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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The use of capitalisation is taken directly from the forums, in this context suggests anger, as a textural form of shouting.
References
Stefani, A., Xenos, M.: E-commerce system quality assessment using a model based on ISO 9126 and belief networks. Softw. Qual. J. 16(1), 107–129 (2008)
Oxton, G.: The power and value of on-line communities. In: 2010: Consortium for Service Innovation, Keynote address in Centre for Next Generation Localisation Public Showcase, Localisation Research Centre CSIS Department, University of Limerick, 27 April 2010
Steichen, B., Wade, V.: Adaptive retrieval and composition of socio-semantic content for personalised customer care. In: International Workshop on Adaptation in Social and Semantic Web (2010)
Negash, S., Ryan, T., Igbaria, M.: Quality and effectiveness in web-based customer support systems. Inf. Manage. 40(8), 757–768 (2003)
Gao, N., Zhao, S., Jiang, W.: Researched customer requirements representation and mapping on ontology. In: 2011 International Conference on Management and Service Science (2011)
Lee, Z., Kim, Y., Lee, S.-G.: The influences of media choice on help desk performance perception. In: Proceedings of the 34th Annual Hawaii International Conference on System Sciences. IEEE (2001)
Na, C., et al.: A value-added service model of mining right information. In: 2010 International Conference on E-Business and E-Government (ICEE). IEEE (2010)
Tam, K.Y., Ho, S.Y.: Web personalization: is it effective? IT Prof. 5(5), 53–57 (2003)
Wu, D., et al.: A framework for classifying personalization scheme used on e-commerce websites. In: Proceedings of the 36th Annual Hawaii International Conference on System Sciences. IEEE (2003)
Viviani, M., Bennani, N., Egyed-Zsigmond, E.: A survey on user modeling in multi-application environments. In: Proceedings of the 2010 Third International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services, pp. 111–116. IEEE Computer Society (2010)
Kim, W., Song, Y.U., Hong, J.S.: Web enabled expert systems using hyperlink-based inference. Expert Syst. Appl. 28(1), 79–91 (2005)
Wang, G.A., et al.: ExpertRank: a topic-aware expert finding algorithm for online knowledge communities. Decis. Support Syst. 54(3), 1442–1451 (2013)
Gizaw, S., Buckley, J., Beecham, S.: Characterising users through an analysis of on-line technical support forums. In: Abrahamsson, P., et al. (eds.) PROFES 2015. LNCS, vol. 9459, pp. 528–545. Springer, Heidelberg (2015). doi:10.1007/978-3-319-26844-6_39
Strauss, A., Corbin, J.M.: Basics of Qualitative Research Techniques and Procedures for Developing Grounded Theory, 2nd edn. Sage Publications, London (1998)
Vesanen, J.: What is personalisation? a conceptual framework. Eur. J. Mark. 41(5–6), 409–418 (2007)
Ralph, P., Parsons, J.: A framework for automatic online personalization. In: Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS 2006). IEEE (2006)
Cohen, J.: Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychol. Bull. 70(4), 213 (1968)
Acknowlegments
This work was supported, in part, by Science Foundation Ireland grant 10/CE/I1855 to Lero - the Irish Software Engineering Research Centre (www.lero.ie). This research is also supported by the Science Foundation Ireland (Grant 07/CE/I1142) as part of the Centre for Next Generation Localisation (CNGL) at the University of Limerick.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Gizaw, S., Buckley, J., Beecham, S. (2016). Empirically Derived Recommendations for Personalised Text-Based Technical Support. In: Clarke, P., O'Connor, R., Rout, T., Dorling, A. (eds) Software Process Improvement and Capability Determination. SPICE 2016. Communications in Computer and Information Science, vol 609. Springer, Cham. https://doi.org/10.1007/978-3-319-38980-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-38980-6_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-38979-0
Online ISBN: 978-3-319-38980-6
eBook Packages: Computer ScienceComputer Science (R0)