Skip to main content
SpringerLink
Log in

Key Aspects of Customer Intelligence in the Era of Massive Data

  • Conference paper
  • First Online:
Intelligent Information and Database Systems (ACIIDS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12672))

Included in the following conference series:

Abstract

The era of massive data has changed the manner that customer intelligence is examined and applied to intelligent information systems. Customer intelligence is the ability to acquire knowledge and skills from massive data through customer analytics then apply them to the process of creating, communicating, delivering, and co-creating to offer value. Considering the vast nature of this research stream, the paper sheds light on investigating key aspects of customer intelligence with relevance to marketing solutions. The objective of the study is to conduct a critical literature review and develop a theoretical framework on customer intelligence in the context of massive data to support marketing decisions. The results of the paper indicate various applications of customer intelligence through the lens of the marketing mix. Accordingly, customer intelligence is applied to the aspects of the extended marketing mix (7P’s), including Product/Service, Price, Promotion, Place, People, Process, and Physical evidence. The paper makes major contributions to the application of customer intelligence for intelligent information systems in supporting marketing decisions.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

  1. Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage. 35(2), 137–144 (2015)

    Article  Google Scholar 

  2. Jagadish, H.V.: Big data and science: Myths and reality. Big Data Res. 2(2), 49–52 (2015)

    Article  MathSciNet  Google Scholar 

  3. Zerbino, P., Aloini, D., Dulmin, R., Mininno, V.: Big data-enabled customer relationship management: a holistic approach. Inf. Process. Manage. 54(5), 818–846 (2018)

    Article  Google Scholar 

  4. Anshari, M., Almunawar, M.N., Lim, S.A., Al-Mudimigh, A.: Customer relationship management and big data enabled: personalization & customization of services. Appl. Comput. Inf. 15(2), 94–101 (2019)

    Google Scholar 

  5. Yan, Y., Huang, C., Wang, Q., Hu, B.: Data mining of customer choice behavior in internet of things within relationship network. Int. J. Inf. Manage. 50, 566–574 (2020)

    Article  Google Scholar 

  6. Sivarajah, U., Kamal, M.M., Irani, Z., Weerakkody, V.: Critical analysis of big data challenges and analytical methods. J. Bus. Res. 70, 263–286 (2017). https://doi.org/10.1016/j.jbusres.2016.08.001

    Article  Google Scholar 

  7. France, S.L., Ghose, S.: Marketing analytics: methods, practice, implementation, and links to other fields. Exp. Syst. Appl. 119, 456–475 (2018). https://doi.org/10.1016/j.eswa.2018.11.002

    Article  Google Scholar 

  8. Dam, N.A.K., Le Dinh, T., Menvielle, W.: A service-based model for customer intelligence in the age of big data (2020)

    Google Scholar 

  9. Holmlund, M., et al.: Customer experience management in the age of big data analytics: a strategic framework. J. Bus. Res. (2020)

    Google Scholar 

  10. Tabrizi, B., Lam, E., Girard, K., Irvin, V.: Digital transformation is not about technology. Harvard Bus. Rev. (2019)

    Google Scholar 

  11. Davenport, T.H., Spanyi, A.: Digital transformation should start with customers. MIT Sloan Manage. Rev. (2019)

    Google Scholar 

  12. Lau, R.Y.K., Zhao, J.L., Chen, G., Guo, X.: Big data commerce. Inf. Manage. 53(8), 929–933 (2016). https://doi.org/10.1016/j.im.2016.07.008

    Article  Google Scholar 

  13. Stebbins, R.A.: Exploratory Research in the Social Sciences, vol. 48. Sage (2001)

    Google Scholar 

  14. Webster, J., Watson, R.T.: Analyzing the past to prepare for the future: writing a literature review. MIS Q. 26(2), xiii–xxiii (2002)

    Google Scholar 

  15. Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)

    Article  Google Scholar 

  16. Barney, J.: Firm resources and sustained competitive advantage. J. Manage. 17(1), 99–120 (1991)

    Google Scholar 

  17. Chen, I.J., Popovich, K.: Understanding customer relationship management (CRM) People, process and technology. Bus Process Manage. J. 9(5), 672–688 (2003)

