In consumer class actions involving allegations of deceptive or false advertising, plaintiffs may allege that a company misrepresented benefits or omitted information about a product in advertisements. In these cases, plaintiffs often claim that consumers relied upon said misrepresentations or omissions when deciding to purchase the at-issue product.
One issue that is often overlooked in deceptive or false advertising cases is consumers’ ability to avoid viewing contested ads. Academics and marketing professionals have long recognized that consumers, for many reasons, frequently engage in ad avoidance.1
If consumers avoid advertisements either in part or entirely, then it may be important to account for this avoidance in any assessments of whether putative class members’ purchase decisions were influenced by the contested ads. For example, experts may rely on survey data to assess what portion of the target population was actually exposed to certain at-issue ads (and did not avoid them), and whether individuals who viewed the contested ads made different purchase decisions than respondents who viewed uncontested ads.
The prevalence of ad avoidance suggests that conclusions drawn from research methods that do not account for this behavior could lead to inflated estimates of the advertising’s influence on purchase decisions.
The prevalence of ad avoidance behavior suggests that conclusions drawn from research methods that do not account for such behavior could lead to inflated estimates of the portion of the population exposed to the contested ads as well as biased estimates of any impact of contested ads on purchase decisions.
Traditional and Online Advertising
Much of the groundbreaking research on ad avoidance was performed before widespread internet use.2 Ad avoidance behavior on traditional media channels, such as television and radio, can take on many different forms, including switching to another channel when an ad appears or reducing the volume of, or muting, the ad, or even mentally zoning out during the ad.3
As consumers spend more time online, new types of advertising have emerged, that, on first glance, may appear to be less susceptible to ad avoidance. Examples of online advertising include paid search engine ads, social media, display ads, pop-ups, native ads embedded in online original content, and video ads.4
For many of these, traditional ad avoidance strategies no longer apply. For instance, consumers who review a website with display advertising may be hesitant to close their browser window entirely to avoid an ad. Furthermore, consumers may be less prone to avoidance because marketers are able to target online ads to specific consumers, which may make the ads more appealing to their targets.
However, some current research on consumer experiences indicates that ad avoidance is common in the online realm and indeed may play a more important role for online ads than it does for traditional advertising. In fact, consumers now have access to technology solutions or special offerings that allow them to selectively or broadly avoid exposure to online advertisements.5 For example, a 2017 survey by Deloitte found that 30 percent of U.S. adults use an ad-blocking software that limits the display of certain ad types on their computers, and just under 20 percent use similar software to block ads on their smartphones.6 Similarly, while ad-supported music and video services such as YouTube include mandatory ad views, users may avoid additional ads by clicking on the “Skip Ad” button.
As of 2020, each U.S. household, on average, had access to over ten internet-connected devices.7 Moreover, according to a 2012 Google study, as many as 90 percent of U.S. consumers use multiple screens sequentially.8 Therefore, one popular method of avoiding online ads is by shifting attention from one screen to another screen or device.
Another form of online ad avoidance is “banner blindness,” the tendency among users to ignore elements of a web page that they either correctly or incorrectly perceive to be ads. Banner blindness is pervasive, with studies indicating that only 14 percent of internet users remember the last ad they saw, and only 8 percent recall the company or product that was promoted.9 In addition, email services like Gmail automatically filter or flag email content related to advertisements thus allowing users to avoid seeing advertisement-related emails.
Ad avoidance can also occur in online entertainment services. As of 2020, U.S. adults had, on average, premium subscriptions to twelve entertainment services.10 Unlike ad-supported free music and video services, premium (paid) versions reduce or eliminate advertisements altogether.
On social media, users may exercise available controls to limit exposure to ads that they deem irrelevant, effectively avoiding the ads. Thus, while consumers who use the internet to make purchases are exposed to an increasing number and variety of advertisements throughout their purchase decision journey, they also have access to a larger set of avoidance behaviors.
