Modeling partial customer churn: On the value of first product-category purchase sequences

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Vera L. Miguéis (Author) FEUP; Dirk Van den Poel (Author) Other; A. S. Camanho (Author) FEUP; João Falcão e Cunha (Author) FEUP

Journal

Title: Expert Systems with Applications

Vol. 39 No. 3

Pages: 11250-11256

ISSN: 0957-4174

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 54 Citations

ISI Web of Science

Scopus - 72 Citations

COMPENDEX

INSPEC

Scientific classification

FOS: Social sciences > Other social sciences

CORDIS: Technological sciences > Technology > Information technology ; Humanities > Information science > Information management > Information processing

Other information

Authenticus ID: P-002-5G1

DOI: 10.1016/j.eswa.2012.03.073

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7