Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences

• Tipo: Artigo em Revista Científica Internacional
• Data: 2012

Autores

Vera L. Miguéis (Autor) FEUP; Dirk Van den Poel (Autor) FEUP; A. S. Camanho (Autor) FEUP; J. Falcão e Cunha (Autor) FEUP

Revista

Título: Advances in Data Analysis and Classification

Vol. 6 Nº 4

Páginas: 337-353

ISSN: 1862-5347

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 17 Citações

ISI Web of Science

Scopus - 18 Citações

Classificação Científica

FOS: Ciências sociais > Economia e gestão

Outras Informações

ID Authenticus: P-002-2WP

DOI: 10.1007/s11634-012-0121-3

Abstract (EN): Currently, in order to remain competitive companies are adopting customer centered strategies and consequently customer relationship management is gaining increasing importance. In this context, customer retention deserves particular attention. This paper proposes a model for partial churn detection in the retail grocery sector that includes as a predictor the similarity of the products' first purchase sequence with churner and non-churner sequences. The sequence of first purchase events is modeled using Markov for discrimination. Two classification techniques are used in the empirical study: logistic regression and random forests. A real sample of approximately 95,000 new customers is analyzed taken from the data warehouse of a European retailing company. The empirical results reveal the relevance of the inclusion of a products' sequence likelihood in partial churn prediction models, as well as the supremacy of logistic regression when compared with random forests.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 17