Main Article Content

Abstract

The dynamic business environment, the fusion of Information Technology (IT) innovation with marketing management strategies has emerged as a crucial element for success amidst heightened competition. As markets evolve and consumer behaviors shift, enterprises are compelled to adapt swiftly, employing innovative tools and methodologies to gain insights and maintain relevance. Within this context, the integration of Big Data analytics emerges as a transformative catalyst, offering unprecedented opportunities to comprehend consumer preferences and optimize marketing endeavors. The convergence of IT and marketing management signifies a paradigm shift in how businesses conceive and execute their strategies. Historically, marketing decisions relied heavily on intuition, market research, and limited data samples. However, the digital revolution has ushered in an era characterized by the generation and collection of vast amounts of data at an unprecedented pace. This proliferation of data presents both challenges and opportunities for marketers. While the sheer volume and complexity of data can be overwhelming, harnessing this reservoir of data can unlock invaluable insights into consumer behavior, preferences, and trends. The integration of Big Data into marketing management strategies has revolutionized consumer understanding and value creation. By leveraging vast amounts of consumer data, businesses can extract valuable insights to gain a competitive advantage and enhance consumer engagement. However, this integration also presents challenges, including concerns regarding data privacy and security. At the forefront of this data-driven revolution lies Big Data analytics—a multidisciplinary field utilizing advanced computational techniques to analyze large and diverse datasets. Unlike traditional analytics approaches, Big Data analytics excels in processing massive volumes of structured and unstructured data with agility and efficiency. By harnessing distributed computing, machine learning algorithms, and cloud infrastructure, organizations can extract actionable intelligence from previously unwieldy datasets. The integration of Big Data analytics into marketing management holds immense promise for unlocking new avenues of consumer understanding. By aggregating and analyzing disparate data sources, marketers can gain comprehensive insights into consumer preferences, behaviors, and sentiments, enabling more targeted and effective marketing strategies. Moreover, Big Data analytics empowers marketers to anticipate and respond to emerging trends and market shifts with unprecedented agility, ensuring a competitive edge in fast-paced industries. However, realizing the full potential of Big Data integration in marketing management requires more than technological prowess—it demands a strategic shift in organizational mindset and culture. Embracing a data-driven approach necessitates breaking down silos between departments, fostering cross-functional collaboration, and promoting a culture of experimentation and innovation. Additionally, it requires a commitment to ethical data practices to safeguard consumer privacy and data security throughout the data lifecycle.

Keywords

Big Data Analytics IT Innovation Marketing Management Strategies Consumer Understanding Data-Driven Approach

Article Details

How to Cite
Putra, A. H. P. K., Rivera, K. M. ., & Pramukti, A. (2023). Optimizing Marketing Management Strategies Through IT Innovation: Big Data Integration for Better Consumer Understanding. Golden Ratio of Mapping Idea and Literature Format, 3(1), 71–91. https://doi.org/10.52970/grmilf.v3i1.398

