Quantifying the effect of status in a multi-tier loyalty program

Abstract

Multi-Tier Loyalty Programs (MTLPs) have become a popular marketing instrument to develop customer-firm relationships. Within a MTLP, customers are assigned to different tiers based on their purchase behavior. In this article, we examine whether and when tiers in the MTLP are effective in influencing customer purchase behavior, specifically share of wallet (SOW). A unique business-to-business dataset of a firm in the German agricultural market from 2009 to 2017 is used for the analysis. Data is available on the customer-specific tier level in the MTLP each year. We utilize a Tobit-style panel regression model for the analysis which is inspired by the Regression Discontinuity Design approach. This study makes several important contributions. First, it examines the effect of status in MTLPs and uses causal design to quantify the hitherto intangible effect of customer tiers. Second, this study reveals important insights on how the tier levels interact with other drivers of customer-firm relationships. Third, we use an interesting dataset from a B2B market and thereby contribute to the limited existing literature on the effectiveness of loyalty programs in B2B markets. Armed with a new understanding of how customers respond to tier levels or the negative effects of tenure especially in the highest tier, academics and managers gain new perspectives of whether and how loyalty programs affect customer behavior and drive desired outcomes in the marketplace. © 202

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