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Prerelease Buzz Evolution Patterns and New Product Performance

Author

Listed:
  • Guiyang Xiong

    (Terry College of Business, University of Georgia, Athens, Georgia 30602)

  • Sundar Bharadwaj

    (Terry College of Business, University of Georgia, Athens, Georgia 30602)

Abstract

This study examines the dynamics of online buzz over time before product release. Employing functional data analysis, we treat the curve of prerelease buzz evolution trajectory as the unit of analysis and find that the shape of the curve significantly adds power in predicting new product performance compared with using product characteristics and firm advertising alone. Moreover, daily prerelease buzz evolution data enable accurate sales forecasting long before product release, which allows sufficient time for managers to adjust product design and/or marketing strategy. For example, the forecasting accuracy using an early buzz evolution curve ending on the 61st day before product release is not only higher than that using accumulated buzz volume until then but also higher than that using the total volume of all buzz up until product release. Beyond the sales outcome, we find that prerelease buzz is quickly reflected in firm stock returns before product release and reduces the absolute amount of postrelease stock price correction. The model accounts for endogeneity, and the results are robust after controlling for buzz sentiment. We also explore the factors influencing prerelease buzz evolution patterns, thus generating insights into how to manage prerelease buzz dynamics to enhance new product performance.

Suggested Citation

  • Guiyang Xiong & Sundar Bharadwaj, 2014. "Prerelease Buzz Evolution Patterns and New Product Performance," Marketing Science, INFORMS, vol. 33(3), pages 401-421, May.
    • Handle: RePEc:inm:ormksc:v:33:y:2014:i:3:p:401-421
    DOI: 10.1287/mksc.2013.0828
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