Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data

Pavel Jasek, Lenka Vrana, Lucie Sperkova, Zdenek Smutny and Marek Kobulsky

Prague Economic Papers, 2019, vol. 2019, issue 6, 648-669

Abstract: The article contributes to the knowledge of customer lifetime value (CLV) models, where extensive empirical analyses on large datasets from online stores are missing. Based on this knowledge, practitioners can decide about the deployment of a particular model in their business and academics can design or enhance CLV models. The article presents predictive performance of selected CLV models: the extended Pareto/NBD model, the Markov chain model, the vector autoregressive model and the status quo model. Six large datasets of medium and large‑sized online stores in the Czech Republic and Slovakia are used for a comparison of the predictive performance of the models. Online stores have annual revenues in the order of tens of millions of euros and more than one million customers. The comparison of CLV models is based on selected evaluation metrics. The results of some of the models which use additional non‑financial data on customer behaviour - the Markov chain model and the vector autoregressive model - do not justify the effort which is needed to collect such data. The advantages and disadvantages of the selected CLV models are discussed in the context of their deployment.

Keywords: CLV models; forecasting; online marketing management; e-commerce; methodology; online shopping; online marketing (search for similar items in EconPapers)
JEL-codes: C53 C55 M21 M31 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://pep.vse.cz/doi/10.18267/j.pep.714.html (text/html)
http://pep.vse.cz/doi/10.18267/j.pep.714.pdf (application/pdf)
free of charge

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:prg:jnlpep:v:2019:y:2019:i:6:id:714:p:648-669

Ordering information: This journal article can be ordered from
Editorial office Prague Economic Papers, University of Economics, nám. W. Churchilla 4, 130 67 Praha 3, Czech Republic
http://pep.vse.cz

DOI: 10.18267/j.pep.714

Access Statistics for this article

Prague Economic Papers is currently edited by Klára Pavlová

More articles in Prague Economic Papers from Prague University of Economics and Business Contact information at EDIRC.
Bibliographic data for series maintained by Stanislav Vojir ().