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Journal of the Academy of Marketing Science

, Volume 46, Issue 2, pp 338–360 | Cite as

Pre-release consumer buzz

  • Mark B. HoustonEmail author
  • Ann-Kristin Kupfer
  • Thorsten Hennig-Thurau
  • Martin Spann
Conceptual/Theoretical Paper

Abstract

“Buzz” during the period leading up to commercial release is commonly cited as a critical success factor for new products. But what exactly is buzz? Based on an extensive literature review and findings from a theories-in-use study (consumer depth interviews and focus groups), the authors argue that pre-release consumer buzz (PRCB) is not just a catchword or a synonym for “word of mouth” but is a distinct construct for which a precise, shared conceptual understanding is notably absent. The authors define PRCB as the aggregation of observable expressions of anticipation by consumers for a forthcoming new product; they conceptualize the construct as being manifested in three distinct types of behaviors (communication, search, and participation in experiential activities) along two dimensions (amount and pervasiveness). PRCB is unique because prior to, versus after, a product’s release, (1) differing information is available, (2) differing mental processes occur, and (3) consumers’ behaviors have differing effects on other consumers, affecting diffusion differently. A quantitative study using secondary data for 254 new products illustrates the performance of the theory-based conceptualization.

Keywords

Buzz Theories-in-use Word of mouth New product success Partial least squares Secondary data Communication Search Movies Video games 

Notes

Acknowledgements

The authors thank Bernd Skiera for his contributions to this project and Peter Bloch, Chris Blocker, Markus Giesler, Marsha Richins, Marko Sarstedt, Srihari Sridhar, Caroline Wiertz, Chris White, and Eric Yorkston for constructive criticism on earlier versions of this manuscript. The first author gratefully acknowledges financial support from the TCU Neeley School of Business Research Grant fund.

