Predictive analytics driven campaign management support systems

Kenneth Goul, Sule Balkan, Daniel Dolk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper uses design science research foundations to establish requirements for predictive analytics-driven Campaign Management Support Systems (CMSS). We assert the 'campaign' as the unit of analysis for these systems, because campaign management is central to the marriage of marketing resource management and the ideals of demand/customer-driven supply chains. Current CMMS are fragmented, disconnected and batch-oriented - they are not enterprise-centric. They do not address governance, integrated deployment or the risk of unexpected consequences of campaigns gone awry. However, they should given examples of recent campaign failures at Target and other companies. Further, they do not support domain specific performance measurement and monitoring. We develop requirements for CMSS. We provide a conceptual architecture and monitoring engine. The architecture and engine are founded in vigilant information systems design theory. The CMSS design builds on earlier research in a predictive analytics deployment methodology called 'DEEPER.'

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Hawaii International Conference on System Sciences
PublisherIEEE Computer Society
Pages4782-4791
Number of pages10
Volume2015-March
ISBN (Print)9781479973675
DOIs
StatePublished - Mar 26 2015
Event48th Annual Hawaii International Conference on System Sciences, HICSS 2015 - Kauai, United States
Duration: Jan 5 2015Jan 8 2015

Other

Other48th Annual Hawaii International Conference on System Sciences, HICSS 2015
CountryUnited States
CityKauai
Period1/5/151/8/15

Keywords

  • Campaign management support systems
  • Predictive analytics

ASJC Scopus subject areas

  • Engineering(all)

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    Goul, K., Balkan, S., & Dolk, D. (2015). Predictive analytics driven campaign management support systems. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2015-March, pp. 4782-4791). [7070388] IEEE Computer Society. https://doi.org/10.1109/HICSS.2015.568