Comparing Approaches to Elicit Brand Attributes both Face-to-face and Online

Abstract

Brand attributes play an important role in tracking customer-based brand equity. Therefore researchers need an effective approach for eliciting attributes. This paper has two aims: to determine which of four different techniques elicit(s) better results; and to test if online data collection is a viable alternative to face-to-face collection. The techniques compared are: Zaltman Metaphor Elicitation Technique (ZMET), Free Elicitation (FE), Repertory Grid (RG) and Projective Elicitation (PE). These approaches are compared on the number and variety of attributes generated, as well as respondent evaluation. FE is the best-performing technique in a face-to-face context, generating the most attributes, evaluated positively by respondents and providing a typical distribution of attribute types. We also provide evidence that online is a viable data collection method for attribute elicitation studies, except ZMET due to respondent drop-out. Online we recommend a combination of FE and PE to obtain a range and variety of responses.