References

  1. Bagozzi, R. P., Dholakia, U. M., & Basuroy, S. (2003). How Effortful Decisions Get Enacted: The Motivating Role of Decision Process, Desires, and Anticipated Emotions. Journal of Behavioral Decision Making, 15, 273–295.CrossRefGoogle Scholar
  2. Bass, F. M. (1969). A New Product Growth Model for Consumer Durables. Management Science, 15, 25–227.CrossRefGoogle Scholar
  3. Bendapudi, N., & Leone, R. P. (2002). Managing Business-to-Business Customer Relationships Following Key Contact Employee Turnover in a Vendor Firm. Journal of Marketing, 66, 83–101.CrossRefGoogle Scholar
  4. Biemans, W., Griffin, A., & Moenaert, R. (2010). In Search of the Classics: A Study of the Impact of JPIM Papers from 1984 to 2003. Journal of Product Innovation Management, 27, 461–484.CrossRefGoogle Scholar
  5. Bohnenkamp, B., Knapp, A.-K., Hennig-Thurau, T., & Schauerte, R. (2015). When Does it Make Sense to Do it Again? An Empirical Investigation of Contingency Factors of Movie Remakes. Journal of Cultural Economics, 39, 15–41.CrossRefGoogle Scholar
  6. Bollen, K., & Lennox, R. (1991). Conventional Wisdom on Measurement: A Structural Equation Perspective. Psychological Bulletin, 110, 305–314.CrossRefGoogle Scholar
  7. Broekhuizen, T. L. J., Delre, S. A., & Torres, A. (2011). Simulating the Cinema Market: How Cross-Cultural Differences in Social Influence Explain Box Office Distributions. Journal of Product Innovation Management, 28, 204–217.CrossRefGoogle Scholar
  8. Campbell, A., Mayzlin, D., & Shin, J. (2017). Managing Buzz. RAND Journal of Economics, 48, 203–229.CrossRefGoogle Scholar
  9. Campbell, C. (1987). The Romantic Ethic and the Spirit of Modern Consumerism. London: Blackwell.Google Scholar
  10. Chen, H., Hu, Y.J., and Smith, M.D. (2017), The Impact of Ebook Distribution on Print Sales: Analysis of a Natural Experiment, Management Science, forthcoming.Google Scholar
  11. Chen, Y., Liu, Y., & Zhang, J. (2012). When Do Third-Party Product Reviews Affect Firm Value and What Can Firms Do? The Case of Media Critics and Professional Movie Reviews. Journal of Marketing, 76, 116–134.CrossRefGoogle Scholar
  12. Chun, H. E. H., Diehl, K., & MacInnis, D. (2017). Savoring an Upcoming Experience Affects Ongoing and Remembered Consumption Enjoyment. Journal of Marketing, 81, 96–110.CrossRefGoogle Scholar
  13. Clement, M., Wu, S., & Fischer, M. (2014). Empirical Generalizations of Demand and Supply Dynamics for Movies. International Journal of Research in Marketing, 31, 207–223.CrossRefGoogle Scholar
  14. Craig, C. S., Greene, W. H., & Versaci, A. (2015). E-Word of Mouth: Early Predictor Of Audience Engagement—How Pre-Release ‘E-WOM’ Drives Box-Office Outcomes of Movies. Journal of Advertising Research, 55, 62–72.CrossRefGoogle Scholar
  15. D’Alessandro, A. (2015), “How Strong is Your Film’s Buzz? Rentrak’s PreAct Can Tell You – CinemaCon,” Deadline. Retrieved April 24, 2015 from http://deadline.com/2015/04/pitch-perfect-2-insidious-chapter-3-southpaw-rentrak-uta-preact-film-campaigns-1201414615/.
  16. Dellarocas, C., Zhang, X. M., & Awad, N. F. (2007). Exploring the Value of Online Product Reviews in Forecasting Sales: The Case of Motion Pictures. Journal of Interactive Marketing, 21, 23–45.CrossRefGoogle Scholar
  17. de Matos, C. A., & Rossi, C. A. V. (2008a). Word-of-Mouth Communications in Marketing: A Meta-Analytic Review of the Antecedents and Moderators. Journal of the Academy of Marketing Science, 36, 578–596.CrossRefGoogle Scholar
  18. Dewan, S., & Ramaprasad, J. (2014). Social Media, Traditional Media, and Music Sales. MIS Quarterly, 38, 101–121.CrossRefGoogle Scholar
  19. Dhar, V., & Chang, E. A. (2009). Does Chatter Matter? The Impact of User-Generated Content on Music Sales. Journal of Interactive Marketing, 23, 300–307.CrossRefGoogle Scholar
  20. Dichter, E. (1966). How Word-of-Mouth Advertising Works. Harvard Business Review, 44, 147–160.Google Scholar
  21. Divakaran, P. K. P., Palmer, A., Søndergaard, H. A., & Matkovskyy, R. (2017). Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data. Journal of Interactive Marketing, 38, 12–28.CrossRefGoogle Scholar
  22. Elberse, A., & Eliashberg, J. (2003). Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures. Marketing Science, 22, 329–354.CrossRefGoogle Scholar
  23. Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1993). Consumer Behavior (8th ed.). Fort Worth: Dryden.Google Scholar
  24. Facebook. (2017), “Facebook Reports Second Quarter 2017 Results,” Retrieved September 21, 2017, from https://s21.q4cdn.com/399680738/files/doc_financials/2017/Q2/FB-Q2'17-Earnings-Release.pdf.
  25. Fahey, Mark (2015), How to Know When a Summer Movie Will Flop, CNBC, May 29, 2015. Retrieved September 14, 2017, from https://www.cnbc.com/2015/05/29/how-to-know-when-a-movie-will-flop-.html.
  26. Freedman, N. (2015), How Social Media is Changing Hollywood, Digital America, April 6, 2015. Retrieved April 26, 2017, from http://www.digitalamerica.org/how-social-media-is-changing-hollywood-nicola-freedman/.
