Related Multiscreening as a Strategy to Retain Audiences and Increase Persuasion During a Commercial Break

Abstract

The aim of the study was to deepen our understanding of how related multiscreening affects audience memory and persuasion. A survey was administered after a live television show. The results showed that the higher the perceived relatedness of the multi-screen activity, the more persuasive the message. This effect was mediated by subsequent attention to television content, program involvement, and attention to the commercial break. The model was replicated for three different multiscreen activities: social media use, chatting, and information search. Furthermore, it was found that related multiscreening increased the likelihood of respondents staying tuned to the television after the show.

Acknowledgement

The authors would like to thank broadcasting organization STER for their cooperation on this study by providing information regarding the broadcasting.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Brand familiarity did correlate with brand attitude (r = .30, p < 001). The results of the models did not change when controlling for brand familiarity.

2. We could not combine the activities, because the participants answered only the question about relatedness when they checked the box. This resulted in three different subsamples. Some respondents participated in one of the three activities, some two, and a few (n = 66) in all three. We also conducted the analyses with “number of activities” as the covariates. The majority of the results remained the same. Only the models for the chatting activity were no longer significant. However, this could be due to a lack of power (Type II error).

3. The text presents only the unstandardized regression coefficients for the social media activity. The information related to the other activities can be found in Tables 3 and 4. Additionally, some individual paths show non-significant results, but the indirect effects of the models are significant.

Additional information

Notes on contributors

Claire M. Segijn

Claire M. Segijn (Ph.D., University of Amsterdam) is an Assistant Professor of Advertising at the Hubbard School of Journalism and Mass Communication, University of Minnesota. Her research focuses on the effects of using multiple media simultaneously (e.g., multiscreening, synced advertising) on information processing and advertising effectiveness.

Theo Araujo

Theo Araujo (Ph.D., University of Amsterdam) is an Assistant Professor at the Amsterdam School of Communication Research, University of Amsterdam. His research interests include the increasing adoption of artificial intelligence and related technologies within our communication environment, with a special focus on conversational agents and automated decision making.

Hilde A. M. Voorveld

Hilde A.M. Voorveld (Ph.D., University of Amsterdam) is an Associate Professor of Persuasion & New Media Technologies at the Amsterdam School of Communication Research, University of Amsterdam. Her research interests include cross-media advertising, media multitasking, and the uses and effects of new media technology.

Edith G. Smit

Edith G. Smit (Ph.D. University of Amsterdam) is Full Professor at the Amsterdam School of Communication Research, University of Amsterdam. Her research is in persuasive communication with a focus on processing of advertising and tailored health campaigns. She is also Dean of the Graduate School of Communication at the University of Amsterdam.