This paper is about how to use data from a random sample of customer relationships to calculate an appropriate average customer lifetime value (CLV). When the sample contains only completed relationships, the simple unweighted average is appropriate. When the sample contains a mix of active and completed relationships, the lifetimes of the active relationships are said to be right censored because the observed lifetime to date is but a lower bound on the eventual lifetime. Because of this censoring, a simple average of the sample CLVs to date will be a biased estimate of the mean CLV. This paper presents and explores several non-parametric estimation methods for correcting for this bias.
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