CRISP:基于客户反应的迭代分割程序,用于直接营销中的反应建模

Wayne S. DeSarbo , Venkatram Ramaswamy
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引用次数: 64

摘要

我们提出了一种称为CRISP(基于客户响应的迭代分割程序)的经验分割程序系统,用于同时导出细分市场并估计每个细分市场中的客户响应模型。虽然响应建模的常见做法是估计数据库中所有客户的单一响应模型,但我们通过校准不同(未知)客户细分的响应模型来考虑客户异质性。我们描述了一个迭代分割程序系统,该系统同时估计客户细分的数量,每个衍生细分的大小,细分级响应参数的值及其统计显著性,所有这些都在一个最大似然框架中,可以容纳各种类型的常见收集的响应数据。为了说明CRISP系统,我们讨论了一个经验性应用程序,该应用程序包含大量家庭的典型二进制响应数据,用于从主要杂志出版商那里获得邮件订阅服务。我们描述了CRISP对列表分割这个特殊问题的具体实现,并讨论了它对直接邮件营销人员的潜在用处。最后,我们讨论了CRISP系统在除列表细分之外的其他直接营销环境中用于响应建模的一般用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CRISP: Customer response based iterative segmentation procedures for response modeling in direct marketing

We present a system of empirical segmentation procedures called CRISP (Customer Response-based Iterative Segrnentation Procedures) for simultaneously deriving market segments and estimating models of customer response in each of these segments. While the common practice in response modeling is to estimate a single response model for all customers in the database, we allow for customer heterogeneity by calibrating response models for different (unknown) customer segments. We describe a system of iterative segmentation procedures that simultaneously estimate the number of customer segments, the sizes of each derived segment, the values of segment-level response parameters, and their statistical significance, all in a maximum likelihood framework that can accommodate various types of commonly collected response data. To illustrate the CRISP system, we discuss an empirical application entailing typical binary response data for a large number of households for a mail subscription offer from a major magazine publisher. We describe the specific implementation of CRISP to this particular problem of list segmentation, and discuss its Potential usefulness to direct mail marketers. We conclude by discussing the general uses of the CRISP system for response modeling in other direct marketing contexts besides list segmentation.

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