Paid to post: The relationships between sponsorship characteristics and user engagement indicators of beauty-related videos on Dutch YouTube channels. A quantitative content analysis

Online influencer marketing in the form of sponsored content is becoming increasingly prevalent on YouTube. However, there are multiple issues associated with sponsored content, such as inconsistencies among creators when it comes to when and where to provide a disclosure, as well as the visibility of these disclosures. As a result, viewers are oftentimes unaware that they are being exposed to an advertisement, which leads to discussion among academics and media practitioners whether or not this type of marketing strategy can be considered ethical. Despite the efforts of establishing clear guidelines, rules regarding sponsored content are often not abided by due to confusion and/or lack of consequences. While the effects of sponsored content on viewers have been researched extensively, little to no research focuses on how viewers actually experience the use of this advertising strategy on YouTube and subsequently, react upon it. Therefore, in this study the relationships between sponsorship characteristics and nine indicators of user engagement were analyzed, to see if relationships between these concepts exist. The corresponding research question that belonged to this research goal was: ‘What are the relationships between sponsorship characteristics of, and indicators of user engagement around, beauty-related videos on Dutch YouTube channels?’. The research method that was used was a quantitative content analysis. The data set consisted of 300 Dutch videos, sampled from 15 different YouTube channels, in which beauty products were evaluated. The channels themselves were expert sampled. For each video, multiple sponsorship characteristics were coded (e.g. how the YouTuber got the product, if and how this is disclosed, the YouTuber’s valence regarding the product, and the presence of a giveaway), as well as several indicators of user engagement (such as the amount of likes, dislikes, comments, shares, etc.). The main findings were that all indicators of user engagement (except for amount of subscriptions driven) could be predicted by the sponsorship characteristics in this study. The YouTuber’s valence was the most prevalent predictor, as it predicted six out of nine user engagement variables. A visual representation of the resulting model, which highlights the significant relations between the predictors and indicators of user engagement, was provided as well. The findings of this study have theoretical implications on multiple theories, such as the uses and gratifications framework, the ACE typology, and persuasion knowledge theory. In terms of practical implications, these findings help media practitioners (such as marketeers, advertisers, and YouTube influencers) optimize their marketing and engagement strategies. Based on the results, detailed recommendations for these media practitioners were provided as well.