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Television Advertising and Online Word-of-Mouth: An Empirical Investigation of Social TV Activity

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  • Beth L. Fossen

    (Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • David A. Schweidel

    (SGoizueta Business School, Emory University, Atlanta, Georgia 30322)

Abstract

In this research, we investigate the relationship between television advertising and online word-of-mouth (WOM) by examining the joint consumption of television programming and production of social media by television viewers, termed social TV. We explore how television advertising impacts the volume of online WOM about advertised brands and about the programs in which the advertisements air. We also examine what encourages or discourages viewers to engage in this particular social TV activity. Using data containing television advertising instances and the volume of minute-by-minute social media mentions, our analyses reveal that television advertising impacts the volume of online WOM for both the brand advertised and the program in which the advertisement airs. We additionally find that the programs that receive the most online WOM are not necessarily the best programs for advertisers interested in online engagement for their brands. Finally, our results highlight the brand, advertisement, and program characteristics that can encourage or discourage social TV activity. We discuss the implications of our findings for media planning strategies and advertisement design strategies.

Suggested Citation

  • Beth L. Fossen & David A. Schweidel, 2017. "Television Advertising and Online Word-of-Mouth: An Empirical Investigation of Social TV Activity," Marketing Science, INFORMS, vol. 36(1), pages 105-123, January.
  • Handle: RePEc:inm:ormksc:v:36:y:2017:i:1:p:105-123
    DOI: 10.1287/mksc.2016.1002
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    1. Rishika Rishika & Ashish Kumar & Ramkumar Janakiraman & Ram Bezawada, 2013. "The Effect of Customers' Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation," Information Systems Research, INFORMS, vol. 24(1), pages 108-127, March.
    2. Olivier Toubia & Andrew T. Stephen, 2013. "Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?," Marketing Science, INFORMS, vol. 32(3), pages 368-392, May.
    3. Murry, John P, Jr & Lastovicka, John L & Singh, Surendra N, 1992. "Feeling and Liking Responses to Television Programs: An Examination of Two Explanations for Media-Context Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(4), pages 441-451, March.
    4. Mingyu Joo & Kenneth C. Wilbur & Bo Cowgill & Yi Zhu, 2014. "Television Advertising and Online Search," Management Science, INFORMS, vol. 60(1), pages 56-73, January.
    5. Jing Wang & Bobby J. Calder, 2006. "Media Transportation and Advertising," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(2), pages 151-162, July.
    6. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    7. Wendy W. Moe & David A. Schweidel, 2012. "Online Product Opinions: Incidence, Evaluation, and Evolution," Marketing Science, INFORMS, vol. 31(3), pages 372-386, May.
    8. Kenneth C. Wilbur, 2008. "A Two-Sided, Empirical Model of Television Advertising and Viewing Markets," Marketing Science, INFORMS, vol. 27(3), pages 356-378, 05-06.
    9. Eric T. Bradlow & David C. Schmittlein, 2000. "The Little Engines That Could: Modeling the Performance of World Wide Web Search Engines," Marketing Science, INFORMS, vol. 19(1), pages 43-62, June.
    10. Onishi, Hiroshi & Manchanda, Puneet, 2012. "Marketing activity, blogging and sales," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 221-234.
    11. Mitchell J. Lovett & Richard Staelin, 2016. "The Role of Paid, Earned, and Owned Media in Building Entertainment Brands: Reminding, Informing, and Enhancing Enjoyment," Marketing Science, INFORMS, vol. 35(1), pages 142-157, January.
    12. Jura Liaukonyte & Thales Teixeira & Kenneth C. Wilbur, 2015. "Television Advertising and Online Shopping," Marketing Science, INFORMS, vol. 34(3), pages 311-330, May.
    13. S. Siddarth & Amitava Chattopadhyay, 1998. "To Zap or Not to Zap: A Study of the Determinants of Channel Switching During Commercials," Marketing Science, INFORMS, vol. 17(2), pages 124-138.
    14. Shyam Gopinath & Jacquelyn S. Thomas & Lakshman Krishnamurthi, 2014. "Investigating the Relationship Between the Content of Online Word of Mouth, Advertising, and Brand Performance," Marketing Science, INFORMS, vol. 33(2), pages 241-258, March.
    15. Kenneth C. Wilbur & Linli Xu & David Kempe, 2013. "Correcting Audience Externalities in Television Advertising," Marketing Science, INFORMS, vol. 32(6), pages 892-912, November.
    16. David A. Schweidel & Natasha Zhang Foutz & Robin J. Tanner, 2014. "Synergy or Interference: The Effect of Product Placement on Commercial Break Audience Decline," Marketing Science, INFORMS, vol. 33(6), pages 763-780, November.
    17. David Godes & José C. Silva, 2012. "Sequential and Temporal Dynamics of Online Opinion," Marketing Science, INFORMS, vol. 31(3), pages 448-473, May.
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    2. Beth L. Fossen & Alexander Bleier, 2021. "Online program engagement and audience size during television ads," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 743-761, July.
    3. Beth L. Fossen & David A. Schweidel, 2019. "Social TV, Advertising, and Sales: Are Social Shows Good for Advertisers?," Marketing Science, INFORMS, vol. 38(2), pages 274-295, March.
    4. Brett R Gordon & Kinshuk Jerath & Zsolt Katona & Sridhar Narayanan & Jiwoong Shin & Kenneth C Wilbur, 2019. "Inefficiencies in Digital Advertising Markets," Papers 1912.09012, arXiv.org, revised Feb 2020.
    5. Ali Goli & Simha Mummalaneni & Pradeep K. Chintagunta & Sanjay K. Dhar, 2022. "Show and Sell: Studying the Effects of Branded Cigarette Product Placement in TV Shows on Cigarette Sales," Marketing Science, INFORMS, vol. 41(6), pages 1163-1180, November.
    6. Beth L. Fossen & Girish Mallapragada & Anwesha De, 2021. "Impact of Political Television Advertisements on Viewers’ Response to Subsequent Advertisements," Marketing Science, INFORMS, vol. 40(2), pages 305-324, March.
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