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Modeling large data sets in marketing[Note 1. The authors are very grateful to Philip Hans Franses ...]
Author(s) -
Balasubramanian S.,
Gupta S.,
Kamakura W.,
Wedel M.
Publication year - 1998
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/1467-9574.00086
Subject(s) - computer science , data science , database transaction , database marketing , transaction data , focus (optics) , profit (economics) , data mining , database , marketing , business , marketing management , relationship marketing , physics , economics , microeconomics , optics
In the last two decades, marketing databases have grown significantly in terms of size and richness of available information. The analysis of these databases raises several information‐related and statistical issues. We aim at providing an overview of a selection of issues related to the analysis of large data sets. We focus on the two important areas: single source databases and customer transaction databases. We discuss models that have been used to describe customer behavior in these fields. Among the issues discussed are the development of parsimonious models, estimation methods, aggregation of data, data‐fusion and the optimization of customer‐level profit functions. We conclude that problems related to the analysis of large databases are far from resolved, and will stimulate new research avenues in the near future.