Marketers and advertisers seek to get close to customers through data analytics procedures that allow for the measurement of personalized messages delivered across multiple communication touchpoints. This article tests a hierarchical integrated marketing communications data integration framework that utilizes customer information (transactional, demographic and psychographic) to develop personalized communication and communication campaigns distributed across multiple interactive customer touchpoints. Our model posits that by using basic customer data we can increase the priority for collecting other types of data needed to get close to customers. Our findings show that customer data needs are hierarchically ordered and that the sequential interaction between these variables impacts customer relationship management system quality and measurement of performance.
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We are grateful to the Marketing Science Institute, the Direct Marketing Policy Center at the University of Cincinnati and the University of Wisconsin, Whitewater for their financial support of the data collection phase of this research.
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Peltier, J., Zahay, D. & Krishen, A. A hierarchical IMC data integration and measurement framework and its impact on CRM system quality and customer performance. J Market Anal 1, 32–48 (2013). https://doi.org/10.1057/jma.2013.1
- marketing analytics
- customer data
- integrated marketing communications (IMC)
- data quality
- customer relationship management (CRM)
- marketing metrics