 Monte Carlo analysis of estimation methods for the prediction of customer response patterns in direct marketingYoung H. Chun European Journal of Operational Research, 2012, vol. 217, issue 3, 673-678 Abstract: In direct marketing, customers are usually asked to take a specific action, and their responses are recorded over time and stored in a database. Based on the response data, we can estimate the number of customers who will ultimately respond, the number of responses anticipated to receive by a certain period of time, and the like. The goal of this article is to derive and propose several estimation methods and compare their performances in a Monte Carlo simulation. The response patterns can be described by a simple geometric function, which relates the number of responses to elapsed time. The “maximum likelihood” estimator appears to be the most effective method of estimating the parameters of this function. As we have more sample observations, the maximum likelihood estimates also converge to the true parameter values rapidly. Keywords: Response pattern; Direct marketing; Probabilistic modeling (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:217:y:2012:i:3:p:673-678 DOI: 10.1016/j.ejor.2011.10.008 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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