The Net Promoter Score is a simple measure used by several companies as indicator of customer loyalty. Studies that address the statistical properties of this measure are still scarce and none of them considered the sample size determination problem. We adopt a Bayesian approach to provide point and interval estimators for the Net Promoter Score and discuss the determination of the sample size. Computational tools were implemented to use this methodology in practice. An illustrative example with data from financial services is also presented.

翻译：净推荐值是多家公司用于衡量客户忠诚度的简单指标。目前针对该指标统计特性的研究仍较为匮乏，且尚未有研究涉及样本量确定问题。我们采用贝叶斯方法为净推荐值提供点估计和区间估计，并探讨了样本量的确定方法。为实际应用该方法，我们开发了配套计算工具。此外，还以金融服务数据为例进行了说明性分析。