The role of slant and message consistency in political advertising effectiveness: evidence from the 2016 presidential election
Beth L. Fossen (),
Donggwan Kim (),
David A. Schweidel () and
Raphael Thomadsen ()
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Beth L. Fossen: University of Indiana
Donggwan Kim: Washington University in St. Louis
David A. Schweidel: Emory University
Raphael Thomadsen: Washington University in St. Louis
Quantitative Marketing and Economics (QME), 2022, vol. 20, issue 1, No 1, 37 pages
Abstract:
Abstract We explore the relationship between the content of political advertising on television and ad effectiveness. Specifically, we investigate how slant – the extremeness of the message – and consistency with the candidate’s primary campaign messaging in national ad buys relate to two measures of voter behavior: online word-of-mouth (WOM) and voter preference (captured through daily polls) for the candidates. Using data from the 2016 presidential election, we find that ad messages that are more (1) centrist and (2) consistent with a candidate’s primary-election platform associate with increases in online WOM and voter preference for the candidate. We further find that consistency is more important in the early (pre-October) stages of the campaign. Our results suggest that while there may be a benefit to candidates moderating their message after winning the primary election, they need to be careful about shedding their messaging from the primary election during the early stages of the general election. Additionally, our results enrich our understanding of the use of extreme messaging in political advertising, a phenomenon that is on the rise, by showing that it may have a cost of decreased candidate-related WOM and voter preference for the candidate.
Keywords: Political advertising; Ad effectiveness; Television advertising; Word-of-mouth; Social media (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:kap:qmktec:v:20:y:2022:i:1:d:10.1007_s11129-021-09246-x
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DOI: 10.1007/s11129-021-09246-x
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