerance for negative campaigning are most responsive to fact-checks. The fact-checks also sway citizens’ likelihood of accepting the claims made in the advertisements. Finally, negative fact-checks (e.g., fact-checks challenging the truthfulness of the claims of the negative commercial) are more powerful than positive fact-checks.”

“Gender Differences in Reactions to Fact Checking of Negative Commercials” Fridkin, Kim L.; Courey, Jillian; Hernandez, Samatha; Spears, Joshua. Politics & Gender , June 2016, Vol. 12. doi: http://dx.doi.org/10.1017/S1743923X16000076 .

Summary: This study from researchers at Arizona State University suggests that fact checking can reduce the impact of negative advertising but that men and women differ in their receptivity to fact checking. “Women are likely to view negative commercials as less useful and less accurate when they are exposed to a fact check challenging the facts presented in an attack advertisement. Perhaps more importantly, women are also less likely to believe the claims in negative commercials when they view a fact check challenging the advertisement’s claims. Men, in contrast, are less likely to be influenced by fact checks refuting the assertions made in a negative commercial.”

“Going Positive: The Effects of Negative and Positive Advertising on Candidate Success and Voter Turnout” Malloy, Liam C; Pearson-Merkowitz, Shanna. Research and Politics , January-March 2016. doi: 10.1177/2053168015625078.

Abstract: “Given the depth of research on negative advertising in campaigns, scholars have wondered why candidates continue to attack their opponents. We build on this research by considering real-world campaign contexts in which candidates are working in competition with each other and have to react to the decisions of the opposing campaign. Our results suggest that it is never efficacious for candidates to run attack ads, but running positive ads can increase a candidate’s margin of victory. These results are conditioned by two factors: candidates must both stay positive and out-advertise their opponent. Second, the effects of positive advertising are strongest in areas where the candidate is losing or winning by a large margin — areas where they might be tempted to not advertise at all.”

“Who’s Afraid of Conflict? The Mobilizing Effect of Conflict Framing in Campaign News” Schuck, Andreas R.T.; Vliegenthart, Rens; De Vreese, Claes H. British Journal of Political Science , January 2016, Vol. 46. doi: 10.1017/S0007123413000525.

Abstract: “The ability of the news media to mobilize voters during an election campaign is not well understood. Most extant research has been conducted in single-country studies and has paid little or no attention to the contextual level and the conditions under which such effects are more or less likely to occur. This study tests the mobilizing effect of conflict news framing in the context of the 2009 European Parliamentary elections. The unique multi-method and comparative cross-national study design combines a media content analysis (N = 48,982) with data from a two-wave panel survey conducted in twenty-one countries (N = 32,411). Consistent with expectations, conflict framing in campaign news mobilized voters to vote. Since the effect of conflict news was moderated by evaluations of the EU polity in the general information environment, conflict framing more effectively mobilized voters in countries where the EU was evaluated more positively.”

“Seeing Spots: An Experimental Examination of Voter Appetite for Partisan and Negative Campaign Ads” Henderson, John A.; Theodoridis, Alexander G. July 2015. SSRN-id2629915.

Abstract:   “We utilize a novel experimental design to assess voter selectivity to political advertising. We randomly expose respondents to comparable positive or negative ads aired by Democratic or Republican candidates from the 2012 Presidential race and the 2013 Virginia Gubernatorial contest. The experiment closely mirrors real consumption of campaign information by allowing subjects to skip ads after five seconds, re-watch and share ads with friends. Using these measures of ad-seeking behavior, we find little evidence that negativity influences self-exposure to election advertising. We find partisans disproportionately tune out ads aired by their party’s opponents, though this behavior is asymmetric: Republican-identifiers are more consistent screeners of partisan ads than Democrats. The results advance our understanding of selectivity, showing that party source, and not ad tone, interacts with partisanship to mediate campaign exposure. The findings have important implications about the role self-exposure to information plays in campaigns and elections in a post-broadcast era.”

“The Effects of Negative Political Campaigns: A Meta-Analytic Reassessment” Lau, Richard R.; Sigelman, Lee; Rovner, Ivy Brown. Journal of Politics , 2007, Vol. 69, Issue 4, 1176-1209. doi: 10.1111/j.1468-2508.2007.00618.x.

