Universität zu Köln

Venkatesan, Rajkumar, Bleier, Alexander, Reinartz, Werner ORCID: 0000-0002-2440-3117 and Ravishanker, Nalini (2019). Improving customer profit predictions with customer mindset metrics through multiple overimputation. J. Acad. Mark. Sci., 47 (5). S. 771 - 795. NEW YORK: SPRINGER. ISSN 1552-7824

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Abstract

Research and practice have called for the incorporation of customer mindset metrics (CMMs) to improve the accuracy of models that predict individual customer profits. However, as CMMs are self-reported data, collected through customer surveys, they are seldom available for a firm's entire customer database and in addition always measured with some degree of error. Their usage in models for individual-level predictions of customer profit has therefore proven challenging. We offer a solution through a new method called multiple overimputation (MO). MO treats missing data as an extreme form of measurement error and imputes the CMMs for both customers with observed, albeit with measurement error, as well as missing values, that are then included as predictors in a model of individual customer profits. Through a simulation study, empirical application in the pharmaceutical industry, and a customer selection exercise, we demonstrate the predictive and economic value of applying MO in the context of CRM.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Venkatesan, Rajkumar UNSPECIFIED UNSPECIFIED UNSPECIFIED Bleier, Alexander UNSPECIFIED UNSPECIFIED UNSPECIFIED Reinartz, Werner UNSPECIFIED orcid.org/0000-0002-2440-3117 UNSPECIFIED Ravishanker, Nalini UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-143651
DOI:	10.1007/s11747-019-00658-6
Journal or Publication Title:	J. Acad. Mark. Sci.
Volume:	47
Number:	5
Page Range:	S. 771 - 795
Date:	2019
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1552-7824
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DYNAMIC-MODEL; DATA FUSION; LIFETIME VALUE; SATISFACTION; MANAGEMENT; BEHAVIOR; IMPACT; PHYSICIANS; SHARE; CLV Multiple languages Business Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14365