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

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  • Yang, Yutao
  • Lan, Tian

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.

Suggested Citation

  • Yang, Yutao & Lan, Tian, 2024. "Boosting Sports Card Sales: Leveraging Visual Display and Machine Learning in Online Retail," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:joreco:v:81:y:2024:i:c:s096969892400287x
    DOI: 10.1016/j.jretconser.2024.103991
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