Abstract: “The conventional wisdom about negative political campaigning holds that it works, i.e., it has the consequences its practitioners intend. Many observers also fear that negative campaigning has unintended but detrimental effects on the political system itself. An earlier meta-analytic assessment of the relevant literature found no reliable evidence for these claims, but since then the research literature has more than doubled in size and has greatly improved in quality. We reexamine this literature and find that the major conclusions from the earlier meta-analysis still hold. All told, the research literature does not bear out the idea that negative campaigning is an effective means of winning votes, even though it tends to be more memorable and stimulate knowledge about the campaign. Nor is there any reliable evidence that negative campaigning depresses voter turnout, though it does slightly lower feelings of political efficacy, trust in government and possibly overall public mood.”

“A Framework for Dynamic Causal Inference in Political Science” Blackwell, Matthew. American Journal of Political Science , April 2013, Vol. 57. doi: 10.1111/j.1540-5907.2012.00626.x.

Abstract: “Dynamic strategies are an essential part of politics. In the context of campaigns, for example, candidates continuously recalibrate their campaign strategy in response to polls and opponent actions. Traditional causal inference methods, however, assume that these dynamic decisions are made all at once, an assumption that forces a choice between omitted variable bias and post-treatment bias. Thus, these kinds of ‘single-shot’ causal inference methods are inappropriate for dynamic processes like campaigns. I resolve this dilemma by adapting models from biostatistics to estimate the effectiveness of an inherently dynamic process: a candidate’s decision to ‘go negative.'” To simplify the analysis, the study looked only at Democratic candidates in U.S. Senate and Gubernatorial elections from 2002 to 2006. It found that, in contrast to earlier research, that negative advertising could be an effective strategy for challengers, while incumbents were hurt by going negative.

“Messages that Mobilize? Issue Publics and the Content of Campaign Advertising” Sides, John; Karch, Andrew. The Journal of Politics , April 2008, Vol. 70, Issue 2, 466-476.

Findings: Targeted campaign ads appear to have only a small measurable effect on groups: “In three election years, we found no consistent evidence that messages related to Social Security and Medicare were associated with higher turnout among seniors or that messages related to veterans were associated with higher turnout among veterans.” Groups such as parents did seem to be mobilized by targeted ads, but the effects may be so small as to be extraordinarily expensive to exploit, with diminishing returns. In one media market, it took more than 4,000 ads to make turnout just 6.4% more likely among parents; in a more lightly advertised market, just 322 spots resulted in a 3.8% increased likelihood in turnout. This means that to achieve a further 2.6 percentage points in likely turnout, the “number of newly mobilized parents yields a cost-per-vote of $282. This is roughly 15 times the average cost-per-vote of door-to-door get-out-the-vote efforts.” Because targeted ads appear to have limited effectiveness, they don’t exacerbate differences in turnout rates between groups. “The participatory tendencies of senior citizens and veterans do not increase when campaigns focus on entitlements and veterans’ benefits, respectively.”

“Variability in Citizens’ Reactions to Different Types of Negative Campaigns” Fridkin, Kim L.; Kenney, Patrick. American Journal of Political Science , 2011, Vol. 55, Issue 2, 307-325. doi: 10.1111/j.1540-5907.2010.00494.x.

Findings: Voters’ tolerance for negative campaigns and political rhetoric depends on individual characteristics: Those with a strong party affiliation and a deep interest in the campaign tend to be more tolerant and their impressions of candidates were not as deeply influenced by negativity. Men are more tolerant than women of negative content, while older respondents are less tolerant. Overall, “people who do not like uncivil and irrelevant discourse in negative communication are more responsive to the variation in the content and tone of negative commercials. These messages directly influence their assessments of incumbents and challengers. This finding stands in stark contrast to those people who are unperturbed by messages presented in an uncivil manner.” Three variables — relevance of message, degree of civility and the tolerance level of the voter — interact in complex ways and determine whether or not negative campaigns “work.” In other words, there is no simple, universal answer: In some cases negative campaigns can have substantial effects on voter impressions; in others, the effect is negligible.

