Towards Efficient and Informative Omni-Channel Customer Relationship Management
M. Carnein, M. Heuchert, L. Homann, H. Trautmann, G. Vossen, J. Becker, K. Kraume, in: S. de Cesare, F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17), Springer International Publishing, Valencia, Spain, 2017, pp. 69–78.
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Conference Paper
| English
Author
Carnein, Matthias;
Heuchert, Markus;
Homann, Leschek;
Trautmann, HeikeLibreCat 
;
Vossen, Gottfried;
Becker, Jörg;
Kraume, Karsten
;
Vossen, Gottfried;
Becker, Jörg;
Kraume, KarstenEditor
de Cesare, Sergio;
Ulrich, Frank
Abstract
Nowadays customers expect a seamless interaction with companies throughout all available communication channels. However, many companies rely on different software solutions to handle each channel, which leads to heterogeneous IT infrastructures and isolated data sources. Omni-Channel CRM is a holistic approach towards a unified view on the customer across all channels. This paper introduces three case studies which demonstrate challenges of omni-channel CRM and the value it can provide. The first case study shows how to integrate and visualise data from different sources which can support operational and strategic decision. In the second case study, a social media analysis approach is discussed which provides benefits by offering reports of service performance across channels. The third case study applies customer segmentation to an online fashion retailer in order to identify customer profiles.
Publishing Year
Proceedings Title
Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)
forms.conference.field.series_title_volume.label
Lecture Notes in Computer Science
Volume
10651
Page
69–78
ISBN
LibreCat-ID
Cite this
Carnein M, Heuchert M, Homann L, et al. Towards Efficient and Informative Omni-Channel Customer Relationship Management. In: de Cesare S, Ulrich F, eds. Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17). Vol 10651. Lecture Notes in Computer Science. Springer International Publishing; 2017:69–78. doi:10.1007/978-3-319-70625-2_7
Carnein, M., Heuchert, M., Homann, L., Trautmann, H., Vossen, G., Becker, J., & Kraume, K. (2017). Towards Efficient and Informative Omni-Channel Customer Relationship Management. In S. de Cesare & F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17) (Vol. 10651, pp. 69–78). Springer International Publishing. https://doi.org/10.1007/978-3-319-70625-2_7
@inproceedings{Carnein_Heuchert_Homann_Trautmann_Vossen_Becker_Kraume_2017, place={Valencia, Spain}, series={Lecture Notes in Computer Science}, title={Towards Efficient and Informative Omni-Channel Customer Relationship Management}, volume={10651}, DOI={10.1007/978-3-319-70625-2_7}, booktitle={Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)}, publisher={Springer International Publishing}, author={Carnein, Matthias and Heuchert, Markus and Homann, Leschek and Trautmann, Heike and Vossen, Gottfried and Becker, Jörg and Kraume, Karsten}, editor={de Cesare, Sergio and Ulrich, Frank}, year={2017}, pages={69–78}, collection={Lecture Notes in Computer Science} }
Carnein, Matthias, Markus Heuchert, Leschek Homann, Heike Trautmann, Gottfried Vossen, Jörg Becker, and Karsten Kraume. “Towards Efficient and Informative Omni-Channel Customer Relationship Management.” In Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17), edited by Sergio de Cesare and Frank Ulrich, 10651:69–78. Lecture Notes in Computer Science. Valencia, Spain: Springer International Publishing, 2017. https://doi.org/10.1007/978-3-319-70625-2_7.
M. Carnein et al., “Towards Efficient and Informative Omni-Channel Customer Relationship Management,” in Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17), 2017, vol. 10651, pp. 69–78, doi: 10.1007/978-3-319-70625-2_7.
Carnein, Matthias, et al. “Towards Efficient and Informative Omni-Channel Customer Relationship Management.” Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17), edited by Sergio de Cesare and Frank Ulrich, vol. 10651, Springer International Publishing, 2017, pp. 69–78, doi:10.1007/978-3-319-70625-2_7.
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