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On dynamic selection of households for direct marketing based on Markov chain models with memory

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Author Info
Pieter Otter ()
Abstract

A simple, dynamic selection procedure is proposed, based on conditional, expected profits using Markov chain models with memory. The method is easy to apply, only frequencies and mean values have to be calculated or estimated. The method is empirically illustrated using a data set from a charitable foundation. The results reveal some interesting features with respect to the time-dependent behavior of certain subsets of households, whereas the profitability increases by about 9% by using the method compared to a benchmark of sending a mailing to all households. Copyright Springer Science+Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11002-006-9007-5
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Publisher Info
Article provided by Springer in its journal Marketing Letters.

Volume (Year): 18 (2007)
Issue (Month): 1 (June)
Pages: 73-84
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:kap:mktlet:v:18:y:2007:i:1:p:73-84

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Web page: http://www.springerlink.com/link.asp?id=100312

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: Information processing; Segmentation research; Estimation and other statistical techniques;

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This page was last updated on 2010-1-1.


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