Empirically Derived Recommendations for Personalised Text-Based Technical Support

Technical Support (TS) is a post sales service provided to users of Information Technology (IT) products where, ideally, TS advisors respond to users’ needs in a timely and effective way when they have problems using a product. Users are not fully satisfied with company-based TS services; partially due to the lack of guidance and support on how they should use information to learn about their software systems and how to assist them when problems arise. This paper presents empirically-derived practices for Technical Support (TS) services. Through an analysis of online forums we identified types of users (personas) and grouped them according to levels of expertise and what they value. Additionally we identified characteristics of the communication handling process that influence desirable and undesirable outcomes. Focussing solely on text based support, we present ways that TS advisors can identify user types and, having identified the user type, how to tailor their response accordingly. Finally, we also indicate how ignoring user-types or through inappropriate handling of a question, the TS advisor/user interaction can fail. There are indications that adopting this persona-level of support will lead to an improved TS, with a higher likelihood of a successful outcome. Successful outcomes have implications for customer retention, company growth, improved reputation of the company, and improved quality of the software being devel-