在贝叶斯方法下估计净促销商评分的最低样本大小.
Eliardo G Costa1, Rachel Tarini Q Ponte2
1Universidade Federal do Rio Grande do Norte, Departamento de Estatística, Av. Senador Salgado Filho, 3000, 59078-970 Natal, RN, Brazil.
Anais da Academia Brasileira de Ciencias
|May 29, 2024
概括
本研究引入了贝叶斯的方法,用于估计客户忠诚度,使用净促销商得分 (NPS). 它提供了用于确定样本大小的统计方法和工具,增强了商业环境中的NPS分析.
科学领域:
- 业务分析 业务分析
- 统计建模 统计建模
- 客户关系管理 客户关系管理
背景情况:
- 净促销商得分 (NPS) 是衡量客户忠诚度的广泛采用的指标.
- 尽管它很普遍,但对NPS属性的严格统计研究和样本大小的确定是有限的.
- 现有的研究往往缺乏NPS分析的强大统计框架.
研究的目的:
- 开发一个贝叶斯统计框架来估计净促销商得分 (NPS).
- 为了解决NPS的统计性质研究的稀缺性.
- 为在NPS调查中确定样本大小提供实用方法.
主要方法:
- 用贝叶斯方法对NPS进行点和间隔估计.
- 为了解决NPS的样本大小确定问题,开发了统计方法.
- 实施了计算工具,以促进拟议方法的实际应用.
主要成果:
- 该研究为NPS提供了统计学上合理的点和间隔估计器.
- 提出了一个明确的方法来确定NPS研究的适当样本大小.
- 贝叶斯方法的有效性通过金融服务的一个例子来证明.
结论:
- 建议的贝叶斯方法为NPS分析提供了一个强大的框架.
- 开发的工具和方法提高了客户忠诚度测量的可靠性.
- 这项研究有助于在商业环境中更严格地理解和应用NPS.
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