Abstract
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.
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Ryżko, D., Kaczmarek, J. (2011). Customer Experience Management Architecture for Enhancing Corporate Customer Centric Capabilities. In: Ryżko, D., Rybiński, H., Gawrysiak, P., Kryszkiewicz, M. (eds) Emerging Intelligent Technologies in Industry. Studies in Computational Intelligence, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22732-5_26
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DOI: https://doi.org/10.1007/978-3-642-22732-5_26
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