TikTok made me buy it: the phenomenon of viralization of makeup brands through reviews on TikTok

Chiara Dragotto Kedikián and Ignacio Pagliano
Additional contact information
Chiara Dragotto Kedikián: Universidad Siglo 21, Licenciatura en Publicidad. Argentina
Ignacio Pagliano: Universidad Siglo 21, Licenciatura en Publicidad. Argentina

Netnography, 2024, vol. 2, 72-72

Abstract: The purpose of this work was to identify the reasons why user content in the form of reviews on TikTok using #TikTokMadeMeBuyIt is linked to the viralization of makeup brands on the platform. We identified the elements that these contents have in common, in order to then find a way for brands to take advantage of them when making their own content. The study was exploratory in scope, and the research approach was qualitative, content analysis. The sample participants were the 15 most shared, commented and liked posts from 3 makeup brands: Fenty Beauty, Maybelline and L'Oréal. Analyzing the publications we could observe the predominance of tutorial and unboxing type reviews and an informative communication strategy with product testing typology. The viralization dynamics that we highlighted were the use of hashtags and trending audios. In addition, the use of advertising discourse execution frameworks, such as informative, testimonial and product demonstration. Based on the results, we made a list of 10 recommendations that brands in the makeup industry could use to generate content with the possibility of viralization.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dbk:netnog:2024v2a72

DOI: 10.62486/net202472

Access Statistics for this article

More articles in Netnography from AG Editor (Uruguay)
Bibliographic data for series maintained by Javier Gonzalez-Argote ().