[Paper Review] Trending Chic: Analyzing the Influence of Social Media on Fashion Brands

Lydia Manikonda, Ragav Venkatesan+2 more|arXiv (Cornell University)|Dec 3, 2015

Digital Marketing and Social Media9 references16 citations

TL;DR

This paper analyzes how top-20 fashion brands use Twitter and Instagram through linguistic and computer vision techniques, focusing on direct vs. indirect marketing strategies. It finds that indirect marketing—using models, events, and lifestyle imagery—yields significantly higher engagement (likes and comments) than direct product promotion, even when textual topics are similar across platforms.

ABSTRACT

Social media platforms are popular venues for fashion brand marketing and advertising. With the introduction of native advertising, users don't have to endure banner ads that hold very little saliency and are unattractive. Using images and subtle text overlays, even in a world of ever-depreciating attention span, brands can retain their audience and have a capacious creative potential. While an assortment of marketing strategies are conjectured, the subtle distinctions between various types of marketing strategies remain under-explored. This paper presents a qualitative analysis on the influence of social media platforms on different behaviors of fashion brand marketing. We employ both linguistic and computer vision techniques while comparing and contrasting strategic idiosyncrasies. We also analyze brand audience retention and social engagement hence providing suggestions in adapting advertising and marketing strategies over Twitter and Instagram.

Motivation & Objective

• To understand how top fashion brands adapt their marketing strategies across Twitter and Instagram.
• To investigate the role of visual content in shaping audience engagement and brand visibility on social media.
• To compare direct marketing (product-focused) versus indirect marketing (lifestyle/event-focused) strategies in fashion branding.
• To identify platform-specific behavioral patterns in posting frequency, content style, and audience interaction.
• To provide actionable insights for marketing researchers and new brands on optimizing social media presence through visual strategy.

Proposed method

• Collected and analyzed social media posts from the top 20 fashion brands on Instagram and Twitter based on follower count.
• Used deep neural network-based visual features (similar to Khosla et al.) to extract and compare visual content embeddings.
• Applied cluster analysis to categorize posts into types: product-focused (C1), runway/events (C2), and portraits (C3).
• Computed platform-specific posting frequency using a time-based indicator function and normalized by active posting months.
• Measured engagement via average likes, comments, and hashtags per post, comparing direct vs. indirect marketing content.
• Conducted cross-platform comparison of textual topics and visual content, identifying discrepancies despite similar messaging.

Experimental results

Research questions

• RQ1 How do top fashion brands differ in their social media strategies between Twitter and Instagram?
• RQ2 What visual and textual patterns distinguish direct marketing from indirect marketing in fashion brand content?
• RQ3 To what extent does indirect marketing strategy increase engagement (likes and comments) compared to direct product promotion?
• RQ4 How do platform-specific visual styles influence audience visibility and brand reach?
• RQ5 What role do celebrities and lifestyle imagery play in enhancing post engagement on Instagram?

Key findings

• Indirect marketing strategies—such as featuring models, celebrities, or event imagery—generated significantly higher average likes (e.g., 47,941 for Michael Kors) compared to direct product shots.
• Despite similar textual topics, brands used distinct visual styles on Twitter versus Instagram, with Instagram favoring high-engagement lifestyle and fashion imagery.
• Nike achieved higher engagement than Adidas not only due to similar content but also because of the presence of tennis celebrities like Rafael Nadal and Serena Williams in their Instagram posts.
• Prada earned four times more likes and comments for its floral-patterned imagery cluster than Armani’s comparable cluster, despite both brands covering similar topics.
• The architecture-focused cluster of Armani received significantly fewer likes and comments than other clusters, indicating lower audience appeal for such content.
• Textual metrics like hashtag count and posting frequency showed no significant correlation with visibility, while visual strategy had a strong impact on engagement outcomes.