How Segmenting by Attitudes vs. Values Can Help Predict Online Behaviors

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Summary

Segmentation by attitudes and values is essential for understanding differences among consumers, but which segment base can help marketers accurately predict online shopping behaviors? A trio of German researchers—a mix of academics and practitioners—used data from a German online apparel retailer to create a model that showed much more differentiated click-through behaviors resulting from segmenting by fashion and online-shopping attitudes, than by value-based segmentation. The key research question was: “Which type of segmentation base produces segments with more differentiated marketing-response behavior?” Using survey data from 3,219 consumers from a German online retailer, along with 163,000 clicks from their consumer database, the research explored the results of three different segmentation models:

human-value based
fashion-attitude based
online shopping-attitude based

Stefan Scheuffelen is a research assistant at RWTH Aachen University, Germany, and a project leader at the Boston Consulting Group in the Berlin area. His research interests are around consumer segmentation and consumer behavior in e-commerce.

Jan Kemper is an assistant professor in innovation management and entrepreneurship at RWTH Aachen University and managing director of Omio, an online travel agency. His research interests center on entrepreneurship, e-commerce, finance, media, and cross-cultural management.

Malte Brettel is professor for business administration at RWTH Aachen University and adjunct professor for entrepreneurship at WHU Otto Beisheim School of Management, Germany.