Data Analytics and Personalized Marketing Strategies in E-commerce Platforms

{"title":"Data Analytics and Personalized Marketing Strategies in E-commerce Platforms","authors":"","doi":"10.57125/fel.2023.09.25.07","DOIUrl":null,"url":null,"abstract":"The purpose of this study is to identify the most adapted digital data analysis tools for developing individual marketing strategies in the e-commerce segment. In the study the following ranking methods were used: the cross-expert rating (based on individual opinions of 15 specialised organisations) and arbitration rating of the most relevant resource - G2.com. Subsequently, a comparative analysis of the leading E-Commerce Analytics applications was performed in order to obtain the ranking results. Using a methodology that took into account the expert ratings, cross- and arbitrage ratings, as well as the user feedback, it was found that the Glassbox was the best option for large enterprises, particularly, for large e-businesses. Google Analytics, on the other hand, is more popular among smaller companies and is considered a more versatile tool for data analysis. The importance of choosing the right tool for data analytics in e-commerce was also highlighted in the study, as the wrong choice can lead to financial losses and loss of investment. Future researches in this area include the creation of universal algorithms for selecting data analytics software solutions, expanding the range of data analytics applications, and more detail in understanding the specific needs of e-commerce platforms.","PeriodicalId":477356,"journal":{"name":"Futurity Economics&Law","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Futurity Economics&Law","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.57125/fel.2023.09.25.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The purpose of this study is to identify the most adapted digital data analysis tools for developing individual marketing strategies in the e-commerce segment. In the study the following ranking methods were used: the cross-expert rating (based on individual opinions of 15 specialised organisations) and arbitration rating of the most relevant resource - G2.com. Subsequently, a comparative analysis of the leading E-Commerce Analytics applications was performed in order to obtain the ranking results. Using a methodology that took into account the expert ratings, cross- and arbitrage ratings, as well as the user feedback, it was found that the Glassbox was the best option for large enterprises, particularly, for large e-businesses. Google Analytics, on the other hand, is more popular among smaller companies and is considered a more versatile tool for data analysis. The importance of choosing the right tool for data analytics in e-commerce was also highlighted in the study, as the wrong choice can lead to financial losses and loss of investment. Future researches in this area include the creation of universal algorithms for selecting data analytics software solutions, expanding the range of data analytics applications, and more detail in understanding the specific needs of e-commerce platforms.
电子商务平台中的数据分析与个性化营销策略
本研究的目的是确定最适合的数字数据分析工具,以制定电子商务细分市场的个人营销策略。在研究中使用了以下排名方法:跨专家评级(基于15个专业组织的个人意见)和最相关资源- G2.com的仲裁评级。随后,对领先的电子商务分析应用程序进行了比较分析,以获得排名结果。使用一种考虑了专家评级、交叉评级和套利评级以及用户反馈的方法,我们发现Glassbox是大型企业,特别是大型电子商务的最佳选择。另一方面,谷歌分析在小公司中更受欢迎,被认为是一种更通用的数据分析工具。该研究还强调了在电子商务中选择正确的数据分析工具的重要性,因为错误的选择可能导致财务损失和投资损失。该领域的未来研究包括创建通用算法来选择数据分析软件解决方案,扩展数据分析应用的范围,以及更详细地了解电子商务平台的具体需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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