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

Nicolas Hamelin (), Ramy A. Rahimi (), Sivapriya Balaji (), Irina Pismennaya (), Nhat Quang Bui () and Hong Anh Ta ()
Additional contact information
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

Journal of Marketing Analytics, 2024, vol. 12, issue 4, No 20, 1052-1065

Abstract: 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.

Keywords: Textual sentiment analysis; Advertising effectiveness; Video sentiment analysis; Emotional impact; Facial expressions analysis; Galvanic Skin Response; Femvertising; Autonomic response; Neuromarketing (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41270-024-00334-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jmarka:v:12:y:2024:i:4:d:10.1057_s41270-024-00334-x

Ordering information: This journal article can be ordered from
http://www.springer. ... gement/journal/41270

DOI: 10.1057/s41270-024-00334-x

Access Statistics for this article

Journal of Marketing Analytics is currently edited by Maria Petrescu and Anjala Krishnen

More articles in Journal of Marketing Analytics from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().