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Customer Experience Analytics: Dynamic Customer-Centric Model

  • Mohamed ZakiEmail author
  • Andy Neely
Chapter
Part of the Service Science: Research and Innovations in the Service Economy book series (SSRI)

Abstract

Creating a strong customer experience is a strategic priority for organizations. Companies are leveraging new technologies such as mobile applications, social media platforms, virtual reality, drones and the Internet of Things to provide smart services and enable a seamless customer experience. The complexity of using these technologies within an organization’s myriad touchpoints has led to a data explosion across touchpoints in the entire customer journey (Lemon and Verhoef, J Market 80:1–62, 2016). Most of this customer data is unstructured textual data, which is generated at several touchpoints in the customer journey (McColl-Kennedy et al., J Serv Market 29:430–435, 2015). Text-mining techniques relating to traditional sentiment have focused on developing more accurate models but failed to obtain managerial insights by adopting these methods (Fenn and LeHong 2012).

Thus, firms require new data-driven methods that could highlight what really matters in driving customer satisfaction and delivering actionable insights (Lemon, GfK MIR 8:44–49, 2016; Hartmann et al., Int J Oper Prod Manag 36:1382–1406, 2016). In this chapter, first, we propose systematic multi-methods using a text-mining approach to capture and analyze customers’ data. This is done to enable firms to identify critical pain points from real-time data and provide deeper insights into critical touchpoints in order to reduce friction and improve the customer experience. Second, our approach enables early recognition of nuances in customer sentiment and demonstrates a novel method for analyzing textual data from CRM and social media data. This will allow an organization to monitor the customer experience while cross-referencing internal and external data sources. Third, extracting employee evaluations and the customer–buyer relationship will be demonstrated in an approach that can be used on ‘big data’, building on text-mining methods relating to the customer experience. Finally, we believe this new approach will enable firms to create rich, dynamic, customer-centric models that can provide a deeper understanding of customer behavior, including subsequent customer responses to organizational attempts to improve the customer experience.

Keywords

Customer experience Text mining CRM Data analytics Customer feedback Customer journey Touchpoints Marketing metrics Employee feedback 