References

  1. A. Ertemel. (2015). Consumer insight as competitive advantage using big data and analytics.
  2. Alshura, M. S., Zabadi, A., & Abughazaleh, M. (2018). Big Data in Marketing Arena. Big Opportunity, Big Challenge, and Research Trends: An Integrated View. Management And Economics Review, 3(1), 75–84. https://doi.org/10.24818/MER%2F2018.06-06
  3. Anshari, M., Almunawar, M. N., Lim, S. A., & Al-Mudimigh, A. (2019). Customer relationship management and big data enabled: Personalization & customization of services. Applied Computing and Informatics, 15(2), 94–101. https://doi.org/10.1016/J.ACI.2018.05.004
  4. Bawack, R. E., Wamba, S. F., & Carillo, K. D. A. (2021). Exploring the role of personality, trust, and privacy in customer experience performance during voice shopping: Evidence from SEM and fuzzy set qualitative comparative analysis. International Journal of Information Management, 58, 102309. https://doi.org/10.1016/j.ijinfomgt.2021.102309
  5. Bheekharry, N. D., & Singh, U. G. (2019). Integrating Information Technology and Marketing for Better Customer Value. In Advances in Intelligent Systems and Computing (pp. 1–9). Springer Singapore. https://doi.org/10.1007/978-981-13-3338-5_1
  6. Big data use in marketing strategy. (2022). Strategic Direction, 39(1), 24–26. https://doi.org/10.1108/sd-11-2022-0137
  7. Blackburn, K., & Boris, K. (2020). Social Media Data Analytics – Using Big Data for Big Consumer Reach. SSRN Electronic Journal. http://dx.doi.org/10.13140/RG.2.2.26634.90565
  8. Brown, B., Chui, M., & Manyika, J. (2011). Are you ready for the era of ‘big data.’ McKinsey Quarterly, 4(1), 24–35.
  9. Bughin, J. (2017). Ten big lessons learned from big data analytics. Applied Marketing Analytics, 2(4), 286–295.
  10. Cavlak, N., & Cop, R. (2021). The Role of Big Data in Digital Marketing. In Advances in Marketing, Customer Relationship Management, and E-Services (pp. 16–33). IGI Global. http://dx.doi.org/10.4018/978-1-7998-8003-5.ch002
  11. Chen, C., Zhao, L., Bian, J., Xing, C., & Liu, T.-Y. (2019). Investment behaviors can tell what inside: Exploring stock intrinsic properties for stock trend prediction. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2376–2384. https://doi.org/10.1145/3292500.3330663
  12. Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904. https://doi.org/10.1016/J.JBUSRES.2015.07.001
  13. Figueiredo, F. atima, Gonçalves, M. J. e A. elico, & Teixeira, S. (2021). Information Technology Adoption on Digital Marketing: A Literature Review. Informatics, 8(4), 74. https://doi.org/10.3390/informatics8040074
  14. Grandhi, B., Patwa, N., & Saleem, K. (2020). Data-driven marketing for growth and profitability. EuroMed Journal of Business, 16(4), 381–398. https://doi.org/10.1108/EMJB-09-2018-0054
  15. Hofacker, C. F., Malthouse, E. C., & Sultan, F. (2016). Big Data and consumer behavior: Imminent opportunities. Journal of Consumer Marketing, 33(2), 89–97. https://doi.org/10.1108/JCM-04-2015-1399
  16. Holley, K., Sivakumar, G., & Kannan, K. (2014). Enrichment patterns for big data. 2014 IEEE International Congress on Big Data, 796–799. https://doi.org/10.1109/BigData.Congress.2014.127
  17. Jia, D. (2019). Research on the Integration of Marketing Management and Big Data Technology. In Advances in Intelligent Systems and Computing (pp. 633–639). Springer International Publishing. http://dx.doi.org/10.1007/978-3-030-15235-2_88
  18. Jim’ enez-Zarco, A. I., Rospigliosi, A., Mart’ inez-Ruiz, M. ia P., & Izquierdo-Yusta, A. (2017). Marketing 4.0. In Advances in Marketing, Customer Relationship Management, and E-Services (pp. 94–117). IGI Global. https://doi.org/10.4018/978-1-5225-2139-6.CH005
  19. Kauffman, R. J., Srivastava, J., & Vayghan, J. (2012). Business and data analytics: New innovations for the management of e-commerce. Electronic Commerce Research and Applications, 11(2), 85–88. https://doi.org/10.1016/j.elerap.2012.01.001
