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Viewing time as a cross-media metric: Comparing viewing time for video advertising on television and online

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  • Bellman, Steven
  • Beal, Virginia
  • Wooley, Brooke
  • Varan, Duane

Abstract

The Media Rating Council recommends weighting advertising exposure by viewing time. Prior research shows viewing time has diminishing returns, implying that effectiveness equivalent to a 100% complete exposure could be achieved by a lower threshold. Results from four laboratory experiments, extending prior banner-ad research to dynamic video ads, suggest 75% viewed is a potential threshold. A second contribution identifies different viewing time distributions for television and online video, due to differences in ad avoidance. More television ads have viewing times exceeding the 75% threshold, and so are more effective than the typical online video ad. Online networks could charge fees equivalent to television ads for video ads that exceed the 75% threshold. A third contribution is the use of interval outcome estimation (IOE), which revealed asymmetric effects of viewing time and that brand familiarity rather than viewing time is the only necessary explanation of ad effectiveness measured by recall.

Suggested Citation

  • Bellman, Steven & Beal, Virginia & Wooley, Brooke & Varan, Duane, 2020. "Viewing time as a cross-media metric: Comparing viewing time for video advertising on television and online," Journal of Business Research, Elsevier, vol. 120(C), pages 103-113.
  • Handle: RePEc:eee:jbrese:v:120:y:2020:i:c:p:103-113
    DOI: 10.1016/j.jbusres.2020.07.034
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    References listed on IDEAS

    as
    1. Paul Gustafson & S. Siddarth, 2007. "Describing the Dynamics of Attention to TV Commercials: A Hierarchical Bayes Analysis of the Time to Zap an Ad," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(5), pages 585-609.
    2. 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.
    3. Alba, Joseph W & Hutchinson, J Wesley, 1987. "Dimensions of Consumer Expertise," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 411-454, March.
    4. F. Thomas Juster, 1966. "Consumer Buying Intentions and Purchase Probability: An Experiment in Survey Design," NBER Books, National Bureau of Economic Research, Inc, number just66-2, March.
    5. Eric Tafani & Elyette Roux & Rainer Greifeneder, 2018. "In the mood for action: When negative program-induced mood improves the behavioral effectiveness of TV commercials," Post-Print hal-01796250, HAL.
    6. Belanche, Daniel & Flavián, Carlos & Pérez-Rueda, Alfredo, 2017. "Understanding Interactive Online Advertising: Congruence and Product Involvement in Highly and Lowly Arousing, Skippable Video Ads," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 75-88.
    7. Wu, Pei-Ling & Yeh, Shih-Shuo & Huan, Tzung-Cheng (.T.C.). & Woodside, Arch G., 2014. "Applying complexity theory to deepen service dominant logic: Configural analysis of customer experience-and-outcome assessments of professional services for personal transformations," Journal of Business Research, Elsevier, vol. 67(8), pages 1647-1670.
    8. Pieters, Rik G M & Bijmolt, Tammo H A, 1997. "Consumer Memory for Television Advertising: A Field Study of Duration, Serial Position, and Competition Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(4), pages 362-372, March.
    9. Megehee, Carol M., 2009. "Advertising time expansion, compression, and cognitive processing influences on consumer acceptance of message and brand," Journal of Business Research, Elsevier, vol. 62(4), pages 420-431, April.
    10. Campbell, Margaret C & Keller, Kevin Lane, 2003. "Brand Familiarity and Advertising Repetition Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 292-304, September.
    11. Pieters, R. & Bijmolt, T.H.A., 1997. "Consumer memory for television advertising : A field study of duration, serial position and competition effects," Other publications TiSEM 1ae20014-8470-4056-8e3d-6, Tilburg University, School of Economics and Management.
    12. Tafani, Eric & Roux, Elyette & Greifeneder, Rainer, 2018. "In the mood for action: When negative program-induced mood improves the behavioral effectiveness of TV commercials," Journal of Business Research, Elsevier, vol. 84(C), pages 125-140.
    13. Thales S. Teixeira & Michel Wedel & Rik Pieters, 2010. "Moment-to-Moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing," Marketing Science, INFORMS, vol. 29(5), pages 783-804, 09-10.
    14. Arch G. Woodside, 2017. "Releasing the death-grip of null hypothesis statistical testing ( < .05): Applying complexity theory and somewhat precise outcome testing (SPOT)," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 27(1), pages 1-15, January.
    15. Goldberg, Marvin E & Gorn, Gerald J, 1987. "Happy and Sad TV Programs: How They Affect Reactions to Commercials," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(3), pages 387-403, December.
    16. Andrea C. Morales & On Amir & Leonard Lee, 2017. "Keeping It Real in Experimental Research—Understanding When, Where, and How to Enhance Realism and Measure Consumer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(2), pages 465-476.
    17. Simmonds, Lucy & Bellman, Steven & Kennedy, Rachel & Nenycz-Thiel, Magda & Bogomolova, Svetlana, 2020. "Moderating effects of prior brand usage on visual attention to video advertising and recall: An eye-tracking investigation," Journal of Business Research, Elsevier, vol. 111(C), pages 241-248.
    18. Olney, Thomas J & Holbrook, Morris B & Batra, Rajeev, 1991. "Consumer Responses to Advertising: The Effects of Ad Content, Emotions, and Attitude toward the Ad on Viewing Time," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(4), pages 440-453, March.
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