Paper Info
Title
Empirically Derived Recommendations for Personalised Text-Based Technical Support.
Abstract
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.
Year
DOI
Venue
2016
10.1007/978-3-319-38980-6_23
Communications in Computer and Information Science
Keywords
Field
DocType
Information technology,Technical support,User characteristics,Online technical support forums,Individualisation,Human factors,Grounded theory
Grounded theory,Revenue,World Wide Web,Loyalty business model,Computer science,Information technology,Knowledge management,Technical communication,Software,Technical support,Reputation
Conference
Volume
ISSN
Citations 
609
1865-0929
1
PageRank 
References 
Authors
0.39
9
3
Name
Order
Citations
PageRank
Solomon Gizaw131.48
Jim Buckley26010.58
Sarah Beecham329022.70