Abstract
Direct marketing tests often generate expectations that are not realized during rollout. One reason for this is that the variability of the response rates tends to be greater than that predicted by the standard binomial model. An alternative model is proposed which accounts for this extra variability, and implications with respect to test design and evaluation are discussed. Results from an actual direct marketing test are used to illustrate different aspects of the proposed model. Recommendations for improving current testing procedures are also examined.
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