A Predictive Model of Redemption and Liability in Loyalty Reward Programs Industry

Abstract

Loyalty reward programs (LRPs), initially developed as marketing programs to enhance customer retention, have now become an important part of customer-focused business strategies. With the growth in these programs, the complexities in their management and control have also increased. One of the challenges faced by LRPs managers is that of developing models to address various forecasting issues to support short, medium, and long term planning and operational decision-making. We propose in this paper a predictive model of redemption and liability in LRPs. The proposed approach is an aggregate inventory model in which the liability of points is modeled as a stochastic process. An illustrative example is discussed as well as a real-life implementation of the methodology to facilitate use and deployment considerations in the context of a frequent flyer program, an airline industry based LRP.

Cross-cultural analysis of the Frequent Flyer Programs (FFPs): The most controversial results

“…Another block of the literature analyses the need for the effective usage of accumulated customers' information from loyalty programs' databases. The marketing side of the issue is also investigated through factors like right targeting, customization, and marketing campaign design in the frame of price and promotions (Nsakanda et al, 2010). The topic of the current master thesis falls within the second block of existing studies.…”