EconPapers    
Economics at your fingertips  
 

Modeling Partial Customer Churn: On the Value of First Product-Category Purchase Sequences

V. L. Miguéis (), Dirk Van den Poel (), A.S. Camanho and J. Falcao E Cunha
Additional contact information
J. Falcao E Cunha: -

Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium from Ghent University, Faculty of Economics and Business Administration

Abstract: Retaining customers has been considered one of the most critical challenges among those included in Customer Relationship Management (CRM), particularly in the grocery retail sector. In this context, an accurate prediction whether or not a customer will leave the company, i.e. churn prediction, is crucial for companies to conduct effective retention campaigns. This paper proposes to include in partial churn detection models the succession of first products’ categories purchased as a proxy of the state of trust and demand maturity of a customer towards a company in grocery retailing. Motivated by the importance of the first impressions and risks experienced recently on the current state of the relationship, we model the first purchase succession in chronological order as well as in reverse order, respectively. Due to the variable relevance of the first customer-company interactions and of the most recent interactions, these two variables are modeled by considering a variable length of the sequence. In this study we use logistic regression as the classification technique. A real sample of approximately 75,000 new customers taken from the data warehouse of a European retail company is used to test the proposed models. The area under the receiver operating characteristic curve and 1%, 5% and 10% percentiles lift are used to assess the performance of the partial-churn prediction models. The empirical results reveal that both proposed models outperform the standard RFM model.

Keywords: Marketing; Customer relationship management; Churn analysis; Predictive analytics; Sequence analysis; Retailing; Classification; Logistic regression (search for similar items in EconPapers)
Pages: 16 pages
Date: 2012-05
New Economics Papers: this item is included in nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed

Downloads: (external link)
http://wps-feb.ugent.be/Papers/wp_12_790.pdf (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:rug:rugwps:12/790

Access Statistics for this paper

More papers in Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium from Ghent University, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Nathalie Verhaeghe ().

 
Page updated 2022-10-05
Handle: RePEc:rug:rugwps:12/790