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Unveiling the power of video sentiment analysis for predicting advertising effectiveness: exploratory research on femvertising

Author

Listed:
  • Nicolas Hamelin

    (SP Jain Neuroscience Lab & American University in Cairo)

  • Ramy A. Rahimi

    (Embry-Riddle Aeronautical University)

  • Sivapriya Balaji

    (SP Jain Neuroscience Lab & American University in Cairo)

  • Irina Pismennaya

    (SP Jain Neuroscience Lab & American University in Cairo)

  • Nhat Quang Bui

    (SP Jain Neuroscience Lab & American University in Cairo)

  • Hong Anh Ta

    (SP Jain Neuroscience Lab & American University in Cairo)

Abstract

This research challenges the conventional method of textual sentiment analysis in evaluating advertising effectiveness. We examined two distinct video ads for a cosmetics brand, employing video sentiment analysis to gauge their emotional impact on 35 female participants. This assessment was conducted using a self-reported questionnaire and a biometric platform integrating facial detection analysis (using Affdex software by Affectiva) and Galvanic Skin Response (GSR). Both video and text sentiment analyses were performed on two 30-s television ads—one promoting women’s empowerment and the other emphasizing anti-aging properties. While the textual analysis suggested a generally positive tone for both ads, video sentiment analysis, incorporating facial expressions via the Face API, revealed a significant contrast. The ad highlighting youthful appearance displayed higher positive emotional content, particularly “surprise,” compared to the “femvertising” ad promoting women’s empowerment. This heightened emotional response, as identified by video sentiment analysis, had a notable impact on participants’ emotional reactions to the ad, correlating with increased purchase intention and ad enjoyment. Conversely, no significant correlations were observed between emotions, purchase intent, and ad enjoyment for the femvertising ad. This outcome underscores the superiority of video sentiment analysis over traditional textual analysis, which fails to capture the emotional nuances conveyed through facial expressions. In summary, this study demonstrates the potential of video sentiment analysis in predicting purchase intent and assessing advertising appeal.

Suggested Citation

  • Nicolas Hamelin & Ramy A. Rahimi & Sivapriya Balaji & Irina Pismennaya & Nhat Quang Bui & Hong Anh Ta, 2024. "Unveiling the power of video sentiment analysis for predicting advertising effectiveness: exploratory research on femvertising," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(4), pages 1052-1065, December.
    • Handle: RePEc:pal:jmarka:v:12:y:2024:i:4:d:10.1057_s41270-024-00334-x
    DOI: 10.1057/s41270-024-00334-x
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    References listed on IDEAS

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    1. Klaudia Macias, 2021. "Femvertising and Its Perception by Polish Female Consumers," Journal of Marketing and Consumer Behaviour in Emerging Markets, University of Warsaw, Faculty of Management, vol. 1(12), pages 55-69.
    2. Batra, Rajeev & Ray, Michael L, 1986. "Affective Responses Mediating Acceptance of Advertising," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 234-249, September.
    3. Yvette Sterbenk & Sara Champlin & Kasey Windels & Summer Shelton, 2022. "Is Femvertising the New Greenwashing? Examining Corporate Commitment to Gender Equality," Journal of Business Ethics, Springer, vol. 177(3), pages 491-505, May.
    4. Hamelin, Nicolas & Moujahid, Othmane El & Thaichon, Park, 2017. "Emotion and advertising effectiveness: A novel facial expression analysis approach," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 103-111.
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