POP Cart: Product Recommendation System by an Agent on a Shopping Cart

被引:2
|
作者
Takada, Ryosuke [1 ]
Hoshimure, Kenya [2 ]
Iwamoto, Takuya [2 ,3 ]
Baba, Jun [2 ,3 ]
机构
[1] Kobe City Coll Technol, 8-3 Gakuen Higashi, Kobe, Hyogo 6512194, Japan
[2] Osaka Univ, 1-1 Machikaneyama, Toyonaka, Osaka 5600043, Japan
[3] CyberAgent Inc, Shibuya Ku, 19F-23F Shibuya Scramble Sq 2-24-12 Shibuya, Tokyo 1506121, Japan
关键词
D O I
10.1109/RO-MAN50785.2021.9515436
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, we developed POP Cart that uses a shopping cart and an agent to recommend products. The agent on POP Cart is designed to call the customer by name, chatting and making recommendations to the customer casually like a friend. POP Cart has two advantages: first, the agent can form a positive relationship with the customer is in the store, which could be beneficial for a high recommendation success rate, as found in previous studies. Second, the agent can make multiple recommendations for different products according to the position of the customer while they are shopping in a large store. To evaluate the effectiveness of the recommendations made by the POP Cart agent, we conducted a field experiment in a real supermarket in Japan, where 49 participants shopped under three cart conditions. The results revealed that having an agent on a shopping cart is an effective way to recommend and sell products.
引用
收藏
页码:59 / 66
页数:8
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