Gaining Customer Experience Insights That Matter

[We’re pleased to welcome authors Janet R. McColl-Kennedy the University of Queensland Business School, Mohamed Zaki of the University of Cambridge, Katherine N. Lemon of the Carroll School of Management, Florian Urmetzer of the University of Cambridge, and Andy Neely of the University of Cambridge. They recently published an article in Journal of Service Research entitled “Gaining Customer Experience Insights That Matter,” which is currently free to read for a limited time. Below, they reflect on the motivation and impact of this research:]

What motivated you to pursue this research?

Customer experience is central to marketing. Providing a meaningful customer experience is viewed as essential to achieving competitive advantage and satisfied customers.
Customer experience management is listed in the top ten priorities of CEOs around the globe.
Organizations that carefully manage the customer experience reap rewards such as increased customer satisfaction, revenue growth, increased customer loyalty and greater employee satisfaction.

But to date knowing what to measure and how to gain rich insights that matter through multiple data sources, especially what to do with open-ended feedback has not been clear. Often open-ended feedback that firms receive is ignored, or simply categorized broadly as a complaint or a compliment.
We show that this rich feedback can be used to identify previously unrecognized, critical touchpoints in the customer experience and to take specific actions to strengthen the customer experience, thereby enhancing revenue growth, customer loyalty and employee and customer satisfaction.

In what ways is your research innovative, and how do you think it will impact the field?

This is the first empirical study of customer experience.
Large amounts of data, including textual data such as verbatim comments from customers, are now generated at many touchpoints in the customer journey. Text mining is well suited to extract customer insights from unstructured comments and customer satisfaction data. However, text mining is not yet mainstream in marketing. Text mining and other emerging technologies offer potentially better ways to measure and manage customer experience. In our model, we connect qualitative data and quantitative data with a text analytics approach. We show that customer experience analytics that apply big data techniques to the customer experience can offer significant insights that matter.

We identify seven root causes for the complex B2B service. Each of these represent opportunities for improving the CX.
Our model is also able to uncover customers who are at risk of leaving the firm, even customers who give high satisfaction scores (or NPS scores). Customers with high satisfaction scores would be seen by the firm as “satisfied”, or those with high NPS scores would be deemed “very likely to recommend”, and therefore not identified by the firm as requiring attention; yet we find that these customers are clearly voicing their concerns in the comments, and may be at higher risk of churning than traditional measures may suggest.

We uncover an entire “hidden” segment of supposedly highly satisfied customers who voice significant concerns. 42% of customers who give scores of 9.5 and above (out of 10) actually complain, as do many who give scores between 7 and 9.4 (44%). Complaints made by customers who gave satisfaction scores of 7 or greater were often ignored, despite these customers being worth over $250,000 on average and accounting for a significant portion of sales. Sales figures shows that when these customers’ concerns were not addressed sales went down significantly. For instance, one such “satisfied” customer reduced its purchases from over $200,000 to less than $2000. The key insight? Ignoring the small details that can be identified through the authors’ text analytics model can mean big losses for firms.

Our approach enables firms to link customer-centric CX elements from the conceptual framework (identified as potential pain points) to specific firm functions and jobs (identified as root causes) to take specific actions to strengthen the customer experience. We provide a step-by-step guide for implementing the approach highlighting what really matters to customers and what actions are needed by managers

What advice would you give to new scholars and incoming researchers in this particular field of study?

This is a very exciting time to be investigating customer experience with new data mining tools available. Learn new tools and apply them to make important contributions to theory and practice. Collaborating with a company that is interested in improving its performance through new approaches can yield innovative insights – both for the firm and for scholarship.

Professor Janet R. McColl-Kennedy, PhD, FAMI, FANZMAC, CPM
Professor of Marketing I UQ Business School The University of Queensland l Brisbane QLD 4072 l AUSTRALIA
P: +617 3346 8178 | E:
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