Evaluating the Effectiveness of Recommendation Engines on Customer Experience Across Product Categories

被引:0
|
作者
Sasanuma, Katsunobu [1 ]
Yang, Gyung Yeol [1 ]
机构
[1] Nagoya Univ Commerce & Business, Nisshin, Japan
关键词
AI-Powered Tools; Correlation Analysis; Customer Journey; Online Marketing; Recommendation Engine; Similarity Analysis; ENGAGEMENT; CHOICE; AI;
D O I
10.4018/IJTHI.345928
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Artificial intelligence (AI)-powered tools such as recommendation engines are widely used in online marketing and e-commerce; however, online retailers often deploy these tools without understanding which human factors play a role in which products and at which stage of the customer journey. Understanding the interaction between AI-powered tools and humans can help practitioners create more effective online marketing platforms and improve human interaction with e-commerce tools. This paper examines customers' reliance on recommendation engines when purchasing fashion goods, electronics, and media content such as video and music. This paper also discusses the potential for improvement in recommendation engines in online marketing and e-commerce.
引用
收藏
页数:22
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