The dark side of CRM: advantaged and disadvantaged customers

Purpose – CRM treats various profiles of customers or individual customers differently, purposively favoring certain customers while deliberately disadvantaging others. This research aims to provide insights into how advantaged (favored) and (non-favored) disadvantaged customers perceive fairness in retailers’ marketing tactics. Design/methodology/approach – A multiple study approach has been adopted, influenced by a three-stage process, which involved exploratory interviews, pilot tests, and the main survey. Findings – The results have provided marketers with a perspective on maintaining and enhancing relationships. Service and marketing communications concern the advantaged customers most, while pricing is the most important aspect for the disadvantaged customers. Practical implications – In terms of handling customers, there are important implications from recognizing how those who are favored and those who are not so advantaged perceive their treatment. Failure to appreciate the pitfalls for visibly treating certain customers more favorably and others demonstrably less so, will have stark consequences for retail management and consumer marketing. Originality/value – Contributions are made to the literatures on CRM and on unfairness, particularly in terms of how to address the inevitable inequities inherent in retailers’ CRM offerings. Identification of the advantaged and disadvantaged customers and their respective views allows marketers to develop more appropriate approaches for handling customers who are sensitive to perceived unfairness.

Sequential designs for phase III clinical trials incorporating treatment selection

Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power. Copyright © 2003 John Wiley & Sons, Ltd.

An adaptive group sequential design for phase II/III clinical trials that select a single treatment from several

There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.