在线购物者购买意愿的数据分析机器学习预测分析

Andrew Frazier, Fatbardha Maloku, Xinzi Li, Yichun Chen, Yeji Jung, Bahman Zohuri
{"title":"在线购物者购买意愿的数据分析机器学习预测分析","authors":"Andrew Frazier, Fatbardha Maloku, Xinzi Li, Yichun Chen, Yeji Jung, Bahman Zohuri","doi":"10.47363/jesmr/2022(3)162","DOIUrl":null,"url":null,"abstract":"In an era of widespread internet-based commerce, any company with a web-based storefront is looking for ways to improve the customer experience, with the ultimate goal of facilitating purchases. This process can take many forms and use many strategies, but all of them start with one core task. The company must be able to identify who is least likely and most likely to make a purchase. We suggest that with basic web browsing analytics, machine learning with integrated artificial intelligence accompany with deep learning component can provide this capability, and is a viable tool for effective customer segmentation.","PeriodicalId":309331,"journal":{"name":"Journal of Economics & Management Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data Analysis of Online Shopper’s Purchasing Intention Machine Learning for Prediction Analytics\",\"authors\":\"Andrew Frazier, Fatbardha Maloku, Xinzi Li, Yichun Chen, Yeji Jung, Bahman Zohuri\",\"doi\":\"10.47363/jesmr/2022(3)162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In an era of widespread internet-based commerce, any company with a web-based storefront is looking for ways to improve the customer experience, with the ultimate goal of facilitating purchases. This process can take many forms and use many strategies, but all of them start with one core task. The company must be able to identify who is least likely and most likely to make a purchase. We suggest that with basic web browsing analytics, machine learning with integrated artificial intelligence accompany with deep learning component can provide this capability, and is a viable tool for effective customer segmentation.\",\"PeriodicalId\":309331,\"journal\":{\"name\":\"Journal of Economics & Management Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economics & Management Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47363/jesmr/2022(3)162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economics & Management Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47363/jesmr/2022(3)162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在一个广泛的基于互联网的商业时代,任何拥有基于网络的店面的公司都在寻找改善客户体验的方法,其最终目标是促进购买。这个过程可以采取多种形式,使用多种策略,但它们都始于一个核心任务。公司必须能够确定谁最不可能和最有可能进行购买。我们建议,通过基本的网页浏览分析,结合人工智能和深度学习组件的机器学习可以提供这种能力,并且是有效细分客户的可行工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Analysis of Online Shopper’s Purchasing Intention Machine Learning for Prediction Analytics
In an era of widespread internet-based commerce, any company with a web-based storefront is looking for ways to improve the customer experience, with the ultimate goal of facilitating purchases. This process can take many forms and use many strategies, but all of them start with one core task. The company must be able to identify who is least likely and most likely to make a purchase. We suggest that with basic web browsing analytics, machine learning with integrated artificial intelligence accompany with deep learning component can provide this capability, and is a viable tool for effective customer segmentation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信