  27. Gibbs, Samuel. (2017), “iPhone 8: Muted Reaction and Small Queues Lead to Questions Over Demand.” Retrieved on September 23, 2017 from http://theguardian.com/technology/2017/sep/22/iphone-8-small-queues-muted-reaction-questions-demand-iphone-x.Google Scholar
  28. Godes, D., & Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth Communication. Marketing Science, 23, 545–560.CrossRefGoogle Scholar
  29. Google. (2014), Year in Search 2014, Google Trends. Retrieved March 10, 2017 from www.google.com/trends/2014/.
  30. Griskevicius, V., Goldstein, N. J., Mortensen, C. R., Sundie, J. M., Cialdini, R. B., & Kenrick, D. T. (2009). Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion. Journal of Marketing Research, 46, 384–395.CrossRefGoogle Scholar
  31. Hair, J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (2nd ed.). Los Angeles: Sage.Google Scholar
  32. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19, 139–152.CrossRefGoogle Scholar
  33. Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of the Academy of Marketing Science, 40, 414–433.CrossRefGoogle Scholar
  34. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic Word-of-Mouth Via Consumer Opinion Platforms: What Motivates Consumers to Articulate Themselves on the Internet? Journal of Interactive Marketing, 18, 38–52.CrossRefGoogle Scholar
  35. Hennig-Thurau, T., Houston, M. B., & Heitjans, T. (2009). Conceptualizing and Measuring the Monetary Value of Brand Extensions: The Case of Motion Pictures. Journal of Marketing, 73, 167–183.CrossRefGoogle Scholar
  36. Hennig-Thurau, T., Houston, M. B., & Sridhar, S. (2006). Can Good Marketing Carry a Bad Product? Evidence from the Motion Picture Industry. Marketing Letters, 17, 205–219.CrossRefGoogle Scholar
  37. Hennig-Thurau, T., Marchand, A., & Hiller, B. (2012). The Relationship between Reviewer Judgments and Motion Picture Success: Re-analysis and Extension. Journal of Cultural Economics, 36, 249–283.CrossRefGoogle Scholar
  38. Hennig-Thurau, T., Wiertz, C., & Feldhaus, F. (2015). Does Twitter Matter? The Impact of Microblogging Word of Mouth on Consumers’ Adoption of New Movies. Journal of the Academy of Marketing Science, 43, 375–394.CrossRefGoogle Scholar
  39. Hewett, K., Rand, W., Rust, R. T., & Van Heerde, H. J. (2016). Brand Buzz in the Echoverse. Journal of Marketing, 80, 1–24.CrossRefGoogle Scholar
  40. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic Consumption: Emerging Concepts, Methods and Propositions. Journal of Marketing, 46, 92–101.CrossRefGoogle Scholar
  41. Hirschman, E. C. (1980). Innovativeness, Novelty Seeking, and Consumer Creativity. Journal of Consumer Research, 7, 283–295.CrossRefGoogle Scholar
  42. Ho, J. Y. C., Dhar, T., & Weinberg, C. B. (2009). Playoff Payoff: Super Bowl Advertising for Movies. International Journal of Research in Marketing, 26, 168–179.CrossRefGoogle Scholar
  43. Holbrook, M. B., & Addis, M. (2008). Art versus Commerce in the Movie Industry: A Two-Path Model of Motion-Picture Success. Journal of Cultural Economics, 32, 87–107.CrossRefGoogle Scholar
  44. JoBlo. (2017). Retrieved March 10, 2017 from http://www.joblo.com/forums/.
  45. Karniouchina, E. V. (2011a). Impact of Star and Movie Buzz on Motion Picture Distribution and Box Office Revenue. International Journal of Research in Marketing, 28, 62–74.CrossRefGoogle Scholar
  46. Karniouchina, E. V. (2011b). Are Virtual Markets Efficient Predictors of New Product Success? The Case of the Hollywood Stock Exchange. Journal of Product Innovation Management, 28, 470–484.CrossRefGoogle Scholar
  47. Kaye, D. (2010), “4 Films that Failed to Live Up to their Blockbuster Comic-Con Buzz,” Blastr.com. Retrieved February 10, 2015 from http://www.blastr.com/2010/12/4_comic_con_buzz_movies_t.php.
  48. Kirmani, A., & Rao, A. R. (2000). No Pain, No Gain: A Critical Review of the Literature on Signaling Unobservable Product Quality. Journal of Marketing, 64, 66–79.CrossRefGoogle Scholar
  49. Liu, Y. (2006). Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue. Journal of Marketing, 70, 74–89.CrossRefGoogle Scholar
  50. Luce, M. F. (1998). Choosing to Avoid: Coping with Negatively Emotion-Laden Consumer Decisions. Journal of Consumer Research, 24, 409–433.CrossRefGoogle Scholar
  51. MacInnis, D. J. (2011). A Framework for Conceptual Contributions in Marketing. Journal of Marketing, 75, 136–154.CrossRefGoogle Scholar
  52. MacInnis, D. J., & de Mello, G. E. (2005). The Concept of Hope and Its Relevance to Product Evaluation and Choice. Journal of Marketing, 69, 1–14.CrossRefGoogle Scholar
  53. Martin, Joe (2015), “Adobe Digital Index Movie Prediction Mid-Summer Update.” Retrieved August 6, 2015 from http://blogs.adobe.com/difitalmarketing/social-media/adobe-digital-index-movie-prediction-mid-summer-update/.
  54. McCracken, G. (1988). The Long Interview. Newbury Park: Sage Publications.CrossRefGoogle Scholar