References

  1. Addis, M. & Holbrook, M. B. (2001). ‘On the conceptual link between mass customisation and experiential consumption: An explosion of subjectivity’, Journal of Consumer Behaviour, Volume 1, Number 1, 1 June 2001, pp. 50–66(17).Google Scholar
  2. Aksoy, L. (2013). ‘How do you measure what you can’t define?’, Journal of Service Management, 24(4), 356–81.CrossRefGoogle Scholar
  3. Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). ‘The social influence of brand community: Evidence from European car clubs’, Journal of Marketing, Vol. 69, No. 3, pp. 19–34.CrossRefGoogle Scholar
  4. Ang, L. (2011). ‘Community relationship management and social media’, Journal of Database Marketing & Customer Strategy Management, 18(1), 31–38.  https://doi.org/10.1057/dbm.2011.3CrossRefGoogle Scholar
  5. Archer-Brown, C., Piercy, N., & Joinson, A. (2015). Sorting the Wheat from the Chat: Influence in Social Networks the Sustainable Global Marketplace (pp. 375–379): Springer.Google Scholar
  6. Berger, Paul and Nada I. Nasr (1998), “Customer Lifetime Value: Marketing Models and Applications,” Journal of Interactive Marketing, 12 (Winter), 17–30CrossRefGoogle Scholar
  7. Berry, L. L., Carbone, L. P., & Haeckel, S. H. (2002). Managing the Total Customer Experience. MIT Sloan Management Review, 43(3), 85–89.Google Scholar
  8. Bolton, R. N., & Lemon, K. N. (1999). A dynamic model of customers' usage of services: Usage as an antecedent and consequence of satisfaction. Journal of Marketing Research, 36(2), 171–186.CrossRefGoogle Scholar
  9. Chapman, P., Clinton, J., Kerber, R., & Khabaza, T. (2000). ‘CRISP-DM 1.0 Step-by-step Data Mining Guide’, ftp://ftp.software.ibm.com/software/analytics/spss/support/Modeler/Documentation/14/UserManual/CRISP-DM.pdf (accessed 31 March 2012), [available at ftp://ftp.software.ibm].
  10. De Keyser, A., Lemon, K. N., Klaus, P., & Keiningham, T. L. (2015). ‘A Framework for Understanding and Managing the Customer Experience’, Marketing Science Institute. Retrieved from: http://www.msi.org/reports/a-framework-for-understanding-and-managingthe-customer-experience/.
  11. Dominic Barton and David Court, (2012), Making Advanced Analytics Work For You, Harvard Business Review, available at https://enterprisersproject.com/sites/default/files/Making%20Advanced%20Analytics%20Work%20For%20You.pdf
  12. Dwyer, F. R., Schurr, P. H., & Oh, S. (1987). ‘Developing Buyer-Seller Relationships’, Journal of Marketing, 51(2), 11–27.  https://doi.org/10.2307/1251126CrossRefGoogle Scholar
  13. Fenn, Jackie, & LeHong, Hung. (2012). Hype cycle for emerging technologies, 2011.Gartner, July.Google Scholar
  14. Erik Brynjolfsson, Yu Jeffrey Hu and Mohammad S. Rahman (2013), Competing in the Age of Omnichannel Retailing, MIT Sloan Review, available at https://sloanreview.mit.edu/article/competing-in-the-age-ofomnichannel-retailing/
  15. Forlizzi, J. & Ford, S. (2000). ‘The Building Blocks of Experience: An Early Framework for Interaction Designers.’ In Proceedings of the 3rd Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques (pp. 419–423). New York, NY, USA: ACM.  https://doi.org/10.1145/347642.347800.CrossRefGoogle Scholar
  16. Gentile, C., Politecnico Milano, Noci, G., Politecnico Milano (2007). ‘How to Sustain the Customer Experience: An Overview of Experience Components that Co-create Value With the Customer’, 25(5), 395–410.Google Scholar
  17. Gouthier, Matthias and Stefan Schmid (2003), Customers and Customer Relationships in Service Firms: The Perspective of the Resource-Based View Marketing Theory, Vol 3, Issue 1, pp. 119–143Google Scholar
  18. Haenlein, M. (2013). ‘Social interactions in customer churn decisions: The impact of’, International Journal of Research in Marketing, 30(3), 236–248.CrossRefGoogle Scholar
  19. Hartmann, P. M., Zaki, M., Feldmann, N., & Neely, A. (2016). ‘Capturing value from big data – a taxonomy of data-driven business models used by start-up firms’, International Journal of Operations & Production Management, 2020.Google Scholar
  20. Heller Baird, C. & Parasnis, G. (2011). ‘From social media to social customer relationship management’, Strategy & Leadership, 39(5), 30–37.CrossRefGoogle Scholar
