Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence

  • Hafedh MiliEmail author
  • Imen Benzarti
  • Marie-Jean Meurs
  • Abdellatif Obaid
  • Javier Gonzalez-Huerta
  • Narjes Haj-Salem
  • Anis Boubaker
Part of the Studies in Computational Intelligence book series (SCI, volume 639)


Customer experience management (CEM) denotes a set of practices, processes, and tools, that aim at personalizing customer’s interactions with a company according to customer’s needs and desires (Weijters et al., J Serv Res 10(1):3–21, 2007 [29]). E-business specialists have long realized the potential of ubiquitous computing to develop context-aware CEM applications (CA-CEM), and have been imagining CA-CEM scenarios that exploit a rich combination of sensor data, customer profile data, and historical data about the customer’s interactions with his environment. However, to realize this potential, e-commerce tool vendors need to figure out which software functionalities to incorporate into their products that their customers (e.g. retailers) could use/configure to build CA-CEM solutions. We propose to provide such functionalities in the form of an application framework within which CA-CEM functionalities can be specified, designed, and implemented. Our framework relies on, (1) a cognitive modeling of the purchasing process, identifying potential touchpoints between sellers and buyers, and relevant influence factors, (2) an ontology to represent relevant information about consumer categories, property types, products, and promotional material, (3) computational intelligence techniques to compute consumer- or category-specific property values, and (4) approximate reasoning algorithms to implement some of the CEM functionalities. In this paper, we present the principles underlying our framework, and outline steps for using the framework for particular purchase scenarios. We conclude by discussing directions for future research.


Customer experience management Customer behavior modeling Service design Customer profile ontology Product ontology Recommendation systems Context awareness Computational Intelligence Data mining 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Hafedh Mili
    • 1
    Email author
  • Imen Benzarti
    • 1
  • Marie-Jean Meurs
    • 1
  • Abdellatif Obaid
    • 1
  • Javier Gonzalez-Huerta
    • 1
  • Narjes Haj-Salem
    • 1
  • Anis Boubaker
    • 1
  1. 1.LATECE LaboratoryUniversité du Québec à MontréalMontréalCanada

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