Last week we tentatively examined the link between poor user experience with ads and a rise in the levels of internet users who are installing ad-blocking software. Now we place ad-blocking under the microscope and really try to gain insight as to why users install such software. Ad avoidance is defined as “all actions by media users that differentially reduce their exposure to ad content” (Speck, 1997). It is not concept that emerged with the digital era: ‘zapping’ between channels on TV, changing the frequency on the radio or quickly flipping pages in the Newspaper are all forms of traditional ad avoidance, which were subject of much research.
Adblock falls under the umbrella of ‘mechanical ad-avoidance‘ – similar to channel zapping, technology i.e. a remote mitigates against ad-exposure (Speck, 1997). Ever since the original ad-block was released in 2006 we’ve been gifted an easy mechanism to simply switch off the ads served to us. Ominously for the entire web ecosystem, year-on-year growth for AdBlock installation was 41% for the period between Q2 2014 and Q2 2015 (An, 2016).
The vast majority of sites, social networks and other means of digesting content, coupled with our interactions with them form the individual components of an ‘Attention-economy’. A term first coined by Herbert A. Simon whereby he envisioned that we would drown in a deep ocean of information where the only scarcity would be our capacity to absorb all the available information (Simon, 1978). Despite writing over thirty-years ago, we can draw many parallels to the present day. One could argue that the entire infrastructure on which the web is built and designed on has been built to treat our attention as a severely lacking commodity and exploits it to maximise the performance of advertisements. All of the KPIs for publishers, Facebook and YouTube are all based around metrics of consumption and features such as auto-playing videos are heralded as improvements to the product, in actual fact they incarcerate users further serving up more and more ads.
Take a news article. A user clearly wants to devote full attention to digesting the article, but contrary to the user’s desire the site is designed to do their utmost to divert their user’s attention to ads. Many will argue that banner ads are pointless because users have developed a subconscious ability to completely ignore them in a phenomenon dubbed ‘Banner Blindness’. However, research has found that we massively underestimate the effect that low exposure has on our purchasing behaviour: contrary to what most believe, consumers do notice static ads, and they do lead to purchases (Yongqiang, 2013). Moreover, consumers will subconsciously be processing these ads on a low-level and applying Information theory, the idea that we simply cannot process the desired content along with the accompanying noise on the page (Seyedghorban, 2015). This cognitive fatigue is detrimental to user experience on site, and in turn is associated with a user’s desire to resort to AdBlock. This manifests itself as one of the leading factors that is cited for users installing AdBlock: 73% of people that install AdBlock do so because ads are interruptive in that they impede on user’s goals whilst browsing the web (An, 2016).
Another school of thought cited significantly less comes from Uses and Gratification theory. Research carried gained insight as to why people move between channels throughout the duration of ad-breaks on TV, they found that some consumers found it gratifying to game the system (Speck, 1997). A concept that to my knowledge has not been explored in the literature, is the idea that we are beginning to observe a gamification of digital ad-avoidance. There is something quite gratifying about the process of loading a video on YouTube, feeling the frustration of seeing a two-minute advertisement begin to buffer, followed by the elation when you see that omnipotent skip-box. You begin to challenge yourself at how rapidly you can hit that button after those fateful six-seconds are up. In addition to this is the feature that is built within the AdBlock extension, there is a pop-up that enables you to see exactly how many ads you have blocked since installing it and even encourages you to share this number to various social networks. Consumers are being allowed to compete in a game amongst their social circles to block the most ads.
The current state of the market is that as consumers we have a cognitive dissonance towards advertisements; more often than not the claims in ads are rejected at face value because there’s a perception that marketing is present to deceive. Therefore, why waste any time watching ads that are automatically going to be rejected, when consumers could spend that time seeking out other content that fulfils either their cognitive needs or affective needs. It was found that those ads that offered playful or insightful content were far less likely to skipped – if that concept is examined in its roots, ads that offered some form of value to consumers were far better received, and had a higher chance of being viewed by the user. 68% of AdBlock users surveyed stated that they were fine seeing ads as long as they ‘weren’t annoying’ and that they understood that ads were needed in ordered to support the free content of the site (An, 2016).
Netflix, who now convey their messages via YouTube ads in six-seconds – they understand the delicate balance we need to get to in order to solve this problem. We need to stop abusing the attention-economy and the ideology that we can just continue to exploit the short attention spans of consumers. Companies that recognise consumer frustration and innovate accordingly are destined for success.
Speck, P. S., & Elliott, M. T. (1997). Predictors of Advertising Avoidance in Print and Broadcast Media. Journal of Advertising, 26(March 2015), 61–76.
Yongqiang, S., Lim, K. H., & Jerry Zeyu, P. (2013). Solving the Distinctiveness – Blindness Debate: A Unified Model for Understanding Banner Processing. Journal of the Association for Information Systems, 14(2), 49–71.
Seyedghorban, Z., Tahernejad, H., & Matanda, M. J. (2015). Reinquiry into Advertising Avoidance on the Internet: A Conceptual Replication and Extension. Journal of Advertising, 3367(November), 1–10.
An, M. (2016). What’s the Deal With Ad Blocking? 11 Stats You Need to Know. [online] Blog.hubspot.com. Available at: http://blog.hubspot.com/marketing/ad-blocking-stats#sm.000yd4pxjfx9ew311jc2ifw9zwchp [Accessed 9 Nov. 2016].