    Article  Google Scholar 

  18. Rygielski, C., Wang, J.-C., Yen, D.C.: Data mining techniques for customer relationship management. Technol. Soc. 24(4), 483–502 (2002)

    Article  Google Scholar 

  19. Keskin, H.: Market orientation, learning orientation, and innovation capabilities in SMEs. Eur. J. Innov. Manage. 9(4), 396–417 (2006)

    Article  Google Scholar 

  20. Lewrick, M., Omar, M., Williams Jr., R.L.: Market orientation and innovators’ success: an exploration of the influence of customer and competitor orientation. J. Technol. Manage. Innov. 6(3), 48–62 (2011)

    Article  Google Scholar 

  21. Guarda, T., Santos, M.F., Pinto, F., Silva, C., Lourenço, J.: A conceptual framework for marketing intelligence. Int. J. e-Educ. e-Bus. e-Manage. e-Learn. 2(6), 455 (2012)

    Google Scholar 

  22. Singh, P., Verma, G.: Mystery shopping: measurement tool for customer intelligence management. IOSR J. Bus. Manage. Sci. 16(6), 101–104 (2014)

    Article  Google Scholar 

  23. Samuel, A.: Data is the next big thing in content marketing. Harvard Bus. Rev. (2015)

    Google Scholar 

  24. Gobble, M.M.: From customer intelligence to customer intimacy. Res. Technol. Manage. 58(6), 56–61 (2015)

    Google Scholar 

  25. Rakthin, S., Calantone, R.J., Wang, J.F.: Managing market intelligence: the comparative role of absorptive capacity and market orientation. J. Bus. Res. 69(12), 5569–5577 (2016)

    Article  Google Scholar 

  26. Stone, M., et al.: How platforms are transforming customer information management. Bottom Line 30(3) (2017)

    Google Scholar 

  27. López-Robles, J.-R., Otegi-Olaso, J.-R., Gómez, I.P., Cobo, M.-J.: 30 years of intelligence models in management and business: a bibliometric review. Int. J. Inf. Manage. 48, 22–38 (2019)

    Article  Google Scholar 

  28. Oxford Dictionary: Intelligence. In: Oxford Dictionary (2014)

    Google Scholar 

  29. Rownd, M., Heath, C.: The American marketing association releases new definition for marketing. AMA, Chicago, Il (2008)

    Google Scholar 

  30. Association, A.M.: Customer definition. In: AMA Dictionary. (2015)

    Google Scholar 

  31. Erevelles, S., Fukawa, N., Swayne, L.: Big data consumer analytics and the transformation of marketing. J. Bus. Res. 69(2), 897–904 (2016)

    Article  Google Scholar 

  32. Baesens, B., Bapna, R., Marsden, J.R., Vanthienen, J., Zhao, J.L.: Transformational issues of big data and analytics in networked business. MIS Q. 40(4) (2016)

    Google Scholar 

  33. LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S., Kruschwitz, N.: Big data, analytics and the path from insights to value. MIT Sloan Manage. Rev. 52(2), 21 (2011)

    Google Scholar 

  34. Fan, S., Lau, R.Y.K., Zhao, J.L.: Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Res. 2(1), 28–32 (2015). https://doi.org/10.1016/j.bdr.2015.02.006

    Article  Google Scholar 

  35. Frow, P., Nenonen, S., Payne, A., Storbacka, K.: Managing co-creation design: a strategic approach to innovation. Br. J. Manage. 26(3), 463–483 (2015)

    Article  Google Scholar 

  36. Verleye, K.: The co-creation experience from the customer perspective: its measurement and determinants. J. Serv. Manage. 26(2), 321–342 (2015)

    Article  Google Scholar 

  37. Rao, T.R., Mitra, P., Bhatt, R., Goswami, A.: The big data system, components, tools, and technologies: a survey. Knowl. Inf. Syst. Manage. 1–81 (2018)

