Nicolas Hamelin, Ramy A. Rahimi, Sivapriya Balaji, Irina Pismennaya, Nhat Quang Bui, Hong Anh Ta
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引用次数: 0
摘要
本研究挑战了在评估广告效果时使用文本情感分析的传统方法。我们研究了某化妆品品牌的两则不同的视频广告,通过视频情感分析来评估它们对 35 名女性参与者的情感影响。这项评估是通过一份自我报告问卷和一个整合了面部检测分析(使用 Affectiva 公司的 Affdex 软件)和 Galvanic Skin Response (GSR) 的生物识别平台进行的。我们对两则 30 秒的电视广告进行了视频和文本情感分析,一则广告宣传妇女赋权,另一则广告强调抗衰老特性。虽然文本分析表明这两则广告的基调总体上是积极的,但通过 Face API 结合面部表情进行的视频情感分析却显示出明显的反差。与宣传女性赋权的 "女性广告 "相比,强调年轻外表的广告显示出更多积极的情感内容,尤其是 "惊喜"。通过视频情感分析发现,这种增强的情感反应对参与者对广告的情感反应产生了显著影响,并与购买意向和广告欣赏度的增加相关联。相反,在女性广告的情感、购买意向和广告欣赏之间没有观察到明显的相关性。这一结果凸显了视频情感分析比传统文本分析的优越性,因为传统文本分析无法捕捉面部表情所传达的情感细微差别。总之,本研究证明了视频情感分析在预测购买意向和评估广告吸引力方面的潜力。
Unveiling the power of video sentiment analysis for predicting advertising effectiveness: exploratory research on femvertising
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.
期刊介绍:
Data has become the new ore in today’s knowledge economy. However, merely storing and reporting are not enough to thrive in today’s increasingly competitive markets. What is called for is the ability to make sense of all these oceans of data, and to apply those insights to the way companies approach their markets, adjust to changing market conditions, and respond to new competitors.
Marketing analytics lies at the heart of this contemporary wave of data driven decision-making. Companies can no longer survive when they rely on gut instinct to make decisions. Strategic leverage of data is one of the few remaining sources of sustainable competitive advantage. New products can be copied faster than ever before. Staff are becoming less loyal as well as more mobile, and business centers themselves are moving across the globe in a world that is getting flatter and flatter.
The Journal of Marketing Analytics brings together applied research and practice papers in this blossoming field. A unique blend of applied academic research, combined with insights from commercial best practices makes the Journal of Marketing Analytics a perfect companion for academics and practitioners alike. Academics can stay in touch with the latest developments in this field. Marketing analytics professionals can read about the latest trends, and cutting edge academic research in this discipline.
The Journal of Marketing Analytics will feature applied research papers on topics like targeting, segmentation, big data, customer loyalty and lifecycle management, cross-selling, CRM, data quality management, multi-channel marketing, and marketing strategy.
The Journal of Marketing Analytics aims to combine the rigor of carefully controlled scientific research methods with applicability of real world case studies. Our double blind review process ensures that papers are selected on their content and merits alone, selecting the best possible papers in this field.