Design and analysis of loyalty reward programs

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Abstract/Contents

Abstract
This thesis provides an in-depth analysis of two major components in the design of loyalty reward programs. First, we discuss the design of coalition loyalty programs - schemes where customers can earn and spend reward points across multiple merchant partners. And second, we conduct a model based comparison of a standalone loyalty reward program against traditional pricing - we theoretically characterize the conditions under which it is better to run a reward program within a competitive environment. Coalition loyalty programs are agreements between merchants allowing their customers to exchange reward points from one merchant to another at agreed upon exchange rates. Such exchanges lead to transfer of liabilities between merchant partners, which need to be frequently settled using payments. We first conduct an empirical investigation of existing coalitions, and formulate an analytical model of bargaining for merchant partners to agree upon the exchange rate and payment parameters. We show that our bargaining model produces networks that are close to optimal in terms of social welfare, in addition to cohering with empirical observations. Then, we introduce a novel alternate methodology for settling the transferred liabilities between merchants participating in a coalition. Our model has three interesting properties -- it is decentralized, arbitrage-proof, and fair against market power concentration -- which make it a real alternative to how settlements happen in coalition loyalty programs. Finally, we investigate the design of an optimal reward program for a merchant competing against a traditional pricing merchant, for varying customer populations, where customers measure their utility in rational economic terms. We assume customers are either myopic or strategic, and have a prior loyalty bias toward the reward program merchant, drawn from a known distribution. We show that for the reward program to perform better, it is necessary for a minimum fraction of the customer population to be strategic, and the loyalty bias distribution to be within an optimal range. This thesis is a useful read for marketers building promotional schemes within retail, researchers in the field of marketing and behavioral science, and companies investigating the intersection of customer behavior, loyalty, and virtual currencies.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2017
Issuance monographic
Language English

Creators/Contributors

Associated with Goel, Arpit Amar
Associated with Stanford University, Department of Management Science and Engineering.
Primary advisor Goel, Ashish
Thesis advisor Goel, Ashish
Thesis advisor Iancu, Dan
Thesis advisor Johari, Ramesh, 1976-
Advisor Iancu, Dan
Advisor Johari, Ramesh, 1976-

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Arpit Amar Goel.
Note Submitted to the Department of Management Science and Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2017.
Location electronic resource

Access conditions

Copyright
© 2017 by Arpit Amar Goel
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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