Segmentation analysis with managerial judgment
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TL;DR
This paper discusses a nonparametric approach for segmentation analysis that does not require a priori knowledge about the true response rate of the segments in the list, other than classifying a segment as being either good, marginal, or bad.
Abstract
This paper discusses a nonparametric approach for segmentation analysis that does not require a priori knowledge about the true response rate of the segments in the list, other than classifying a segment as being either good, marginal, or bad. Drawing on the binomial distribution, three major issues involved in the segmentation approach are discussed—determining the sample size of the segment in the test mailing, recommending or rejecting a segment from the rollout mailing, and determining the regression-to-the-mean (RTM) effect for projecting the rollout response rate. Detailed tables are presented to help implement the results for practical applications.