  55. Meenaghan, T., McLoughlin, D., & McCormack, A. (2013). New Challenges in Sponsorship Evaluation Actors, New Media, and the Context of Praxis. Psychology & Marketing, 30, 444–460.CrossRefGoogle Scholar
  56. Mestyán, M., Yasseri, T., & Kertész, J. (2013). Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data. PLoS One, 8, e71226.CrossRefGoogle Scholar
  57. Mizik, N., & Jacobson, R. (2008). The Financial Value Impact of Perceptual Brand Attributes. Journal of Marketing Research, 45, 15–32.CrossRefGoogle Scholar
  58. Mlodinow, L. (2006), “Meet Hollywood’s Latest Genius,” LA Times, July 2, 2006. Retrieved September 14, 2017, from http://econweb.ucsd.edu/~vcrawfor/la-tm-random27jul02,1,1850294,full.story.html.
  59. Moulard, J. G., Kroff, M. W., & Garretson, J. A. (2012). Unraveling Consumer Suspense: The Role of Hope, Fear, and Probability Fluctuations. Journal of Business Research, 65, 340–346.CrossRefGoogle Scholar
  60. Movie Fan Central (2017), “Welcome to Movie Fan Central: Where Movie Fans Roam.” Retrieved April 15, 2017 from http://www.moviefancentral.com/.
  61. Muller, E., Peres, R., & Mahajan, V. (2009). Innovation Diffusion and New Product Growth. Cambridge: Marketing Science Institute.Google Scholar
  62. Okazaki, S. (2009). The Tactical Use of Mobile Marketing: How Adolescents’ Social Networking Can Best Shape Brand Extensions. Journal of Advertising Research, 49, 12–26.CrossRefGoogle Scholar
  63. Peres, R., Muller, E., & Mahajan, V. (2010). Innovation diffusion and new product growth models: A critical review and research directions. International Journal of Research in Marketing, 27, 91–106.CrossRefGoogle Scholar
  64. Siefert, C. J., Kothuri, R., Jacobs, D. B., Levine, B., Plummer, J., & Marci, C. D. (2009). Winning the Super ‘Buzz’ Bowl: How Biometrically-Based Emotional Engagement Correlates with Online Views and Comments for Super Bowl Advertisements. Journal of Advertising Research, 49, 293–303.CrossRefGoogle Scholar
  65. Srinivasan, S., Rutz, O. J., & Pauwels, K. (2015). Paths to and off Purchase: Quantifying the Impact of Traditional Marketing and Online Consumer Activity. Journal of the Academy of Marketing Science, 44, 440–453.CrossRefGoogle Scholar
  66. Sundaram, D. S., Mitra, K., & Webster, C. (1998). Word-of-Mouth Communications: A Motivational Analysis. Advances in Consumer Research, 25, 527–531.Google Scholar
  67. Tang, T., Fang, E., & Wang, F. (2014). Is Neutral Really Neutral? The Effects of Neutral User-Generated Content on Product Sales. Journal of Marketing, 78, 41–58.CrossRefGoogle Scholar
  68. The Street. (2012); “5 Big-Buzz IPOs That Disappointed,” Forbes. Retrieved April 21, 2017, from https://www.forbes.com/sites/thestreet/2012/01/25/5-big-buzz-ipos-that-disappointed/#74eb819e75a1.
  69. Thompson, C. J. (1997). Interpreting Consumers: A Hermeneutical Framework for Deriving Marketing Insights from the Texts of Consumers' Consumption Stories. Journal of Marketing Research, 34, 438–455.CrossRefGoogle Scholar
  70. Thompson, C. J., Locander, W. B., & Pollio, H. R. (1989). Putting Consumer Experience Back into Consumer Research: The Philosophy and Method of Existential-Phenomenology. Journal of Consumer Research, 16, 133–146.CrossRefGoogle Scholar
  71. Tuli, K. R., Kohli, A. K., & Bharadwaj, S. G. (2007). Rethinking Customer Solutions: From Product Bundles to Relational Processes. Journal of Marketing, 71, 1–17.CrossRefGoogle Scholar
  72. Twitter. (2017), “About Twitter.” Retrieved March 10, 2017 from https://about.twitter.com/company.
  73. Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude. Journal of Marketing Research, 40, 310–320.CrossRefGoogle Scholar
  74. Wikipedia. (2017), “Wikipedia:About.” Retrieved March 10, 2017 from en.wikipedia.org/wiki/wikipedia:about.Google Scholar
  75. Wiles, M. A., & Danielova, A. (2009). The Worth of Product Placement in Successful Films: An Event Study Analysis. Journal of Marketing, 73, 44–63.CrossRefGoogle Scholar
  76. Wise, D. (2013), “IMDb – The Mecca for Movie Buffs,” OneClickRoute. Retrieved April 15, 2017 from http://www.oneclickroot.com/reviews/imdb-the-mecca-for-movie-buffs/.
  77. Xiong, G., & Bharadwaj, S. (2014). Prerelease Buzz Evolution Patterns and New Product Performance. Marketing Science, 33, 401–421.CrossRefGoogle Scholar
  78. Zaltman, G., LeMasters, K., & Heffring, M. (1982). Theory Construction in Marketing. New York: John Wiley & Sons.Google Scholar

Copyright information

© Academy of Marketing Science 2018

Authors and Affiliations

  • Mark B. Houston
    • 1
    Email author
  • Ann-Kristin Kupfer
    • 2
  • Thorsten Hennig-Thurau
    • 2
  • Martin Spann
    • 3
  1. 1.Department of Marketing, Neeley School of BusinessTexas Christian UniversityFort WorthUSA
  2. 2.Marketing Center MuensterUniversity of MuensterMuensterGermany
  3. 3.Institute of Electronic Commerce and Digital MarketsLudwig-Maximilians-University MunichMunichGermany

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