Category: Digital Disruption

From The Conversation.

Wherever you go online, someone is trying to personalise your web experience. Your preferences are pre-empted, your intentions and motivations predicted. That toaster you briefly glanced at three months ago keeps returning to haunt your browsing in tailored advertising sidebars. And it’s not a one-way street. In fact, the quite impersonal mechanics of some personalisation systems may not only influence how we see the world, but how we see ourselves.

It happens every day, to all of us while we’re online. Facebook’s News Feed attempts to deliver tailored content that “most interests” individual users. Amazon’s recommendation engine uses personal data tracking combined with other users’ browsing habits to suggest relevant products. Google customises search results, and much more: for example, personalisation app Google Now seeks to “give you the information you need throughout your day, before you even ask”. Such personalisation systems don’t just aim to provide relevance to users; through targeted marketing strategies, they also generate profit for many free-to-use web services.

Perhaps the best-known critique of this process is the “filter bubble” theory. Proposed by internet activist Eli Pariser, this theory suggests that personalisation can detrimentally affect web users’ experiences. Instead of being exposed to universal, diverse content, users are algorithmically delivered material that matches their pre-existing, self-affirming viewpoints. The filter bubble therefore poses a problem for democratic engagement: by restricting access to challenging and diverse points of view, users are unable to participate in collective and informed debate.

Attempts to find evidence of the filter bubble have produced mixed results. Some studies have shown that personalisation can indeed lead to a “myopic” view of a topic; other studies have found that in different contexts, personalisation can actually help users discover common and diverse content. My research suggests that personalisation does not just affect how we see the world, but how we view ourselves. What’s more, the influence of personalisation on our identities may not be due to filter bubbles of consumption, but because in some instances online personalisation is not very “personal” at all.

Data tracking and user pre-emption

To understand this, it is useful to consider how online personalisation is achieved. Although personalisation systems track our individual web movements, they are not designed to “know” or identify us as individuals. Instead, these systems collate users’ real-time movements and habits into mass data sets, and look for patterns and correlations between users’ movements. The found patterns and correlations are then translated back into identity categories that we might recognise (such as age, gender, language and interests) and that we might fit into. By looking for mass patterns in order to deliver personally relevant content, personalisation is in fact based on a rather impersonal process.

When the filter bubble theory first emerged in 2011, Pariser argued that one of the biggest problems with personalisation was that users did not know it was happening. Nowadays, despite objections to data tracking, many users are aware that they are being tracked in exchange for use of free services, and that this tracking is used for forms of personalisation. Far less clear, however, are the specifics of what is being personalised for us, how and when.

Data gathering: less complex than we might think. Anton Balazh/Shutterstock

Finding the ‘personal’

My research suggests that some users assume their experiences are being personalised to complex degrees. In an in-depth qualitative study of 36 web users, upon seeing advertising for weight loss products on Facebook some female users reported that they assumed that Facebook had profiled them as overweight or fitness-oriented. In fact, these weight loss ads were delivered generically to women aged 24-30. However, because users can be unaware of the impersonal nature of some personalisation systems, such targeted ads can have a detrimental impact on how these users view themselves: to put it crudely, they must be overweight, because Facebook tells them they are.

It’s not just targeted advertising that can have this impact: in an ethnographic and longitudinal study conducted of a handful of 18 and 19-year-old Google Now users, I found that some participants assumed the app was capable of personalisation to an extraordinarily complex extent. Users reported that they believed Google Now showed them stocks information because Google knew their parents were stockholders, or that Google (wrongly) pre-empted a “commute” to “work” because participants had once lied about being over school age on their YouTube accounts. It goes without saying that this small-scale study does not represent the engagements of all Google Now users: but it does suggest that for these individuals, the predictive promises of Google Now were almost infallible.

Are you an ideal user? EPA/DANIEL DEME

In fact, critiques of user-centred design suggest that the reality of Google’s inferences is much more impersonal: Google Now assumes that its “ideal user” does – or at least should – have an interest in stocks, and that all users are workers who commute. Such critiques highlight that it is these assumptions which largely structure Google’s personalisation framework (for example through the app’s adherence to predefined “card” categories such as “Sports”, which during my study only allowed users to ‘follow’ men’s rather than women’s UK football clubs). However, rather than questioning the app’s assumptions, my study suggests that participants placed themselves outside the expected norm: they trusted Google to tell them what their personal experiences should look like.

Though these might seem like extreme examples of impersonal algorithmic inference and user assumption, the fact that we cannot be sure what is being personalised, when or how are more common problems. To me, these user testimonies highlight that the tailoring of online content has implications beyond the fact that it might be detrimental for democracy. They suggest that unless we begin to understand that personalisation can at times operate via highly impersonal frameworks, we may be putting too much faith in personalisation to tell us how we should behave, and who we should be, rather than vice versa.

Author: Tanya Kant, Lecturer in Media and Cultural Studies, University of Sussex

From The Conversation.

Businesses seem obsessed these days with getting you to “like” them on Facebook.

It’s difficult to browse the internet without being inundated with requests to like a company’s Facebook page or with contests and offers dependent on doing so.

