Understanding Customer Dynamics in a Data-rich Environment 公开

Xu, Nuo (2016)

Permanent URL: https://etd.library.emory.edu/concern/etds/q237hs659?locale=zh
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Abstract

Consumers' behaviors are dynamic. The understanding of these dynamic processes is critical for managerial decisions. In a data rich environment, an effective use of the data can help us uncover these dynamics and deliver actionable intelligence. These three essays all focus on providing solutions to important managerial questions in a data rich environment. The first essay looks into the banking industry where customers' life cycle plays a critical role in their financial activities. The goal of the first essay is to provide a solution based on Cusum control chart to detect a life change of interest using observed customer activities. The recovery of this life change information can help managers better customize direct marketing efforts based on customers' life events. The second essay extends the application of Cusum control chart to detect changes in the market's responses to marketing stimulus. This essay presents another fine property of the Cusum control chart: the test statistic can help managers to trace the time point when changes occur. This time point provides a road map for managers to conceptualize and understand the underlying cause of the change. The plan is to use a dataset provides by Dominic supermarket chain to illustrate the effectiveness of the proposed solution in detecting changes in the pattern of market responses when new brands or new products enter the market. The third essay examines customers' shopping behaviors using a coalition loyalty program in Europe. The goal of the essay is to model the synergies among the merchants participating the coalition loyalty program in order to understand the impact of cross buying on customers' purchase behavior at the focal merchant store overtime. In sum, these three essays provide solutions for managers in a data-rich environment to transfer massive data into customer knowledge and actionable intelligence.

Table of Contents

Chapter 1 1

Chapter 2 8

2.1 Introduction 8

2.2 Literature Review 11

2.3 Empirical Context 15

2.4 Data 17

2.5 Method 20

2.6 Empirical Analysis 32

2.7 Managerial Insights 41

2.8 Discussion 45

Chapter 3 49

3.1 Introduction 49

3.2 Literature Review 52

3.3 A Control Chart Approach to Monitor Market Responses 56

3.4 Simulation 61

3.5 Empirical Study 65

3.6 Conclusion 75

Chapter 4 77

4.1 Introduction 77

4.2 Background and Theory 81

4.3 Research Question and Hypotheses 93

4.4 Data and Method 99

4.5 Empirical Findings 108

4.6 Discussion 117

Chapter 5 122

Bibliography 125

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