“The Implicit and Explicit Effects of Negative Political Campaigns: Is the Source Really Blamed?” Carraro, Luciana; Castelli, Luigi. Political Psychology , August 2010, Vol. 31, Issue 4, 617-645. doi: 10.1111/j.1467-9221.2010.00771.x.

Abstract: “Despite the widespread use of negative campaigns, research has not yet provided unambiguous conclusions about their effects. So far studies, however, have mainly focused on very explicit measures. The main goal of the present work was to explore the effects of different types of negative campaigns on both implicit and explicit attitudes, as well as in relation to two basic dimensions of social perception, namely competence and warmth. Across a series of three studies, we basically showed that not all negative campaigns lead to the same consequences. Specifically, especially personal attacks toward the opposing candidate may backfire at the explicit level…. Overall, it appeared that negative messages decreased the perceived warmth of the source while simultaneously increasing the perceived competence. Results are discussed by focusing on the importance of implicit measures in political psychology and on the crucial role of perceived competence.”

“Do Voters Perceive Negative Campaigns as Informative Campaigns?” Sides, John; Lipsitz, Keena; Grossman, Matthew. American Politics Research , 2010, Vol. 38, No. 3, 502-530. doi: 10.1177/1532673X09336832.

Findings: Voters tend to separate a campaign ad’s tone from whether they believe it to be informative: many voters will (correctly) perceive a campaign as negative but will also believe that it is providing truthful information. “These dimensions appear to be separate constructs in citizens’ minds.” Voters can accurately perceive whether a campaign is negative, and such judgment is not just a matter of which candidate they prefer. “Public perceptions of negativity do in fact respond to reality.” The degree of a campaign’s negativity as reflected in advertising has little bearing on whether voters believe it is informative. “There was no relationship between the volume of negative appeals and beliefs about whether the candidates were providing useful information or discussing policy issues.”

“Comparing Negative and Positive Campaign Messages: Evidence From Two Field Experiments” Arceneaux, Kevin; Nickerson, David W. American Politics Research , January 2010, Vol. 38, No. 1, 54-83. doi: 10.1177/1532673X09331613.

Abstract: “Considerable research indicates that personal contact from political campaigns can mobilize people to vote, but little attention has been given to whether the tone of the message matters. Studies of message tone have mostly been confined to mass media campaigns and ignored the growing role grassroots techniques play in contemporary political campaigns. Two randomized field experiments were conducted to determine the importance of message tone in grassroots contact. We find evidence that personally delivered messages can be effective at influencing voting preferences, but neither experiment uncovered a systematic difference between the effects of negative and positive messages on voter turnout or political attitudes.”

“The Role of Candidate Traits in Campaigns” Fridkin, Kim L.; Kenney, Patrick, J. Journal of Politics , January 2011, Vol. 73, Issue 1, 61-73. doi: 10.1017/S0022381610000861.

Abstract: “We examine how candidates shape citizens’ impressions of their personal traits during U.S. Senate campaigns. We look at the personality traits emphasized by candidates in their controlled communications and in news coverage of their campaigns. We couple information about campaign messages with a unique survey dataset allowing us to examine voters’ understanding and evaluations of the candidates’ personalities. We find that messages from the news media influence people’s willingness to rate the candidates on trait dimensions. In addition, negative trait messages emanating from challengers and the press shape citizens’ impressions of incumbents. In contrast, voters’ evaluations of challengers are unmoved by campaign messages, irrespective of the source or tone of the communications. Finally, we find citizens rely heavily on traits when evaluating competing candidates in U.S. Senate campaigns, even controlling for voters’ party, ideological and issue preferences.”

“The Seeds of Negativity: Knowledge and Money” Lovett, Mitchell J.; Shachar, Ron. Marketing Science , 2011, Vol. 30, No. 3, 430-446. doi: 10.1287/mksc.1110.0638.

