Volume 4, Issue 1, June 2019, Page: 53-56
Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive
Hui-Hsin Huang, Department of Business Administration, Aletheia University, New Taipei City, Taiwan
Received: Apr. 17, 2019;       Accepted: May 31, 2019;       Published: Jun. 24, 2019
DOI: 10.11648/j.ajdmkd.20190401.18      View  226      Downloads  30
Abstract
In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.
Keywords
Queue, Purchase Rate, The Speed of Product Consumption, Inactive Probability
To cite this article
Hui-Hsin Huang, Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive, American Journal of Data Mining and Knowledge Discovery. Vol. 4, No. 1, 2019, pp. 53-56. doi: 10.11648/j.ajdmkd.20190401.18
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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