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Technological developments have enabled marketing and advertising experts to integrate consumer information into tailoring personalized content drawn from the personal interests of individual consumers (Tucker, 2012). In the recent years, we have witnessed a vast scale change in the type of advertisements and marketing strategies we come across in our daily lives. As social media and online platforms increasingly become an integrated part of our daily lives, marketing and advertising strategies are developing accordingly. Hence, we are consistently being exposed to online adverts, some of which we realise while some of which slip our attention. With the utilisation of consumer data for the creation of more personally tailored advertising, new strategies emerge in the form of personalization, customization and retargeting (Aguirre, Mahr, Grewal, de Ruyter, & Wetzels, 2015; Bleier & Eisenbeiss, 2015). Aguirre et al. (2015) analyze the effectiveness of these new strategies on online advertisement and evaluate the personalization paradox, which refers to the situation in which greater personalization in marketing strategies lead to increased response rates from customers while, paradoxically, they could also result in an increased sense of vulnerability of customers, ergo lower response rates. Customers’ sense of vulnerability is assumed to be directly associated with two types of data collection: overt and covert. Consumers display higher click-through responses to personalized advertisements that engage in overt information collection, in contrast with covert data collection strategies which threaten the effectiveness of personalization (Aguirre et al. 2015). In this essay, I will analyze two personalized advertisements I have come across on my social media accounts in an attempt to verify their accuracy based on the links between the advertised content and my personal interests and previous online behaviour.
Personal Customer Experience
The first example of personalized advertisement (see Visual 1 in Annexes) was a sponsored content available on my Facebook home page, which was a promo for the UEFA EURO 2020, the international men’s football championship. The advert was directing to a website where a contest was set up to win tickets to attend the final draw of the tournament in Budapest and meet the official artist of the 2020 tournament, Martin Garrix. Since this is a personalized advertising, the algorithms underlying this strategy should have linked either the football tournament or the artist to my personal interests. However, this example constitutes a poorly personalized advertisement due to several reasons. First, the advertisement doesn’t relate to my personal interests on any level. On one hand, I am not interested in neither football, nor the international tournaments of football. Therefore, virtually it isn’t possible to trace this back to my previous online social interactions such as following accounts related to football on my social media accounts or liking/sharing related posts; to my online shopping behaviour as I have never bought any tickets for football games or any product related to football or UEFA; and to my browser history which doesn’t involve any football-related search. On the other hand, my musical interests don’t include the genre that is associated with Martin Garrix either. My Spotify account is connected through my Facebook account, allowing Facebook to be able to trace my listening history on Spotify, which doesn’t comprise Martin Garrix. This advert appearing on my Facebook page, despite the fact that none of my online behaviour could be related to the content of the advert, shows that this is a poorly personalized advertisement, making it less appealing. Moreover, Bleier and Eisenbeiss (2015) suggest that ad personalization is a complex strategy that can be analysed in two dimensions: depth and breadth. The depth refers to the how accurately an ad reflects a customer’s implied interests, and the breadth refers to how meticulously and exhaustively these are represented (Bleier & Eisenbeiss, 2015). In this case, there is no depth of advertisement as the sponsored content does not accurately represent my interests; and hence no breadth either.
The second example (see Visual 2 in Annexes) was also a sponsored content, available on my Instagram feed (which is also connected to my Facebook page, the parent company of WhatsApp), and it was an advertisement for wireless noise-cancelling earphones, Huawei Freebuds 3. The advert directed me to the brand’s website where the product was available for purchase. This is an example of good personalization, as the ad is traceable to my personal interests, as well as online behaviour. Prior to seeing this ad, I had done some research on the internet about headphones and earphones to have an idea of the available products in the market and their prices, and I also had conversations with friends about this type of products both online and offline. On WhatsApp, I recently had a conversation with a friend who had bought some noise-cancelling headphones, and I expressed my interests in buying a similar product, while I also had conversations with friends, face-to-face, about getting noise-cancelling headphones. So the ad can be traceable to my interests based on my previous research on internet, previous conversations with friends both online, and offline. Moreover, I had never considered Huawei as an option for buying earbuds, which makes this ad even more appealing as it’s a product I have never experienced before as a consumer, and therefore might have a go at. Nevertheless, this ad also makes me feel vulnerable as a consumer at some point, as it shows that the allegedly encrypted WhatsApp messages are possibly used by Facebook and by Instagram to collect my consumer data, which constitute to a violation of privacy.
Conclusions
Tailoring banners and advertisements to individual customers is an effective method, but it also is of a complex and fragile nature as its implementation carries the risk of triggering adverse responses (Bleier & Eisenbeiss, 2015). The examples studied in this case yield the complexity and delicacy of personalization in advertising, as it is shown that even in the case of good personalization, the risk of creating a sense of vulnerability in the customers emerges.
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