Abstract: “This paper studies the tendency to use negative ads. For this purpose, we focus on an interesting industry (political campaigns) and an intriguing empirical regularity (the tendency to “go negative” is higher in close races). We present a model of electoral competition in which ads inform voters either of the good traits of the candidate or of the bad traits of his opponent. We find that in equilibrium, the proportion of negative ads depends on both voters’ knowledge and the candidate’s budget. Furthermore, for an interesting subset of the parameter space, negativity increases in both knowledge and budget.”

“When Does Negativity Demobilize? Tracing the Conditional Effect of Negative Campaigning on Voter Turnout” Krupnikov, Yanna. American Journal of Political Science , 2011, Vol. 55, Issue 4, 797-813. doi: 10.1111/j.1540-5907.2011.00522.x.

Abstract: “Do negative campaign advertisements affect voter turnout? Existing literature on this topic has produced conflicting empirical results. Some scholars show that negativity is demobilizing. Others show that negativity is mobilizing. Still others show that negativity has no effect on turnout. Relying on the psychology of decision making, this research argues and shows that this empirical stalemate is due to the fact that existing work ignores a crucial factor: the timing of exposure to negativity. Two independent empirical tests trace the conditional effect of negativity. The first test relies on data from the 2004 presidential campaign. The second test considers the effect of negativity over a broader period of time by considering elections 1976 to 2000. Taken together, both tests reinforce that negativity can only demobilize when two conditions are met: (1) a person is exposed to negativity after selecting a preferred candidate and (2) the negativity is about this selected candidate.”

“The Influence of Tone, Target and Issue Ownership on Political Advertising Effects in Primary Versus General Elections” Meirick, Patrick C., et al. Journal of Political Marketing , 2011, Vol. 10, Issue 3. doi: 10.1080/15377857.2011.588111.

Abstract: “The conventional wisdom in the literature about political advertising effects — e.g., going negative risks backlash, stick to issues your party owns — has been derived from studies of general elections. Much less attention has been paid to primary elections, in which a partisan audience may be receptive to attacks on the opposing party and may judge most issues to be handled better by their own party. This experiment (N = 223) sets out to investigate the roles of tone (positive versus comparative), target (none, primary opponent, or general election opponent), and issue ownership (party-owned issue or unowned issue) in responses to political advertising during primary versus general elections. As predicted, partisans in primary election conditions had lower ad and sponsoring candidate evaluations for comparative ads attacking a primary opponent than for positive ads or comparative ads attacking the eventual general election opponent, but there were no differences between the latter two. Independents in the general election conditions responded more positively to positive ads than comparative ads. Issue ownership had no main effects.”

“A Negativity Gap? Voter Gender, Attack Politics, and Participation in American Elections” Brooks, Deborah Jordan. Politics & Gender , 2010, Vol. 6, Issue 3, 319-341. doi: http://dx.doi.org/10.1017/S1743923X10000218.

Findings:  Men are more likely to be motivated to vote by a negative campaign message. Highly negative campaigns saw the “biggest gender differences: an 88% probability of voting for men and just a 77% probability of voting for women.” In contests with the least amount of negative campaigning, “women are slightly higher than men in terms of predicted probability of going to the polls.” There is a further distinction between “civil” versus “uncivil” (“inflammatory, gratuitous, and divisive”) negative messaging. Comparing men’s and women’s reactions along these lines reveals further gender gaps: “Men are disproportionately mobilized by uncivil negativity as compared to women [and] women appear to be slightly more likely than men to vote after viewing civil negative messages.” After viewing uncivil negative ads, only 9% of men said they would definitely not vote, while 21% of women said they would not.

“The Mass Media and the Public’s Assessments of Presidential Candidates, 1952-2000” Gilens, Martin ; Vavreck, Lynn; Cohen, Martin. The Journal of Politics , November 2007, Vol. 69, Issue 4, 1160-1175. doi: 10.1111/j.1468-2508.2007.00615.x.

Abstract: “Media critics blame contemporary news for increasing levels of apathy and ignorance among the electorate. We agree that the amount of policy-oriented information in news coverage of presidential campaigns has declined and the level of news consumption has fallen. Yet, based on 50 years of data on media content and public attitudes, we find that over this period of time Americans have just as much to say about the major-party presidential candidates, what they have to say is more policy oriented, the association of vote choice with policy considerations has strengthened while the association with character considerations has weakened, and factual knowledge about the presidential candidates’ issue positions has not declined. We assess the role of education, party polarization, and paid advertising in explaining trends in Americans’ political knowledge and engagement. We show that the public’s steady level of information and increased focus on policy in presidential politics reflects the high level of policy content in paid ads, which have compensated for the shift of news coverage toward candidate character, scandal, and the horse race.”