  20. Ketty Grishikashvili, S. Dibb, & M. Meadows. (2014). Investigation into Big Data Impact on Digital Marketing.
  21. Kitchens, B., Dobolyi, D., Li, J., & Abbasi, A. (2018). Advanced Customer Analytics: Strategic Value Through Integration of Relationship-Oriented Big Data. Journal of Management Information Systems, 35(2), 540–574. https://doi.org/10.1080/07421222.2018.1451957
  22. Lacarcel, F. J. S., Polanco-Diges, L., & Debasa, F. (2021). A Better Understanding of Big Data and Marketing Analytics. In Advances in Marketing, Customer Relationship Management, and E-Services (pp. 1–15). IGI Global. https://doi.org/10.4018/978-1-7998-8003-5.ch001
  23. Ling Miao. (2021). Influence of Big Data Technology on Enterprise Marketing Strategy.
  24. Mahdiraji, H. A., Kazimieras Zavadskas, E., Kazeminia, A., & Abbasi Kamardi, A. (2019). Marketing strategies evaluation based on big data analysis: A CLUSTERING-MCDM approach. Economic Research-Ekonomska Istraživanja, 32(1), 2882–2898. https://doi.org/10.1080/1331677x.2019.1658534
  25. Marr, B. (2015). Big Data: Using SMART big data, analytics and metrics to make better decisions and improve performance. John Wiley & Sons.
  26. Matz, S. C., & Netzer, O. (2017). Using Big Data as a window into consumers’ psychology. Current Opinion in Behavioral Sciences, 18, 7–12. https://doi.org/10.1016/j.cobeha.2017.05.009
  27. Miklosik, A., & Evans, N. (2020). Impact of Big Data and Machine Learning on Digital Transformation in Marketing: A Literature Review. IEEE Access, 8, 101284–101292. https://doi.org/10.1109/ACCESS.2020.2998754
  28. Nan, W., & Xiaochun, S. (2020). The Influence and Countermeasures of Enterprise Marketing Activities under the Big Data Background. Journal of Physics: Conference Series, 1684(1), 012016.
  29. Pantano, E., Giglio, S., & Dennis, C. (2020). Integrating Big Data Analytics Into Retail Services Marketing Management. In Handbook of Research on Innovations in Technology and Marketing for the Connected Consumer (pp. 205–222). IGI Global. https://doi.org/10.1088/1742-6596%2F1684%2F1%2F012016
  30. Salvador, A. B., & Ikeda, A. A. (2014). Big Data Usage in the Marketing Information System. Journal of Data Analysis and Information Processing, 02(03), 77–85. http://dx.doi.org/10.4236/jdaip.2014.23010
  31. Sayyad, S., Mohammed, A., Shaga, V., Kumar, A., & Vengatesan, K. (2019). Digital Marketing Framework Strategies Through Big Data. In Lecture Notes on Data Engineering and Communications Technologies (pp. 1065–1073). Springer International Publishing. https://doi.org/10.1007/978-3-030-24643-3_127
  32. Sestino, A. (2019). Business Development, Marketing Automation and Predictive Analysis: An Integration Perspective—An Overview Towards New Opportunities for Studying Consumer Behavior and Business Integration. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.3316759
  33. Tian, X., & Liu, L. (2016). Does big data mean big knowledge? Integration of big data analysis and conceptual model for social commerce research. Electronic Commerce Research, 17(1), 169–183. https://doi.org/10.1007/s10660-016-9242-7
  34. Van Auken, S. (2015a). From consumer panels to big data: An overview on marketing data development. Journal of Marketing Analytics, 3(1), 38–45. http://dx.doi.org/10.1057/jma.2015.2
  35. Wang, W. Y. C., & Wang, Y. (2020). Analytics in the era of big data: The digital transformations and value creation in industrial marketing. In Industrial Marketing Management (Vol. 86, pp. 12–15). Elsevier. https://doi.org/10.1016/j.indmarman.2020.01.005
  36. Wright, L. T., Robin, R., Stone, M., & Aravopoulou, D. E. (2019). Adoption of Big Data Technology for Innovation in B2B Marketing. Journal of Business-to-Business Marketing, 26(3–4), 281–293 http://dx.doi.org/10.1080/1051712X.2019.1611082 .
  37. Zhan, Y., Tan, K. H., Li, Y., & Tse, Y. K. (2016). Unlocking the power of big data in new product development. Annals of Operations Research, 270(1–2), 577–595. https://doi.org/10.1007/s10479-016-2379-x