    Google Scholar 

  38. Yohn, D.L.: 6 ways to build a customer-centric culture. Havard Bus. Rev. (2018)

    Google Scholar 

  39. Ramaswamy, V., Ozcan, K.: Digitalized interactive platforms: turning goods and services into retail co-creation experiences. NIM Mark. Intell. Rev. 11(1), 18–23 (2019)

    Google Scholar 

  40. Rawson, A., Duncan, E., Jones, C.: The truth about customer experience. Harvard Bus. Rev. (2013)

    Google Scholar 

  41. Amado, A., Cortez, P., Rita, P., Moro, S.: Research trends on big data in marketing: a text mining and topic modeling based literature analysis. Eur. Res. Manage. Bus. Econ. 24(1), 1–7 (2018). https://doi.org/10.1016/j.iedeen.2017.06.002

    Article  Google Scholar 

  42. McCarthy, E.J., Shapiro, S.J., Perreault, W.D.: Basic Marketing. Irwin-Dorsey (1979)

    Google Scholar 

  43. Burrell, L.: Co-creating the employee experience. Harvard Bus. Rev. (2018)

    Google Scholar 

  44. Oertzen, A.-S., Odekerken-Schröder, G., Brax, S.A., Mager, B.: Co-creating services—conceptual clarification, forms and outcomes. J. Serv. Manage. 29(4), 641–679 (2018)

    Article  Google Scholar 

  45. Rashid, Y., Waseem, A., Akbar, A.A., Azam, F.: Value co-creation and social media. Eur. Bus. Rev. (2019)

    Google Scholar 

  46. Ngai, E.W.T., Xiu, L., Chau, D.C.K.: Application of data mining techniques in customer relationship management: a literature review and classification. Expert Syst. Appl. 36(2), 2592–2602 (2009). https://doi.org/10.1016/j.eswa.2008.02.021

    Article  Google Scholar 

  47. Dam, N.A.K., Le Dinh, T.: A literature review of recommender systems for the cultural sector. In: Paper presented at the Proceedings of the 22nd International Conference on Enterprise Information, Czech Republic (2020)

    Google Scholar 

  48. Lemon, K.N., Verhoef, P.C.: Understanding customer experience throughout the customer journey. J. Mark. 80(6), 69–96 (2016)

    Article  Google Scholar 

  49. Dam, N.A.K., Le Dinh, T., Menvielle, W.: A systematic literature review of big data adoption in internationalization. J. Mark. Anal. 7(3), 182–195 (2019). https://doi.org/10.1057/s41270-019-00054-7

    Article  Google Scholar 

  50. Siggelkow, N., Terwiesch, C.: The age of continuous connection. Harvard Bus. Rev. (2019)

    Google Scholar 

  51. Maechler, N., Neher, K., Park, R.: From touchpoints to journeys: Seeing the world as customers do. Retrieved 18 Mar 2017 (2016)

    Google Scholar 

  52. Halvorsrud, R., Kvale, K., Følstad, A.: Improving service quality through customer journey analysis. J. Serv. Theor. Pract. (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Université du Québec à Trois-Rivières, Trois-Rivières, QC, G8Z 4M3, Canada

    Nguyen Anh Khoa Dam, Thang Le Dinh & William Menvielle

  2. The University of Danang, University of Science and Technology, Da Nang, Vietnam

    Nguyen Anh Khoa Dam

Authors
  1. Nguyen Anh Khoa Dam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thang Le Dinh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. William Menvielle
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nguyen Anh Khoa Dam .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Suphamit Chittayasothorn

  3. Nanyang Technological University, Singapore, Singapore

    Dusit Niyato

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dam, N.A.K., Le Dinh, T., Menvielle, W. (2021). Key Aspects of Customer Intelligence in the Era of Massive Data. In: Nguyen, N.T., Chittayasothorn, S., Niyato, D., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2021. Lecture Notes in Computer Science(), vol 12672. Springer, Cham. https://doi.org/10.1007/978-3-030-73280-6_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-73280-6_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73279-0

  • Online ISBN: 978-3-030-73280-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation