Abstract

Successful marketing data analysis depends critically on the quality of the data that are available for analytical work. This paper draws on general quality management concepts as well as recent developments in the field of data quality management to address issues related to marketing data analysis. Marketing databases have a number of particular characteristics that can be described and should be addressed in a quality management programme. Particular recommendations are made for detecting data quality problems that pertain to marketing databases that should be part of a continuous quality management programme. The common application of predictive modelling to drive target marketing programmes should include attention to data quality management issues at both the model building and customer scoring phases. A modelling professional can make significant contributions to ongoing data quality management and should be alert to data quality issues since they are a significant success factor.

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