Authors
Gilles Beaudon, Eddie Soulier,
Title
Datum Based Event Mining: The Case of Customer Experience in Insurance
In
Proceedings of the 2018 International Conference on Computational Science and Computational Intelligence (CSCI'18: 13-15 December 2018, Las Vegas, Nevada, USA)
Pages
1099–1104
Publisher
IEEE Computer Society
Year
2018
Publisher's URL
https://american-cse.org/csci2018/pdfs/CSCI2018-3OvSlHpbnpxVCh7wjFqa17/3q9vMvBEeNZ9Rd6kaysIhi/25vj5mbfCTNRWMASyMXLU4.pdf
Indexed by
Abstract
To face deep changes of Insurance market, French Mutual Health-Insurers (FMHI) have to improve their Customer Experience Management (CEM). CEM is based on Customer Experience (CE) analytics. Our paper explores issues observed throughout collaborative workshops focused on designing CE. Marketing executives lead those and utilize Customer Journey Application (CJA) to analyze CE. In our case, journey visualizations created with CJA are decontextualized. That problem comes from raw interactions (customer’s single contact) used and obtained through FMHI’s information system. We propose to enrich CJA with massive and contextual data (Datum) whence customers’ interactions emerge. Our contribution here is to improve interactions’ sequences visualizations (Trajectories) for marketing executives. That is made possible through the use of Classification and Event Mining techniques. The combination of those techniques allows offering new qualitative analytics on CE.
Affiliations
Offprint