A new, award-winning research project highlights the emergence of something you may not have considered before - personalised music in video advertising.
by Michael Lynham
Online digital video advertising is growing rapidly driven by greater capacity to target audiences, drive engagement and measure impact. Advances in customer profiling technologies and music classification technologies provide the basis for personalised background music in advertising.
Extant research is based on the traditional notion of an advertisement having static non-personalised music, a ‘one size fits all’ approach. Despite the large body of empirical results and managerial interest in the area of background music in advertising, the academic literature has not addressed how advances in digital technologies might renovate existing theory or present new avenues for research.
This research explores the potential role of music classification technologies in advertising. It is posited that music classification technologies can reduce risk associated with background music selection in advertising through greater predictability of familiarity, fit and induced mood so positively influencing the contribution of background music to cognitive, affective and conative outcomes of video-based advertising.
Music serves a variety of functions in advertising including entertainment, structure and continuity, memorability, lyrical language, targeting and authority establishment (Huron, 1989).
The design for the present study involves exposing subjects to advertisements featuring non-personalised and personalised background music. Personalised background music is selected using music classification technology deployed by the Spotify online music service.
I conducted preliminary tests for cognitive, attitudinal and conative effects. Subjects were first exposed to a video advertisement featuring non-personalised background music, and then where exposed to a video advertisement featuring personalised background music selected using music classification technology. Participants were exposed to both stimuli and their results were compared.
The findings of this research study suggest that the personalisation of background music can result in significantly higher results for advertisement recall, attitudes towards the advertisement and emotional effects and also purchase intention. At the same time, the results also suggest there is no impact on perceived fit or music congruence where the background music is selected using music classification technologies.
The ability to personalise background music for advertising opens up a substantial realm of new research not merely validating this preliminary study but also exploring whether there is a need renovate the extensive established literature that explores the execution factors, consumer behaviour factors, processing models and effects in a much more comprehensive and systematic way.
The implications of personalised background music are significant for practitioners. It represents a shift from mass consumer broadcast advertising to personalised advertising not merely within a channel, such as Pandora Radio, but within the advertising creative. Does the brand and advertiser no longer have a role in background music selection? Far from it, the selection of the original music still serves as a comparison point for fit and therefore considerations on technical attributes particularly acoustic based attributes are critical. However, familiarity need not necessarily be as significant a consideration as in the past, particularly in broadcast advertising. This has ramifications for licensing and may result in a significant change in the economics of background music licensing.
This study suggests that music classification can be used as a mechanism within the background music selection process to select less expensive and more unique pieces of music to be used in advertising.
From a wider perspective, as more and more consumers view and hear advertisements from digital devices, the introduction of programmatic personalised advertisement elements, whether background music, messaging or otherwise, will not only transform the creative industry but also the wider advertising ecosystem as new technology and data driven participants enter the market with enabling technologies.
In conclusion, I suggest two tentative implications from this research study of personalised background music in advertising using music classification. Firstly, the results would seem to suggest that music classification can be used as an effective mechanism for selecting less expensive and more niche pieces of music for use in advertising without impacting music congruence within the advertisement creative. Secondly, background music need not be a ‘one size fits all’ homogenous element of an advertisement. It has the potential to be a heterogeneous personalised experience that can affect marketing outcomes without negatively impacting fit.
Mick Lynham is International Marketing Officer at Trinity College Dublin. His research project recently won a European Digital Communication award in Berlin.
image via The Library of Congress
