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Augmenting Analytical CRM Strategies with Social BI

Author

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  • Daniel Beverungen

    (European Research Center for Information Systems, University of Münster, Münster, Germany)

  • Mathias Eggert

    (European Research Center for Information Systems, University of Münster, Münster, Germany)

  • Matthias Voigt

    (European Research Center for Information Systems, University of Münster, Münster, Germany)

  • Michael Rosemann

    (Department of Science and Engineering, Queensland University of Technology, Brisbane, QLD, Australia)

Abstract

Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

Suggested Citation

  • Daniel Beverungen & Mathias Eggert & Matthias Voigt & Michael Rosemann, 2013. "Augmenting Analytical CRM Strategies with Social BI," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 4(3), pages 32-49, July.
    • Handle: RePEc:igg:jbir00:v:4:y:2013:i:3:p:32-49
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    Cited by:

    1. Maas, Peter & Schmid, Kevin Paul & Steiner, Philipp Hendrik, 2016. "Social Data – Wie wertvolles Kundenwissen aus den Social Media die CRM Systeme der Assekuranz bereichern kann," Marketing Review St.Gallen, Universität St.Gallen, Institut für Marketing und Customer Insight, vol. 33(2), pages 42-53.

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