A New Spatial Classification Methodology for Simultaneous Segmentation, Targeting, and Positioning (STP Analysis) for Marketing Research

W. DeSarbo, Simon J. Blanchard, S. Atalay
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引用次数: 6

Abstract

The Segmentation-Targeting-Positioning (STP) process is the foundation of all marketing strategy. This chapter presents a new constrained clusterwise multidimensional unfolding procedure for performing STP that simultaneously identifies consumer segments, derives a joint space of brand coordinates and segment-level ideal points, and creates a link between specified product attributes and brand locations in the derived joint space. This latter feature permits a variety of policy simulations by brand(s), as well as subsequent positioning optimization and targeting. We first begin with a brief review of the STP framework and optimal product positioning literature. The technical details of the proposed procedure are then presented, as well as a description of the various types of simulations and subsequent optimization that can be performed. An application is provided concerning consumers' intentions to buy various competitive brands of portable telephones. The results of the proposed methodology are then compared to a naive sequential application of multidimensional unfolding, clustering, and correlation/regression analyses with this same communication devices data. Finally, directions for future research are given.
一种用于市场研究的同时分割、目标和定位(STP分析)的新的空间分类方法
细分-目标-定位(STP)过程是所有营销策略的基础。本章提出了一种新的约束集群多维展开过程,用于执行STP,该过程同时识别消费者细分,导出品牌坐标和细分级理想点的联合空间,并在派生的联合空间中创建指定产品属性和品牌位置之间的联系。后一项功能允许品牌进行各种策略模拟,以及随后的定位优化和目标定位。我们首先简要回顾STP框架和最优产品定位文献。然后介绍了所提出程序的技术细节,以及对各种类型的模拟和可执行的后续优化的描述。提供了一个关于消费者购买各种竞争品牌移动电话的意向的应用程序。然后将提出的方法的结果与使用相同通信设备数据的多维展开、聚类和相关/回归分析的朴素顺序应用进行比较。最后,对今后的研究方向进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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