Download Available for download on Monday, July 01, 2024

Download Full Text (22 KB)


This project aims to establish the scope in which social media data plays a considerable role in A&R signings in 2022, from the discovery to the management of new talent; and evaluate the risks associated with said signings. The study dissects the paradigm shift in artist discovery following the digital transformation of the music industry and predominance of social media, within the context of the attention economy. The re-definition of what is seen as ‘talent’ in 2022 is therefore introduced and the importance of virality in data-based signings is discussed; in addition to an evaluation of the role of data in offering record contracts (data collected across all social media and streaming platforms). A specific focus is given to TikTok metrics, as a highly relevant social media platform within the attention economy, and a source of considerable major record deals since 2020. The risks associated with signings resulting from going viral on Tiktok are covered, aiming to grasp the success rate of specific artists and assessing talent originality. Hence the research question of this study: To what extent can Data de-risk A&R signings? Based on 13 interviewees from the UK, US and Canada and a quantitative analysis of TikTok-based major signings in 2020, this paper introduces an A&R speculative Framework, aiming to assess the risks associated with the signings based solely on TikTok virality. It presents a music-factors vs a data-factors based analysis, to better grasp the decisions behind the multi-millions dollars record deals. The results conclude that although virality offers short-term visibility on both social media and funnels to DSPs, it does not constitute a strong enough argument for return on investment of multi-million dollar desks. Indeed, out of all the artists analyzed in this study, the only ones managing to keep consistent streaming numbers are the ones who display strong music-factors, and respond to a more traditional approach of A&R. Therefore, data helps in filtering the thousands of songs released everyday, and in calculating the risks associated with a new signing in the short term, but does not de-risk nor predict the long term potential of an artist.

Publication Date



Valencia (Spain) Campus

To what extent can data de-risk A&R signings?  An A&R speculative framework of TikTok-based signings in 2022