Boosting Sports Card Sales: Leveraging Visual Display and Machine Learning in Online Retail

Yutao Yang and Tian Lan

Journal of Retailing and Consumer Services, 2024, vol. 81, issue C

Abstract: Trading cards are a fast-growing industry. However, previous research in sports merchandise has largely overlooked the role of cards’ visual appeal in online-commerce. This study addresses this gap by analyzing over 7000 samples from a leading sports card trading platform. Using computer vision algorithms (Mask R–CNN) and a machine learning algorithm (CatBoost), we unveil the importance of 12 image display attributes and their relationship with the card premium rate. Moreover, we identify inverted U-shaped relationships with attributes such as warm hue, saturation, and brightness. The findings offer valuable insights for card dealers to enhance product image display effectiveness.

Keywords: Sports trading card visual display; E-commerce; Visual analysis; Price premium; Machine learning; Sales performance (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:81:y:2024:i:c:s096969892400287x

DOI: 10.1016/j.jretconser.2024.103991

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