Tags: elections, campaign ads, research roundup, tweeting, social media, fact checking

About the Authors

Denise-Marie Ordway

John Wihbey

Letitia James

Attorney general james secures more than $10 million from at&t, t-mobile, and verizon wireless for deceptive advertising, multistate investigation found that wireless service providers misled millions of americans with deceptive ads about “unlimited” data plans and “free” phones, may 9, 2024.

NEW YORK – New York Attorney General Letitia James and a multistate, bipartisan coalition of 50 attorneys general today secured more than $10.22 million from AT&T Mobility, LLC and its subsidiary Cricket Wireless, LLC (AT&T); T-Mobile USA, Inc. (T-Mobile); and Cellco Partnership d/b/a Verizon Wireless and its subsidiary TracFone Wireless, Inc. (Verizon), for deceptively marketing wireless service plans for years. A multistate investigation found that the companies made false claims in advertisements in New York and across the nation, including misrepresentations about “unlimited” data plans that were in fact limited and had reduced quality and speed after a certain limit was reached by the user. The companies will pay $520,000 to New York and are required to change their advertising to ensure that wireless service plans are accurately and fairly explained.

“New Yorkers, and all Americans, deserve to know that when they buy a service or product, they will be treated fairly and can trust what the seller is saying,” said Attorney General James . “AT&T, Verizon, and T-Mobile lied to millions of consumers, making false promises of free phones and ‘unlimited’ data plans that were simply untrue. Big companies are not excused from following the law and cannot trick consumers into paying for services they will never receive. We will continue to go after companies that hurt everyday Americans and try to take advantage of this basic and critical service.”  

The multistate investigation found that the wireless companies made several misleading claims in their advertising, including misrepresenting “unlimited” data plans that were actually limited, offering “free” phones that came at a cost, and making false promises about switching to different wireless carrier plans. These advertisements, which were broadcast on TV and online, lured consumers to sign up for plans that did not live up to their promises and that typically failed to disclose key limitations, restrictions, or details.

Today’s agreement requires the wireless service providers to pay $10,224,135 to the states and improve their advertising and marketing of their services to consumers. The wireless services providers are required to ensure that: 

• All advertisements and representations are truthful, accurate, and non-misleading; 
• “Unlimited” mobile data plans can only be marketed if there are no limits on the quantity of data allowed during a billing cycle; 
• Offers to pay for consumers to switch to a different wireless carrier must clearly disclose how much a consumer will be paid, how consumers will be paid, when consumers can expect payment, and any additional requirements consumers have to meet to get paid; 
• Offers of “free” wireless devices or services must clearly state everything a consumer must do to receive the “free” devices or services; 
• Offers to lease wireless devices must clearly state that the consumer will be entering into a lease agreement; and 
• All “savings” claims must have a reasonable basis. If a wireless carrier claims that consumers will save using its services compared to another wireless carrier, the claim must be based on similar goods or services or differences must be clearly explained to the consumer. 

In addition, the companies must appoint a dedicated representative to work with the attorneys general to address ordinary complaints filed by consumers. They must also train their customer service representatives to comply with the terms of the agreement and implement and enforce a program to ensure compliance.

Joining Attorney General James in today’s agreement are the attorneys general of Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Georgia, Hawai’i, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming, and the District of Columbia.

For New York, the investigation and settlement discussions were led by Assistant Attorneys General Noah Popp and Kate Matuschak of the Consumer Frauds and Protection Bureau under the supervision of Deputy Bureau Chief Laura J. Levine and Bureau Chief Jane M. Azia. The Consumer Frauds Bureau is part of the Division of Economic Justice, which is led by Chief Deputy Attorney General Chris D’Angelo and overseen by First Deputy Attorney General Jennifer Levy.

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