Avoiding Personalized Ads on Social Media : Understanding how YouTube users experience personalized advertising and what leads to ad avoidance in the context of personalization

Abstract: Recent trends and developments in the fields of Big Data, Machine Learning, and Artificial Intelligence are completely transforming the way brands are engaging and communicating with their audience, allowing more personalized communications than ever. With the spread of social networking sites, such as Facebook, YouTube or Instagram a new opportunity arises for companies to connect to their consumers. However, since social media personalization implies the collection and analysis of highly personal data, consumers may develop negative reactions, attitudes or perceptions towards personalized advertising. Research covers extensively issues such as privacy concerns, invasiveness, forced exposure or irritation, which can lead to advertising avoidance. Though understanding the user perspective is crucial, the topic advertising avoidance in the context of personalization, especially in social media environments, hasn’t been discussed at great length. The purpose of this thesis is to understand how YouTube users experience personalized advertising while using the platform. The empirical findings of this thesis contribute to the ongoing research on personalized advertising within a social media setting. In addition, by understanding what can influence personalized ad avoidance on YouTube and describing how consumers express ad avoidance on the platform, this thesis aims to nurture a deeper understanding of the phenomenon. This study is based on an interpretative, abductive as well as a qualitative research design. It uses semi-structured interviews to explore the views, experiences, beliefs, and motivations of individual participants as well as focus groups that can leverage group dynamics to generate new qualitative data. The results of this thesis show that YouTube users experience ad avoidance in relationship with personalized ads for several reasons linked to prior negative attitudes, perceived goal impediment or ad irritation. The analysis of the findings revealed that users can experience cognitive, affective and behavioral ad avoidance as presented in the literature, but a theoretical model which can perfectly explain the phenomena of personalized ad avoidance on social media is currently not existent. While some antecedents claimed by the previously mentioned theoretical frameworks were also visible in the study, additional aspects may have an impact on how consumers experience personalized advertising avoidance in the social media environment, and more specifically on YouTube.