Skip to main content
SpringerLink
Log in

Customer Experience Analytics: Dynamic Customer-Centric Model

  • Chapter
  • First Online:
Handbook of Service Science, Volume II

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • 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 

  • Aksoy, L. (2013). ‘How do you measure what you can’t define?’, Journal of Service Management, 24(4), 356–81.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.2011.3

    Article  Google Scholar 

  • 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 

  • Berger, Paul and Nada I. Nasr (1998), “Customer Lifetime Value: Marketing Models and Applications,” Journal of Interactive Marketing, 12 (Winter), 17–30

    Article  Google Scholar 

  • 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 

  • 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.

    Google Scholar 

  • 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].

  • 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/.

  • 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

  • Dwyer, F. R., Schurr, P. H., & Oh, S. (1987). ‘Developing Buyer-Seller Relationships’, Journal of Marketing, 51(2), 11–27. https://doi.org/10.2307/1251126

    Article  Google Scholar 

  • Fenn, Jackie, & LeHong, Hung. (2012). Hype cycle for emerging technologies, 2011.Gartner, July.

    Google Scholar 

  • 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/

  • 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.

    Chapter  Google Scholar 

  • 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 

  • 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. 119–143

    Google Scholar 

  • Haenlein, M. (2013). ‘Social interactions in customer churn decisions: The impact of’, International Journal of Research in Marketing, 30(3), 236–248.

    Article  Google Scholar 

  • 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 

  • Heller Baird, C. & Parasnis, G. (2011). ‘From social media to social customer relationship management’, Strategy & Leadership, 39(5), 30–37.

    Article  Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • Kumar, V., & Reinartz, W. J. (2006) Customer relationship management: a database approach, Business & Economics, Wiley

    Google Scholar 

  • 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 

  • LaSalle, D. & Britton, T. A. (2003). Priceless: Turning Ordinary Products into Extraordinary Experiences. Boston, MA, Harvard Business School Press.

    Google Scholar 

  • 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) 1–12

    Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • Lipkin, M. (2016). ‘Customer experience formation in today’s service landscape’, Journal of Service Management, 27(5), 678–703.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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

  • Meyer, Christopher and Schwager, Andre 2007, Harvar Business Review, available at, https://hbr.org/2007/02/understanding-customer-experience

  • 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.

    Article  Google Scholar 

  • 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

  • MSI (2016). ‘Marketing Science Institute – Research Priorities 2008-2010’, Marketing Science Institute, [available at http://www.msi.org/uploads/articles/MSI_RP16-18.pdf].

  • Murdough, C. (2009). ‘Social Media Measurement’, Journal of Interactive Advertising, 10(1), 94–99. https://doi.org/10.1080/15252019.2009.10722165

    Article  Google Scholar 

  • 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, 2006

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Payne, Adrian, Pennie Frow (2005) A Strategic Framework for Customer Relationship Management. Journal of Marketing: October 2005, Vol. 69, No. 4, pp. 167–176.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Reinartz, Werner, Manfred krafft, and Wayne D. Hoyer, Journal of Marketing Research Vol. XLI (August 2004), 293–305

    Google Scholar 

  • Ribarsky, W., Wang, D. X., & Dou, W. (2014). ‘Social media analytics for competitive advantage’, Computers & Graphics, 38, 328–331.

    Article  Google Scholar 

  • 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 

  • 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), 17–32

    Article  Google Scholar 

  • 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 

  • Singh, S. N., Hillmer, S., & Wang, Z. (2011). ‘Efficient Methods for Sampling Responses from Large-Scale Qualitative Data’, Marketing Science, 30(3), 532–549.

    Article  Google Scholar 

  • Smith, S. & Wheeler, J. (2002). Managing the Customer Experience. Financial Times Prentice Hall.

    Google Scholar 

  • Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. (2011). ‘Lexicon-based Methods for Sentiment Analysis’, Computational Linguistics, 37(2), 267–307.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Verhoef, Peter C., Edwin Kooge, and Natasha Walk (2016), Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. New York: Routledge.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Engineering, Institute for Manufacturing, University of Cambridge, Cambridge, UK

    Mohamed Zaki

  2. Department of Engineering, University of Cambridge, Cambridge, UK

    Andy Neely

Authors
  1. Mohamed Zaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andy Neely
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohamed Zaki .

Editor information

Editors and Affiliations

  1. University of California, Merced, Merced, CA, USA

    Paul P. Maglio

  2. IBM Research—Almaden, San Jose, CA, USA

    Cheryl A. Kieliszewski

  3. IBM Cognitive Opentech, Almaden, San Jose, CA, USA

    James C. Spohrer

  4. University of Toronto, Toronto, ON, Canada

    Kelly Lyons

  5. INESCTEC and Faculty of Engineering, University of Porto, Porto, Portugal

    Lia Patrício

  6. Graduate School of Management, Nagoya University of Commerce and Business Business School, Nagoya, Aichi, Japan

    Yuriko Sawatani

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zaki, M., Neely, A. (2019). Customer Experience Analytics: Dynamic Customer-Centric Model. In: Maglio, P.P., Kieliszewski, C.A., Spohrer, J.C., Lyons, K., Patrício, L., Sawatani, Y. (eds) Handbook of Service Science, Volume II. Service Science: Research and Innovations in the Service Economy. Springer, Cham. https://doi.org/10.1007/978-3-319-98512-1_10

Download citation

Publish with us

Policies and ethics

Search

Navigation