Considerations for Consumer Class Actions
Particularly relevant in the class action setting, ad avoidance behavior can differ substantially across consumers. For instance, while consumers in general are increasingly making purchases online, more tech-savvy consumers likely know better how to effectively leverage technology to avoid online ads than less tech-savvy consumers.
Findings from the Deloitte survey indicate that 17 percent of 18 to 34 year olds avoided multiple types of advertising, compared to less than 5 percent of adults 45 years and older.11 The survey also found that more educated users, those with higher incomes, and those currently employed are more likely to avoid ads. Any analysis of the impact (if any) of contested ads on purchase decisions in deceptive or false advertising matters may need to account for these differences in the context of the relevant population of consumers for a given product. For some individuals, online ad avoidance behavior will affect the likelihood of being exposed to the alleged deceptive advertising.
The views expressed herein do not necessarily represent the views of Cornerstone Research.
1 See, for example, Paul Speck and Michael Elliott, “Predictors of Advertising Avoidance in Print and Broadcast Media,” Journal of Advertising 26, no. 3 (1997): 61–76 (“Speck and Elliott (1997)”); Marjolein Moorman et al., “The Effects of Program Involvement on Commercial Exposure and Recall in a Naturalistic Setting,” Journal of Advertising 36, no. 1 (2007): 121–137.
2 See, for example, Speck and Michael Elliott (1997); Avery Abernathy, “Television Exposure: Programs vs. Advertising,” Current Issues and Research in Advertising 13, nos. 1–2 (1991): 61–77.
3 Other ad avoidance behaviors for traditional media channels include: using recording devices, such as DVRs, that can filter out ad content; multitasking and paying attention to other tasks when advertisements appear; and physically leaving the room with the television or radio when an ad comes on.
4 SendPulse, “What Is Internet Advertising? – Definition and Tips,” https://sendpulse.com/support/glossary/advertising.
5 See, for example, Chang-Hoan Cho and Hongsik J. Cheon, “Why Do People Avoid Advertising on the Internet?,” Journal of Advertising 33, no. 4 (2004): 89–97; Josh Chasin, “How Big Is Ad Avoidance?,” Advertising Research Foundation, June 6, 2018, https://thearf.org/category/articles/how-big-is-ad-avoidance/; Carlos Ferreira et al., “Social Media Advertising: Factors Influencing Consumer Ad Avoidance,” Journal of Customer Behaviour 16, no. 2 (2017): 183–201.
6 Deloitte, “Is There an #adlergic Epidemic? Ad Blocking across Media,” 2017, https://www2.deloitte.com/content/dam/Deloitte/global/Images/infographics/technologymediatelecommunications/gx-deloitte-tmt-2018-adblocking-media-report.pdf.
7 Martin Kokholm, “New Study: The Decline of the Computer Continues While Newer Devices Are on the Rise,” AudienceProject, March 26, 2020, https://www.audienceproject.com/blog/key-insights/new-study-the-decline-of-the-computer-continues-while-newer-devices-are-on-the-rise/.
8 Google/Ipsos/Sterling, “The New Multi-Screen World Understanding Cross-Platform Consumer Behavior,” 2012, https://www.thinkwithgoogle.com/consumer-insights/consumer-trends/multi-screen-world-infographic/.
9 Infolinks, “The Banner Blindness Infographic,” April 21, 2013, https://www.infolinks.com/blog/infographic/the-banner-blindness-infographic/.
10 The Statista 2021 study was conducted in the United States between December 2019 and January 2020. It included 2,103 respondents aged 18 years and older. Subscriptions include pay TV, streaming video/music, video games, audiobooks, and digital magazines/newspapers.
11 Deloitte, “Is There an #adlergic Epidemic? Ad Blocking across Media,” 2017, https://www2.deloitte.com/content/dam/Deloitte/global/Images/infographics/technologymediatelecommunications/gx-deloitte-tmt-2018-adblocking-media-report.pdf.
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