SegmentTalk: the difference engine: a comparison of loyalty marketing perceptions among specific US consumer segments

Rick Ferguson (COLLOQUY, Milford, Cincinnati, Ohio, USA)
Kelly Hlavinka (COLLOQUY, Milford, Cincinnati, Ohio, USA)

Journal of Consumer Marketing

ISSN: 0736-3761

Publication date: 21 March 2008



The purpose of this paper is to use current loyalty market landscape data to examine differences in loyalty‐program participation among key consumer segments.


Using data from the Loyalty Census research study conducted by COLLOQUY (JCM v24i5), this paper applies the information to six demographic segments of high interest to loyalty‐marketing practitioners – affluent, young adult, senior, core women, emerging Hispanic, and general adult – to determine rends related to participation, needs, redemption, and satisfaction.


The paper identifies the emergence of underserved and important demographic segments looking for attention in the world of loyalty marketing. The paper also establishes the new battlegrounds for loyalty programs in regards to rewards and redemption. Finally, the research reveals fresh strategies for marketers designing loyalty offerings.

Practical implications

Personalization is key to driving participation in contemporary loyalty marketing programs. Companies must identify the individual and tailor rewards, offers and benefits ‐ constructing a “difference engine” to serve all markets, build advocacy, retention and return on investment.


The paper further deconstructs the current loyalty marketing landscape and spotlights budding demographic segments previously overlooked or understudied. The text derives ten concrete suggestions from the data for building successful loyalty programs in today's changing market.



Ferguson, R. and Hlavinka, K. (2008), "SegmentTalk: the difference engine: a comparison of loyalty marketing perceptions among specific US consumer segments", Journal of Consumer Marketing, Vol. 25 No. 2, pp. 115-127.

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Copyright © 2008, Emerald Group Publishing Limited

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