Predicting likelihood to recommend and likelihood to churn based on cumulative experience of online services: modeling transitions in customer attitudes and behaviours

客户希望以有竞争力的价格获得高质量、高带宽的服务。在实践中，在保证提高质量水平和相关成本之间存在工程权衡。累积服务质量与反映在态度和行为上的最终客户满意度之间的关系是什么，例如净推荐分数（或推荐可能性，L2R）。我们将进行一系列的实验和观察研究，我们的目标是开发一系列模型，最终为每个无线服务家族，预测关键态度分数和L2R基于经验质量随时间的模式。通过对照实验、实地研究和纵向研究，我们将调查累积经验如何转化为基于挫折和满意度经历的服务态度。我们将开发模型来预测累积经验在不同情况下的影响，并将研究经验质量的变化如何导致态度的变化，并最终决定，这些变化反映在L2R的判断中（在某些情况下还会停止服务）。这项研究的一个重要部分将涉及可以检验因果关系假设的对照实验。因此，我们的策略不仅是开发模型，还要在正式实验中测试其预测，并对实验结果进行方差分析，以确定影响L2R的因果因素。这项研究的结果还将包括监督和管理服务交付的指导方针，以提高满意度和忠诚度，并减少挫折和流失。

Customers want high quality, and high bandwidth services, at competitive pricing. In practice there are engineering tradeoffs between guaranteeing increasing levels of quality and the associated costs. What is the relationship between cumulative service quality and resulting customer satisfaction as reflected in attitudes and behaviors such as the net promoter score (or likelihood to recommend, L2R). We will carry out a series of experiments and observational studies where our goal will be to develop a family of models, ultimately for each family of wireless services, that predict key attitude scores and L2R based on patterns of quality of experience over time. Using controlled experiments and field and longitudinal studies we will investigate how cumulative experience translates into attitudes towards services based on the history of frustration and satisfaction experienced. We will develop models that predict the impact of cumulative experience in different contexts and will examine how changes in quality of experience lead to changes in attitudes, and finally decisions, that are reflected in L2R judgments (and discontinuation of service in some cases). An important part of the research will involve controlled experiments that can test hypotheses about causal relationships. Thus our strategy will be not only to develop models, but also to test their predictions in formal experiments, with analysis of variance carried out on the experimental results to identify causal factors that influence L2R. The outcomes of this research will also include guidelines for monitoring and managing service delivery so as to increase satisfaction and loyalty, and reduce frustration and churn on the other.