Methods and Measures That Profile Heavy Users
本文指出常用均值比较法在重度用户细分中的诊断缺陷，提出一种聚类方法有效区分重度与轻度用户，并发现人格特征比生活方式或人口统计特征更能区分两者。
<h3>ABSTRACT</h3> Heavy users can be a critical segment for packaged-goods marketers to target. Yet many attempts to profile heavy users have proven to be unsuccessful because of methodological and measurement problems. This article shows the diagnostic shortcomings of the commonly used mean comparison method of heavy-user segmentation, and it presents a clustering method that effectively differentiates different types of heavy users from light users. Characteristics that differentiate heavy and light users were collected from academic and commercial studies and are shown to relate to five basic lifestyle factors and six personality sectors. Whilse providing a key starting point for studying heavy users, they also show the dominant role that personality characteristics (as opposed to lifestyle or demographic characteristics) play in differentiating heavy and light users.