Hessey, Sue and Venters, Will
(2016)
Sensing distress – towards a blended method for detecting and responding to problematic customer experience events.
In:
HCI in Business, Government, and Organizations: eCommerce and Innovation.
Lecture Notes in Computer Science (9751).
Springer International (Firm), Switzerland, pp. 395-405.
ISBN 978-3-319-39395-7
Abstract
Excellent Customer Experience (CE) is a strategic priority for many large service organisations in a competitive marketplace. CE should be seamless, and in most cases it is, with customers ordering, paying for and receiving services that align with their expectations. However, in rare cases, an exceptional process event leads to service delivery delay or failure, and both the customer and organ-isation end up in complex recovery situations as a result. Unless this recovery is handled effectively inefficiency, avoidable costs and brand damage can result. So how can organisations sense when these problems are occurring and how can they respond to avoid these negative consequences? Our paper proposes a blended methodology where process mining and qualitative user research com-bine to give a holistic picture of customer experience issues, derived from a par-ticular customer case study. We propose a theoretical model for detecting and responding to customer issues, and discuss the challenges and opportunities of such a model when applied in practice in large service organisations.
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