Planning Pre-Launch Positioning: Segmentation Via Willingness-to-Pay and Means-End Brand Differentiators

20 Pages Posted: 24 Apr 2018

See all articles by Michael Mulvey

Michael Mulvey

affiliation not provided to SSRN

Date Written: February 2017

Abstract

Brand positioning is effective only to the extent that it aligns with prospects’ needs and interests and is viewed as worth spending their money on. Accordingly, marketing needs research tools that are capable of identifying the criteria that consumers use when choosing a brand in a given category. Yet all too often, studies ask consumers to rate brands with pre-specified attributes and benefit lists that may be at variance with the standards that come to mind naturally without cued prompting. Moreover, such methods may fail to capture the elusive – yet crucial – salient higher-order social and psychoemotional reasons that lend importance to an individual’s decision and willingness-to-pay. This research builds on and extends the means-end approach to brand positioning that looks at brands through consumers’ eyes by developing a latent class segmentation model that examines preference heterogeneity and identifies segment-level differences in decision themes and reservation prices. Using data from an empirical field study, the model detects three distinct segments of potential high-end adopters of a next-generation cellphone with innovative design features. The results offer insights to guide go-to-market branding strategy, and related product line, pricing, and positioning decisions. Implications for customer value assessment, benefit-based market segmentation, and innovation management are discussed.

Keywords: brand positioning, means-end theory, innovation adoption, customer value-based pricing, segmentation, latent class regression

Suggested Citation

Mulvey, Michael, Planning Pre-Launch Positioning: Segmentation Via Willingness-to-Pay and Means-End Brand Differentiators (February 2017). Journal of Brand Management, Vol. 24, Issue 3, 2017. Available at SSRN: https://ssrn.com/abstract=3160712 or http://dx.doi.org/10.1057/s41262-017-0030-z

Michael Mulvey

affiliation not provided to SSRN

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