An empirically-derived personalised theory for technical support

This thesis focuses on Technical Support (TS) as a post sales service provided to users of Information Technology (IT). One of the goals of TS is to maintain a high level of customer satisfaction by providing high quality answers to technical questions. TS Advisers aim to respond to users’ needs in a timely and effective way when they have problems using a product. However, the sophistication of software, frequent changes and updates to new technologies has made developing an effective Technical Support (TS) challenging. Users of software systems need support. These days users are not only demanding a quality product, but also an effective service with respect to product delivery, cost of the product and after sales service. When users choose to go directly to online forums rather than report issues to the source of the problem, software companies lose out. Software companies miss opportunities to gather information on where their systems could be improved, and can lose customer loyalty, future sales and goodwill. With the growing user and customer demands, service providers are looking for ways to provide better TS. In particular, software companies are starting to realise the importance of incorporating users’ individual characteristics in their TS for an improved user experience. The explicit aim of the research presented in this thesis is to empirically derive and evaluate TS User behaviour in order to determine prevalent user characteristics and prevalent interaction characteristics in TS. Empirically derived personalised characteristics could strengthen the current understanding of how to characterise users. Taking an inductive approach may provide novel perspectives and new characteristics that may, if implemented, improve TS. Providing an empirical basis for such user characteristics could provide important evaluation of presumably relevant personalisation attributes in TS, and interaction characterisation could provide a strong basis for determining how best to handle different characteristics of users and customise content for individuals. Without such empirically grounded characterization, efforts to personalise TS may be misguided. Users and TS Advisers’ behaviour is investigated by analysis of the related TS and personalisation literature. Grounded Theory method (GT) is also adopted to investigate users and TS Advisers’ behaviour in several TS web-forums dataset, where individual/interaction characteristics are identified towards improving TS personalised practices. The contribution of this research is an empirically derived substantive theory (Personalisation In Practice) that identifies TS Users according to groups of characteristics. Analysis of the data suggests that users of TS systems can be grouped according to their level of expertise and what they value. Additionally the communication handling process can influence desirable and undesirable outcomes. Derived from this, recommendations are presented based on the successful work-practices of personalised TS services. This assessment of the informal TS forums is aimed at supporting TS in a company-based setting. These emerging user characteristics can be considered during company-based TS system development to enhance the service in a more targeted, personalised manner.