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Heterogeneity in the Effects of Online Persuasion

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  • Kaptein, Maurits
  • Eckles, Dean

Abstract

Average effects of influence strategies on consumers' attitudes and behaviors have been studied extensively. Less is known about the relative size of individual differences in these effects, despite recognition of their importance in social psychology. Two experiments use repeated exposures to influence strategies to identify the effects of each social influence strategy for individual participants. Study 1 provides evidence of large variation in the effects of influence strategies, such that for many participants the estimated effect of using an influence strategy is negative, even though the effect of that strategy is significantly positive on average. Study 2 replicates these findings over three sessions, each a week apart. The observed variation in responses to influence strategies cannot be attributed to transient intra-individual variation (e.g., strategy×mood interactions). Meta-judgmental measures of personality constructs (e.g., need for cognition) explain only a small portion of the observed variance, suggesting the importance of directly modeling heterogeneity in responses to influence attempts. These results are important for interactive marketeers since they indicate that different influence strategies substantially differ in their effects on individual consumers and should thus be adapted to individuals.

Suggested Citation

  • Kaptein, Maurits & Eckles, Dean, 2012. "Heterogeneity in the Effects of Online Persuasion," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 176-188.
    • Handle: RePEc:eee:joinma:v:26:y:2012:i:3:p:176-188
    DOI: 10.1016/j.intmar.2012.02.002
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    References listed on IDEAS

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    Cited by:

    1. Blazevic, Vera & Wiertz, Caroline & Cotte, June & de Ruyter, Ko & Keeling, Debbie Isobel, 2014. "GOSIP in Cyberspace: Conceptualization and Scale Development for General Online Social Interaction Propensity," Journal of Interactive Marketing, Elsevier, vol. 28(2), pages 87-100.
    2. Meents, Selmar & Verhagen, Tibert & Merikivi, Jani & Weltevreden, Jesse, 2020. "Persuasive location-based messaging to increase store visits: An exploratory study of fashion shoppers," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    3. Dean Eckles & Maurits Kaptein, 2019. "Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences," SAGE Open, , vol. 9(2), pages 21582440198, June.
    4. Díaz, Estrella & Martín-Consuegra, David, 2016. "A latent class segmentation analysis of airlines based on website evaluation," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 20-40.
    5. Maurits Kaptein & Robin van Emden & Davide Iannuzzi, 2017. "Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    6. Estrella Díaz & David Martín-Consuegra & Hooman Estelami, 2016. "A persuasive-based latent class segmentation analysis of luxury brand websites," Electronic Commerce Research, Springer, vol. 16(3), pages 401-424, September.
    7. Pappas, Ilias O. & Kourouthanassis, Panos E. & Giannakos, Michail N. & Chrissikopoulos, Vassilios, 2016. "Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions," Journal of Business Research, Elsevier, vol. 69(2), pages 794-803.
    8. Barnes, Stuart J. & Pressey, Andrew D., 2016. "Cyber-mavens and online flow experiences: Evidence from virtual worlds," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 285-296.

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