  21. Homburg, C., Jozić, D., & Kuehnl, C. (2015). ‘Customer experience management: toward implementing an evolving marketing concept’, Journal of the Academy of Marketing Science, 1–25.Google Scholar
  22. Hopmann, Jörg and Anke Thede, (2016) Applicability of Customer Churn Forecasts in a Non-Contractual Setting, Journal of Service Research, 9 issue: 2, page(s): 95–112.Google Scholar
  23. Wyllie, Jessica, Benjamin Lucas, Jamie Carlson, Brent Kitchens, Ben Kozary, and Mohamed Zaki (2016), “An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media,” Plos One, 11 (10), e0163914.CrossRefGoogle Scholar
  24. Kumar, V., & Reinartz, W. J. (2006) Customer relationship management: a database approach, Business & Economics, WileyGoogle Scholar
  25. Kunz, W., Aksoy, L., Hughes Hall, Bart, Y., & Heinonen, K., Relationship Marketing (2017). ‘Customer Engagement in a Big Data World’, Journal of Service Marketing (617), 1–39.Google Scholar
  26. LaSalle, D. & Britton, T. A. (2003). Priceless: Turning Ordinary Products into Extraordinary Experiences. Boston, MA, Harvard Business School Press.Google Scholar
  27. Leeflang, Peter S.H., Peter C. Verhoef a,⇑, Peter Dahlström c, Tjark Freundt (2015), Challenges and solutions for marketing in a digital era, European Management Journal 32 (2014) 1–12Google Scholar
  28. Lemon, K. N. (2016). ‘The Art of Creating Attractive Consumer Experiences at the Right Time: Skills Marketers Will Need to Survive and Thrive’, 44–49.Google Scholar
  29. Lemon, K. N. & Verhoef, P. C. (2016). ‘Understanding Customer Experience and the Customer Journey’, Journal of Marketing, (JM-MSI Special Issue), 1–62.Google Scholar
  30. Libai,Barak, Ruth Bolton, Marnix S. Bügel, Ko de Ruyter, Oliver Götz, Hans Risselada, and Andrew T. Stephen, (2010) Customer-to-Customer Interactions: Broadening the Scope of Word of Mouth Research, Journal of Service Research 13(3) 267–282.CrossRefGoogle Scholar
  31. Lipkin, M. (2016). ‘Customer experience formation in today’s service landscape’, Journal of Service Management, 27(5), 678–703.CrossRefGoogle Scholar
  32. Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., & Zhang, M. (2013). ‘Managing Customer Relationships in the Social Media Era: Introducing the Social CRM House’, Journal of Interactive Marketing, 27(4), 270–80.CrossRefGoogle Scholar
  33. McColl-Kennedy, J. R., Vargo, S. L. Dagger, T. S., Sweeney, J. C., & van Kasteren, Y. (2012). ‘Health Care Customer Value Cocreation Practice Styles’, Journal of Service Research, 15(4), 370–389.CrossRefGoogle Scholar
  34. McColl-Kennedy, J. R., Gustafsson, A., Jaakkola, E., Klaus, P., Radnor, Z., Perks, H., & Friman, M. (2015). ‘Fresh Perspectives on Customer Experience’, Journal of Services Marketing, 29(9), 430–435.CrossRefGoogle Scholar
  35. Mediapost, 2010, Poor Customer Service Costs Companies $83 Billion Annually, available at https://www.mediapost.com/publications/article/122502/poor-customer-service-costs-companies-83-billion.html
  36. Meyer, Christopher and Schwager, Andre 2007, Harvar Business Review, available at, https://hbr.org/2007/02/understanding-customer-experience
  37. Morgan, N. A. & Rego, L. L. (2006). ‘The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance’, Marketing Science, 25(5), 426–39.CrossRefGoogle Scholar
  38. MSI (2010). Marketing Science Institute 2010-2012 Research Priorities. Retrieved from: http://image.sciencenet.cn/olddata/kexue.com.cn/upload/blog/file/2010/9/201091515178616316.pdf
  39. MSI (2016). ‘Marketing Science Institute – Research Priorities 2008-2010’, Marketing Science Institute, [available at http://www.msi.org/uploads/articles/MSI_RP16-18.pdf].
  40. Murdough, C. (2009). ‘Social Media Measurement’, Journal of Interactive Advertising, 10(1), 94–99.  https://doi.org/10.1080/15252019.2009.10722165CrossRefGoogle Scholar
  41. Neslin, Scott A., Dhruv Grewal, Robert Leghorn, Venkatesh Shankar, Marije L. Teerling, Jacquelyn S. Thomas, and Peter C. Verhoef, Challenges and Opportunities in Multichannel Customer Management, Journal of Service Research, Vol 9, Issue 2, pp. 95–112, 2006CrossRefGoogle Scholar
  42. Ordenes, F. V., Theodoulidis, B., Burton, J., Gruber, T., & Zaki, M. (2014). ‘Analysing Customer Experience Feedback Using Text Mining: A Linguistics-Based Approach’, Journal of Service Research, 17(3), 278–295.  https://doi.org/10.1177/1094670514524625.CrossRefGoogle Scholar
