In the light of the digitalization and the emergence of social media, the concept of influencer marketing has increased significantly in importance on a global scale and is now considered one of the most effective, powerful and cost-effective marketing tools for businesses in today’s society. Nevertheless, despite the effectiveness of influencer marketing, the growing worldwide marketing trend of Computer Generated Imagery (CGI) influencers, also described as human-like influencers, is currently revolutionizing today’s influencer marketing and is expected to become the new way of marketing from a future perspective. With millions of followers on social media, CGI influencers are quickly gaining three times higher follower engagement than prominent celebrities and human influencers, even though their existence is not real. As a result, the organizational use of CGI influencer marketing has intensified markedly on a global scale from several world-leading brands. Although CGI influencers are expected to increase significantly within marketing, the current knowledge and understanding of CGI influencers as a marketing strategy for brands and products is insufficient and is in essential need of further exploration. This thesis contributes to the yet very limited empirical research by focusing on the research gap of differences between CGI influencers and human influencers from a consumer perspective, with the following research question: “How do CGI influencers differ from human influencers in terms of its impact on consumers’ purchase intentions?” The research purpose of this thesis is to explore whether there is any difference in the impact of CGI influencers and human influencers on consumers’ purchase intentions in order to increase the understanding of the effectiveness of virtual influencer marketing in comparison to influencer marketing on consumer behavior. The research purpose was fulfilled by undertaking a qualitative inductive research approach and performing ten semi-structured interviews with respondents which both follow at least one macro- or mega human influencer and CGI influencer on Instagram. The thesis focuses on CGI influencers in relation to the aspects of motivations to follow, opinion leadership and parasocial relationships, since these are closely linked to purchase intentions. By increasing the understanding of consumers’ view, attitude and behavior, this thesis has discovered multiple key aspects in how CGI influencers differ from human influencers in terms of its impact on consumers’ purchase intentions. The results show that CGI influencers are generally seen as more or less the same as human influencers in terms of inspiration. Followingly, it is possible for consumers to create parasocial relationships with CGI influencers. Nevertheless, this thesis has identified a dominant perspective that CGI influencers affect purchase intentions to a lesser extent than human influencers at present, which is primarily based on higher-developed parasocial relationships, a greater perceived genuineness and higher consumer trust for human influencers. The core theoretical implications are the expanded scientific research on CGI influencers as a marketing phenomenon, and the perceived differences and similarities between CGI influencers and human influencers from a consumer perspective. The key practical implications are the increased understanding of the effectiveness of virtual influencer marketing in comparison to influencer marketing on consumer behavior, and how to implement CGI influencers in the marketing strategy successfully. On a societal level, the most central societal implications are several ethical issues of CGI influencers within marketing.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-197669 |
| Date | January 2022 |
| Creators | Arusell, Mattias, Pettersson, Magdalena |
| Publisher | Umeå universitet, Företagsekonomi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0024 seconds