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    A model for the adaptation of contact centre computer user interfaces

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    Article (820.6Kb)
    Date
    2009
    Author
    Jason, Bronwin
    Calitz, Andrè
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    Abstract
    Maintaining effective customer contact is important because customer interaction is seen as a valuable asset for building lasting and profitable customer relationships. Contact centres, are the primary interaction point between a company and its customers. One of the important challenges in today’s contact centre solutions is to increase the speed at which contact centre agents (CCAs) retrieve information to answer customer queries. CCAs however have different capabilities, experience and expertise. Studies have provided empirical support that user performance can be increased when the computer user interface (UI) characteristics match the user skill level. As a result, software systems have to become more individualised and cater for different users. Users are normally classified as either experts or novices, and in some cases somewhere in-between. There is evidence to support the fact that novice and expert users behave differently when using a specific UI. Expertise and skill affects the way users interact with software. It is thus envisaged that an adaptive user interface (AUI) which dynamically changes from a novice UI to an expert UI could possibly improve users’ performance. This research focuses on applying this concept of AUIs to the domain of contact centres and investigates whether an AUI for CCAs could improve the CCA’s performance. A model was proposed for AUIs which was applied to the domain of contact centres. Implementation was done on the proposed model as proof of concept and the model was then evaluated. Results indicate a difference in interaction data for novice and expert CCAs and this shows that the proposed model can be used to provide an AUI for both novice and expert CCAs. Most users approved the use of AUIs and the research showed that AUIs can improve the speed at which CCAs provide call resolution.
    URI
    http://hdl.handle.net/10570/701
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    • School of Computing and Informatics Technology (CIT) Collection

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