Luxury is what you say: Analyzing electronic word‐of‐mouth marketing of luxury products using artificial intelligence and machine learning

Abstract

Many luxury brands are investing heavily in creating dynamic video content to actively engage consumers. While it is straightforward to calculate the views or "likes" from a particular campaign to benchmark performance, analyzing consumers' comments on luxury brands' dynamic video content presents a challenge due to the unstructured nature of natural language and large comment volumes. Previous studies utilizing machine learning and artificial intelligence (AI) have not adequately examined the impact of brand types, brand luxuriousness, and consumer diversity.To address this research gap, this article tests a conceptual framework with over 29,000 comments from 88 YouTube campaigns for nine luxury brands using a combination of automatic text and image analyses. The results indicate significant differences in comments' psycholinguistic nature depending on the brand's luxuriousness (premium, prestige, and exquisite) and Copelandian classification (convenience, shopping, and specialty), as well as consumers' demographic characteristics (age, gender, and ethnicity). These findings suggest that brand managers can use machine learning and AI methods to better tailor dynamic content creation to further engage diverse target segments by refining the campaign message to encourage additional engagement.automatic text and image analysis, brand luxuriousness, luxury marketing communications, machine learning and artificial intelligence (AI), nature of electronic word-of-mouth (eWOM), social media video advertising, YouTube | INTRODUCTIONWhile broadcast television remains a relevant communication channel for many brands (Hengel, 2021), many luxury brands are increasingly embracing social media video platforms (e.g., Instagram, YouTube, and TikTok) to enthuse consumers with the latest trends (Arienti, 2020;Pentina et al., 2018). These platforms encourage more active forms of engagement as consumers may like, dislike, share, comment on videos or upload their video responses (Parent et al., 2011), thus facilitating a two-way flow between luxury brands

Artificial Intelligence in Advertising: Advancements, Challenges, and Ethical Considerations in Targeting, Personalization, Content Creation, and Ad Optimization

“…Lastly, in content planning, AI can employ NLP for sentiment analysis of consumer behavior and preference data, that is, analyzing consumer feedback on online platforms like social media, assisting in identifying and analyzing data-driven preferences (Sun et al, 2022). This data aids in adjusting advertising messages to curate better dynamic Content Creation (Oc et al, 2023). NLP-based sentiment analysis helps overcome the high costs of obtaining labeled data.…”