探索在电子商务网站上阅读产品信息所花费时间的影响:一种机器学习方法来分析消费者行为
1Department of Accounting, Business Information Systems and Statistics, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, 700505 Iasi, Romania.
Behavioral sciences (Basel, Switzerland)
|June 27, 2023
概括
分析电子商务点击流数据显示,阅读产品细节的时间显著影响购买决策. 机器学习模型揭示了复杂的客户行为和影响在线购物结果的非线性关系.
科学领域:
- 电子商务分析分析
- 消费者行为研究研究
- 机器学习应用程序 机器学习应用程序
背景情况:
- 电子商务正在迅速扩张,需要对在线消费者行为有更深入的了解.
- 电子商务网站上的客户导航模式极大地影响购买决策.
- 消费者行为是复杂和动态的,需要先进的分析方法.
研究的目的:
- 调查阅读产品信息所花费的时间如何影响电子商务消费者的行为.
- 了解客户导航及其对购买决策的影响.
- 探索机器学习在分析复杂的消费者数据集中的实用性.
主要方法:
- 利用机器学习 (ML) 算法来分析来自电子商务网站的点击流数据.
- 开发了一种方法来检查消费者数据集中的非线性关系.
- 根据他们的在线导航模式识别和分析客户群.
主要成果:
- 阅读产品信息的时间是购买决策的重要因素.
- 跳出率,退出率和客户类型也明显影响了购买行为.
- 机器学习分析为客户细分和行为模式提供了新的见解.
结论:
- 阅读产品细节所花费的时间是网上购买行为的关键预测指标.
- 对导航指标和客户属性的综合分析增强了对电子商务动态的理解.
- 结果为优化电子商务网站设计和营销策略提供了实用的见解.
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