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.

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