A Multiactivity Latent Attrition Model for Customer Base Analysis

David A. Schweidel (), Young-Hoon Park () and Zainab Jamal ()
Additional contact information
David A. Schweidel: Goizueta Business School, Emory University, Atlanta, Georgia 30322
Young-Hoon Park: Samuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, New York 14853
Zainab Jamal: Hewlett-Packard Labs, Palo Alto, California 94304

Marketing Science, 2014, vol. 33, issue 2, 273-286

Abstract: Customer base analysis is a key element in customer valuation and can provide guidance for decisions such as resource allocation. Yet extant models often focus on a single activity, such as purchases from a retailer or donations to a nonprofit organization. These models do not consider other ways that an individual may engage with an organization, such as purchasing in multiple brands or contributing user-generated content. In this research, we propose a framework to generalize extant models for customer base analysis to multiple activities.Using the data from a website that allows users to purchase digital content and/or post digital content at no charge, we develop a flexible “buy ‘til you die” model to empirically examine how the two activities are related. Compared with benchmarks, our model more accurately forecasts the future behavior for both types of activities. In addition to finding evidence of coincidence between the activities while customers are “alive,” we find that the latent attrition processes are related. This suggests that conducting one type of activity is informative of whether customers are still alive to conduct another type of activity and, consequently, affects inferences of customer value.

Keywords: customer base analysis; latent changepoint model; multivariate choice model; multivariate “buy ‘til you die” model; digital content (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.2013.0832 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:33:y:2014:i:2:p:273-286

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().