营销科学学报 ›› 2023, Vol. 3 ›› Issue (4): 1-21.

• •    下一篇

短视频视觉、听觉和内容特征对电商营销效果影响的研究

孙正辉,郑建萍,王有为   

  1. 孙正辉,上海字节跳动科技有限公司, E-mail:1206209211@qq.com   郑建萍,复旦大学管理学院博士研究生, E-mail:18110690015@fuda.edu.cn   王有为,通信作者,复旦大学管理学院教授,博士生导师, E-mail: ywwang@fudan.edu.cn
  • 出版日期:2023-10-10 发布日期:2024-01-18
  • 基金资助:
    本研究得到国家自然科学基金面上项目(编号:71972047)的资助,特此致谢。

Research on the Marketing Effects of Visual, Auditory and Content Features of Short Videos on E-commerce Platform

Sun Zhenghui, Zheng Jianping, Wang Youwei   

  1. Sun Zhenghui,Shanghai Byte Dance Technology Co., Ltd;  Zheng Jianping, School of Management, Fudan University  Wang Youwei,School of Management, Fudan University
  • Online:2023-10-10 Published:2024-01-18

摘要: 随着短视频的流行,“短视频电商”模式逐渐兴起。短视频凭借比文本、图片更强大的信息展示力为电子商务注入了新的活力。然而,究竟何种短视频能更有效地促进电商营销?本文选取“蘑菇街”平台上的短视频为对象,从视觉感受、听觉感受和视频内容等可能影响短视频营销效果的因素出发提取特征,并分别构建多元线性回归模型、CART(分类回归树)模型与随机森林模型研究短视频特征与营销效果之间的关联,其中,营销效果以短视频所展示的产品的销量衡量。研究结果表明,短视频的视觉、听觉和内容特征与营销效果均有一定的相关性,其中,内容特征对产品销量的预测能力最强。

关键词: 短视频, 电商, 多媒体特征, 分类回归树, 随机森林

Abstract: With the popularity of short videos, “short video e-commerce” are adopted by more and more companies. Short videos are very helpful in e-commerce context because they carry more information than texts and pictures do. However, what kind of short videos can more effectively promote product sales in e-commerce context? This paper draw samples o£ short videos on the "Mogujie" platform and extracts features that may affect the marketing effects of short videos, such as visual perception, auditory perception and video content. Then we construct multiple linear regression model, classification and regression tree model and random forest model to study the relationship between short video features and their marketing effects, which are measured by the sales of the products introduced in the short video. The research results show that although the visual, auditory and content features of short videos are all related to the marketing effects, the content features have the strongest effects on the sales performance.

Key words: short videos; , e-commerce; , multimedia features; , classification and regression tree; , random forest