Mark Zuckerberg famously told his team that “a squirrel dying in your front yard may be more relevant to your interests right now than people dying in Africa” (Zuniga Navajas, 2015). What he referred to is the algorithms used by Facebook to personalize and shape its content to the preference model of each individual Facebook user. In Zuckerberg’s view, if a Facebook user has a passion for Squirrels, then Facebook’s mission is to create a personalized Facebook experience for this particular user centred around information about Squirrels.
Facebook is not the only company personalizing content and filtering information. As discussed by Parser in his now famous TED Talk (2011), a Google search for the term ‘Egypt’ made during the Arabic spring uproar performed by two of his friends yielded very different search results. As seen in below; for Scott (left), this search phrase returned information mainly about the uproar, while the search results for Daniel (right) returned only travel information.
News also is becoming highly driven by personalized content. According to Trendhunter.com (2017), people are turning away from traditional news-channels towards aggregation services such as News360 (2017) and Yahoo (2017) that filtering out news not directly corresponding to preferences defined by the user.
Content personalization, however, is not a new phenomenon. Marketers for a long time have understood the importance of adapting design and copy of sales messages to the preference model of target audiences which has formed the basis of much of today’s leading marketing literature including Kotler, Kartajaya and Setiawan (2017), Scott (2016) and Holiday (2014); not to forget David Ogilvys’ timeless classic ‘Ogilvy on advertising’ in which he states: “as a marketer you should use the language of the customers, the language they use every day, the language in which they think” (Ogilvy, 1985).
This quest by marketers to understand the particular needs and wants of audience segments is also well reflected in the exponential growth of the market research industry which according to the ‘Esomar Global Market Research Report 2016’ (Research Live, 2017) grew almost five percent in 2016 to 44.3 billion us dollars; money made from marketers desperate to understand how to communicate more efficiently through copy, design, and imagery.
With the growth of the internet, marketers also increasingly move from traditional channels to digital, and in 2016 digital ad-spending for the first time surpassed TV (Katz, 2017). This new paradigm of the advertising industry has given marketers access to an unprecedented amount of customer- and market data, and new possibilities to tailor design and content to narrow market segments—which in turn have generated an explosion of marketing tools for tracking customers, segmenting markets, and to personalize design and content; including Adobe Marketing Cloud (2017), Oracle Marketing Cloud (2017) and Optimizely (2017).
Advocates of personalization.
The advocates of a personalized web argue that content filtering is a necessity on an ever-growing Internet, and that web users without personalization algorithms would drown in the millions of new web pages published each day, basically not being able to locate information relevant to their searches and personal interests (Horling, 2009; Hicks, 2010; Hogg, 2017). Other proponents, including Trendhunter.com, go even further, claiming that content filtering “ultimately, gives consumers the power to move away from click-bait towards reliable, relevant information” (2017).
The loudest proponents of personalisation and content filtering, though, comes from the marketing space where personalization often is argued as the key to success and a critical factor for efficient communication, improved engagement, and to keep customers happy. Marketers such as Clutterbuck (2016) claims that a personalization of design and content is a necessity for any company wanting to survive in today’s competitive market, and that customers actually want their shopping- and advertising experiences to be personalized to their needs and wants.
Other proponents; including Entrepreneur.com, goes even further claiming that “people don’t want to be bombarded with irrelevant information” (2014), and that business owners who do not want to annoy customers need to personalize design and content of their communicative assets.
Voices against content filtering and web personalization.
In his 2014 best-seller ‘The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think’ (2014), Eli Pariser raises concerns about the implications of a personalized web.
In the book, he claims that market personalization strengthens confirmation biases about products, politics, and people around us by confirming existing beliefs. What Pariser is referring to, is the fact that the focus of personalization algorithms is to filter out information which users categorically have not asked for, and that you in a personalised web are more likely to get information confirming your pre-existing beliefs whether you think the world is flat (The Flat Earth Society, 2017), that global warming is a hoax (Globalclimatescam.com, 2017), or that the holocaust never happened (Biblebelievers.org.au, 2017). According to Pariser, a marketing process driven by web personalization is treacherous as it works by excluding any information indicating that your beliefs may be erroneous and which consequently will strengthen your confirmation biases even further.
Other prominent writers including Chomsky (2003), McChesney (2004), El-Bermawy et al. (2017), Anderle (2017) and Madrigal (2017) raises concerns about personalization algorithms being a threat to democracy and free societies as the concept of “truth,” ultimately, will be in the hands of profit-driven organisations whom might or might not decide to give users of their services (search engines, news channels, social media networks or e-commerce platforms) unbiased information and data. This also is discussed in Wired Magazine, who points out that 61 percent of millennials use Facebook as their primary source for news about politics (WIRED, 2016), which put Zuckerberg’s quote about a squirrel dying in your front yard in a whole new perspective.
In his book ‘The Persuaders’ (2016), James Garvey also raises concerns about content personalisation. In the book, he discusses how this new paradigm driven by algorithms and neuroscience influence buyer decisions by shaping the design, tone, and content of sales messages to the preferences of individual consumers. According to Garvey, the problem with this is not so much that neuromarketing and web personalization help companies in selling more products, but that companies employing these methods, in effect, are involved in an advanced scheme to manipulate their customers into buying products they do not really need.
A question of moral.
Adapting marketing assets to the preference model of a target audience based on consumer research, ultimately, is about manipulation and, as such, designers have a responsibility.
As a designer, you can choose to build your career by working with projects that have a commendable influence on society, and use the possibilities offered by web-personalization to influence positive societal change. But you also have the choice to use your talent and these technologies to build a career on manipulating people to buy stuff they do not really need.
If and how you personally decide to use these tools and methodologies in your work, ultimately is a matter of choice and moral. Just because you can sell more products by using neuroscience, algorithms, and advanced marketing tools to influence views and decisions of a target audience; the question you need to ask yourself is whether doing so is morally right or not.
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