  43. Ostrom, A. L., Parasuraman, A., Bowen, D. E., Patrício, L., & Voss, C. A. (2015). ‘Service Research Priorities in a Rapidly Changing Context’, Journal of Service Research, 18(2), 127–59.CrossRefGoogle Scholar
  44. Pang, B. & Lee, L. (2008). ‘Opinion Mining and Sentiment Analysis’, Foundations and Trends® in Information Retrieval, 2(1–2), 1–135.  https://doi.org/10.1561/1500000001.CrossRefGoogle Scholar
  45. Paul, M. J. & Dredze, M. (2014). ‘Discovering health topics in social media using topic models’, PLoS One, 9(8), e103408.  https://doi.org/10.1371/journal.pone.0103408.CrossRefGoogle Scholar
  46. Payne, Adrian, Pennie Frow (2005) A Strategic Framework for Customer Relationship Management. Journal of Marketing: October 2005, Vol. 69, No. 4, pp. 167–176.CrossRefGoogle Scholar
  47. Payne, A. F., Storbacka, K., & Frow, P. (2008). ‘Managing the co-creation of value’, Journal of the Academy of Marketing Science, 36(1), 83–96.  https://doi.org/10.1007/s11747-007-0070-0.CrossRefGoogle Scholar
  48. Reinartz, Werner, Manfred krafft, and Wayne D. Hoyer, Journal of Marketing Research Vol. XLI (August 2004), 293–305Google Scholar
  49. Ribarsky, W., Wang, D. X., & Dou, W. (2014). ‘Social media analytics for competitive advantage’, Computers & Graphics, 38, 328–331.CrossRefGoogle Scholar
  50. Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004). ‘Return on Marketing’, Using Customer Equity to Focus Marketing Strategy, 68 (1), 109–27.Google Scholar
  51. Schulze, Christian, Bernd Skiera, & Thorsten Wiesel, (2012), Linking Customer and Finanical Metrics to Shareholder Value: The Leverge Effect in customer-based valuation, Journal of Marketing, Volume 76 (March 2012), 17–32CrossRefGoogle Scholar
  52. Schmitt, B. H. (1999). Experiential Marketing: How to Get Customers to SENSE, FEEL, THINK, ACT and RELATE to Your Company and Brands. New York, The Free Press, p. 37.Google Scholar
  53. Singh, S. N., Hillmer, S., & Wang, Z. (2011). ‘Efficient Methods for Sampling Responses from Large-Scale Qualitative Data’, Marketing Science, 30(3), 532–549.CrossRefGoogle Scholar
  54. Smith, S. & Wheeler, J. (2002). Managing the Customer Experience. Financial Times Prentice Hall.Google Scholar
  55. Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. (2011). ‘Lexicon-based Methods for Sentiment Analysis’, Computational Linguistics, 37(2), 267–307.CrossRefGoogle Scholar
  56. Tirunillai, S. & Tellis, G. J. (2014). ‘Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation’, Journal of Marketing Research, 24–37.Google Scholar
  57. Trainora, K. J., Andzulisb, J., Rappb, A., & Agnihotric, R. (2014). ‘Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM’, Journal of Business Research, 67(6), 1201–1208.CrossRefGoogle Scholar
  58. Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). ‘Customer Experience Creation: Determinants, Dynamics and Management Strategies’, 85 (2007), 31–41.CrossRefGoogle Scholar
  59. Verhoef, Peter C., Edwin Kooge, and Natasha Walk (2016), Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. New York: Routledge.CrossRefGoogle Scholar
  60. Verhoef, P. C., Reinartz, W. J., & Krafft, M. (2010), ‘Customer engagement as a new perspective in customer management’, Journal of Service Research, Vol. 13, No. 3, pp. 247–52.CrossRefGoogle Scholar
  61. Woodcock, N., Green, A., & Starkey, M. (2011). ‘Social CRM as a business strategy’, Journal of Database Marketing & Customer Strategy Management, 18(1), 50–64.  https://doi.org/10.1057/dbm.2011.CrossRefGoogle Scholar
  62. Wübben, Markus & Florian v. Wangenheim, Instant Customer Base Analysis: Managerial Heuristics Often “Get It Right”, 2008, Journal of Marketing, 82 Vol. 72 (May 2008), 82–93.CrossRefGoogle Scholar
  63. Zeng, D., Chen, H., Lusch, R., & Li, S.-H. (2010). ‘Social media analytics and intelligence’, Intelligent Systems, 25(6), 13–16.  https://doi.org/10.1109/MIS.2010.151.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Engineering, Institute for ManufacturingUniversity of CambridgeCambridgeUK
  2. 2.Department of EngineeringUniversity of CambridgeCambridgeUK

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