Real-Time Evaluation of E-mail Campaign Performance
提出一种分裂风险模型，利用虚拟时间变换实时预测电子邮件营销活动的打开率和点击率，在一小时十五分钟内得到比传统方法十四小时更准确可靠的估计。
We develop a testing methodology that can be used to predict the performance of e-mail marketing campaigns in real time. We propose a split-hazard model that makes use of a time transformation (a concept we call virtual time) to allow for the estimation of straightforward parametric hazard functions and generate early predictions of an individual campaign's performance (as measured by open and click propensities). We apply this pretesting methodology to 25 e-mail campaigns and find that the method is able to produce in an hour and fifteen minutes estimates that are more accurate and more reliable than those that the traditional method (doubling time) produces after 14 hours. Other benefits of our method are that we make testing independent of the time of day and we produce meaningful confidence intervals. Thus, our methodology can be used not only for testing purposes, but also for live monitoring. The testing procedure is coupled with a formal decision theoretic framework to generate a sequential testing procedure useful for the real time evaluation of campaigns.