Customer Experience Management Architecture for Enhancing Corporate Customer Centric Capabilities

Dominik Paweł Ryżko , Jan Kaczmarek


The paper reports results of theoretical research aimed at devising methods for representation of experience in computer systems for the purpose of implementing Customer Experience Management (CEM) systems. The paper introduces a novel architecture for modelling customer experience with respect to company, brand, product and its relation to consumer decisions. A process for customer experience approximation is proposed and links to customer decision making are mapped. Experience gaining by a customer has been modelled as a learning process which opens up the way for applying various machine learning algorithms to customer experience emulation. Each customer is represented as an intelligent agent, which reflects the distributed nature of the problem and allows for autonomy of its elements. It is shown how the architecture can be utilised with existing resources e.g. Customer Relationship Management systems as a source of data for CEM.
Author Dominik Paweł Ryżko (FEIT / IN)
Dominik Paweł Ryżko,,
- The Institute of Computer Science
, Jan Kaczmarek (FEIT / IN)
Jan Kaczmarek,,
- The Institute of Computer Science
Book Ryżko Dominik Paweł, Rybiński Henryk, Gawrysiak Piotr, Kryszkiewicz Marzena (eds.): Emerging Intelligent Technologies in Industry, Studies in Computational Intelligence, vol. 369, 2011, Springer, ISBN 978-3-642-22731-8, 342 p., DOI:10.1007/978-3-642-22732-5
ASJC Classification1702 Artificial Intelligence
ProjectDevelopment of new methods and algorithms in the following areas: computer graphics, artificial intelligence, and information systems; and distributed systems. Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 24-06-2010, planned end date 31-12-2010, end date 30-11-2011, II/2010/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
ryzko-kaczmarek.pdf 217.17 KB
Score (nominal)4
Publication indicators Scopus Citations = 0; WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2011 = 0.384
Citation count*3 (2020-03-07)
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