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. Effective customer support can increase an IT company's revenue, improve the quality of their software, build customer loyalty, and enhance their reputation. However, not all companies realise these benefits as many customers and users are choosing alternative forms of support such as open source non-proprietary support forums.This paper posits that this movement to forums is because of a perceived improvement in service levels and thus presents a study of empirically-derived practices for Technical Support (TS) from these forums. In this analysis 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.