The Disturbance of Abnormal Events to Customer Value: An Application of Individual-level Hierarchical Bayesian Models
Date Issued
2007
Date
2007
Author(s)
Wang, Wei-Lin
DOI
en-US
Abstract
Customer value is a key reference for businesses to formulate marketing strategies. From the suppliers’ perspectives, customer lifetime value is a managerial tool which is used to calculate the present value of the profit contributed by each customer. However, customer lifetime value models usually ignore the impact of abnormal events due the lack of data, and therefore overestimate/underestimate the true customer lifetime value.
Since the occurrence of an abnormal event is identified, this study regards customers who have been affected by the event as the experimental group. Besides, this research uses individual-level hierarchical Bayesian models to simulate the true customer lifetime value of customers belong to the experimental group based on data previous to the occurrence of the event. Furthermore, another group of customers who have not been influenced by the event are regarded as the control group which is used to adjust the simulated customer lifetime value of the experimental group. Finally, by comparing the simulated value after adjustment and the realized value, the disturbance of the abnormal event to customers from the experimental group could be estimated.
In empirical study, this research studies an online stationary vender in Taiwan. The customer database of this company was stolen and leveraged to run a new business by an ex-employee of the company. To study this abnormal event, this research select customers who had been recorded in the database before the event occurred with at least two transactions both ex ante and ex post as the experimental group. In addition, other customers who was recorded in the database after the occurrence of the event and have at least two transactions are chosen as the control group, After the analysis, this research finds that the abnormal event does decrease the customer lifetime value of customers from the experimental group, and the loss value in terms of cumulative sales at the 228 day after the event occurred is NT$ 3,377,181.
Another finding in this study is that although all customers keep purchasing after the occurrence of the event, some of them lengthen their inter-purchase time, while others shorten their inter-purchase time. This phenomenon is detected in both groups, but comparing to the control group, more customers from the experimental group lengthen their inter-purchase time. In order to identify whether each customer belonging to the experimental group has a structural change in his or her purchase behavior in terms of inter-purchase time after the event occurred, individual-level hierarchical Bayesian mixture models are introduced. Unfortunately, these models face the question of under-identified. Thus, future researches are needed to improve the method and to study the tapped but unsolved issue.
Subjects
顧客價值
顧客終生價值
異常事件
層級貝式模型
購買期間
層級貝式混合模型
customer value
customer lifetime value
abnormal event
hierarchical Bayesian model
inter-purchase time
hierarchical Bayesian mixture model
Type
thesis
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