From the company’s perspective, a like on Facebook offers a chance to stay “top of mind,” a marketing concept that means a consumer thinks of a specific brand first for a certain product or service by having its promotional messages show up in that user’s Facebook newsfeed. Being liked can also be used as a metric to determine the performance of social media campaigns and other promotional activities. The more a company is liked, the more successful the promotion is thought to be.

But is this really the case? To find out, we surveyed hundreds of Facebook users to dig into the meaning and value of the Facebook like. We wanted to understand the motivations behind liking certain types of brands and discover how that affects interactions between the user and the business. We also sought to understand how this varies depending on brand type (i.e., product makers versus service providers).

Findings from two studies we undertook reveal that what likes say about consumers and what they think about the brands they like is surprisingly varied.

Does Facebook’s ‘like’ button create brand loyalty? Fabrizio Bensch/Reuters

The loyalty of liking

For the first study, we asked 150 Facebook users to tell us about a brand that they currently like on Facebook. We then asked them to describe their motivation behind clicking the like button the first time, their interactions with the brand since liking them and any changes that have occurred in their relationship with the brand since then.

From our results, it seems that the primary reason that consumers choose to like a brand on Facebook is a sense of existing loyalty or obligation to support a brand. The largest percentage of respondents said they liked a brand simply because they felt that’s what a loyal fan should do. The next biggest share seemed to be more focused on getting something in return for their like, such as information, social recognition or entries into contests.

Interestingly, only a relatively small percentage of respondents reported that they “liked” the brand on Facebook because they simply liked (had a positive attitude toward) the brand. This differs from loyalty in subtle ways.

For example, I may have a positive attitude toward the Rolls Royce brand after seeing its products in advertisements, product placements, etc., but I have never owned one of its cars; therefore, I do not feel loyalty or obligation to the brand. This finding shows that some users who may not have purchased products from the brand may still like the brand on Facebook for various reasons.

As for levels of interaction since first liking a brand, over half of users said that while they may have read the brand’s posts or viewed its images in their Facebook newsfeed, they haven’t given any information whatsoever back to the brand. Just one-fifth said they reposted or shared content from the brand, while only 17 percent reported actually commenting on brand posts.

Finally, there was an interesting and contradictory set of instances in which respondents reported no change in the brand relationship but at the same time went on to actually detail positive brand-related consequences.

For example, a respondent initially noted that his relationship with Ford did not change after liking the Ford page, but later noted that he did look at more photos of new Ford trucks posted by the company on Facebook. This could be interpreted as a change in their relationship, because they are interacting more with the brand.

This suggests that generating Facebook likes can indeed have positive outcomes for a company, including having more interaction with its fans.

Are all likes created equal?

While the first study provided interesting results, we wanted to see if there was a statistically significant difference in the way that Facebook users reported interacting with product versus service brands.

While varying types of businesses may all be trying to gain the same outcome, there is evidence that differences exist between how product- and service-based brands interact with potential customers, ones that require distinct engagement strategies.

Just as all brands are not the same, all likes are not equal. It may seem more natural to like a brand that makes an actual product such as a favorite car manufacturer or clothing brand than a service like a plumber, cable provider or pet groomer. That’s because, due to their intangible nature, services can be much more difficult for consumers to evaluate. As a result, service companies need to initiate social interactions with their customers in order to communicate value and set appropriate expectations.

So in our second study, we surveyed 300 Facebook users to explore these differences and discovered some interesting similarities and differences in the way they interact with brands selling products and those offering services.

For example, we found that “fans” of product brands were more likely to report engaging in passive interactions with the company such as by reading or liking posts compared with those of service brands. They also reported a greater intention to make future purchases.

We found no differences between the groups, however, in their intentions to engage in more active Facebook interactions such as sharing or commenting on posts.

Parsing the results

So what does this all mean?

First, it tells us that simply adding up Facebook likes does not necessarily tell us how engaged a customer is with a company’s brand. Many of our respondents liked their respective brands for reasons other than wanting to engage in an interactive relationship. In other words, quantity of likes does not equal quality of relationships.

In addition, brand and social media managers should not automatically assume that new Facebook followers are new to the company. Many of our respondents felt that it was their obligation to a favorite or oft-purchased brand to like that brand on Facebook.

Although passive engagement with followers is perhaps not what gets the most attention when pundits discuss the benefits of Facebook engagement, it still offers benefits, such as becoming more “top of mind.” Brand managers should not always assume that their loudest and most active Facebook followers are the only ones getting the message.

Finally, our research offers different lessons for service- and product-based brands. For the former, feelings of brand connectedness were a strong outcome of Facebook interaction. These companies should perhaps focus more on personalizing their Facebook messages in an attempt to further stimulate and enhance this elevated sense of connectedness.

For product-based brands, although brand connectedness was lower, purchase intention and brand attitude – the positive or negative associations one has with the brand – were higher. To leverage this, these companies should perhaps include more calls to action on Facebook and showcase their latest and greatest product offerings.

So next time you “like” a brand on Facebook, think about what you are telling the company. And whether that’s the message you want to send.