Integrating Big Data Analytics Into Marketing Mix Development
Keywords:Marketing analytics, Big Data, Marketing Mix
In the era of digital disruption, the world has seen a tremendous increase in the amount of data being transmitted, and at a much faster pace than before. New data is created everyday via a variety of formats and a large amount of this is not being managed and analyzed. Big data has changed the way marketers are able to access consumers’ information, they are now able to do this extremely quickly and in real time. This is because consumers use digital devices which include built-in sensors that track and collect their behavioral information. This can lead to a more in-depth understanding of consumer insights and behaviors by analyzing the produced big data, and then converting it to actionable insights. There are 4 main methods of managing big data: descriptive, diagnostic, predictive and prescriptive analysis. According to a recent survey, it was revealed by those working in top management that marketing professionals lack the competency to manage big data effectively due to being unable to integrate it using mixed marketing strategies. Therefore, this article will present a potential solution to the integration of big data analytics using mixed marketing, namely: product, price, place and promotion. In addition, firms should also play a key role in building a data-driven, decision-based culture by providing education on the benefits of data-driven decision-making and enhancing competency in big data analytics. One potential issue, however, is that this would require support from various corporate departments, such as: marketing, IT, human resources and top management.
Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang. (2016). Bachelor of Science Program in Data Science and Business Analytics. Retrieved from http://www1.it.kmitl.ac.th/admissions/dsba/it59 [in Thai].
School of Information Technology, Institute of Social Technology, Suranaree University of Technology. (2018). Bachelor of Information Science Retrieved from http://soctech.sut.ac.th/it/webitsut2015/program_it_60.php?lang=th [in Thai].
Cao, G., & Tian, N. (2020). Enhancing Customer-Linking Marketing Capabilities Using Marketing Analytics. Journal of Business and Industrial Marketing. doi:10.1108/JBIM-09-2019-0407
Chatterjee, P. (2019). Teaching Digital Marketing Analytics for the Real World. Marketing Management Association Annual Conference Proceedings, 127-128.
Davenport, T. H., Harris, J. G., & Morison, R. (2010). Analytics at Work: Smarter Decisions, Better Results. Boston, Massachusetts: Harvard Business Press.
Dietrich, B. L., Plachy, E. C., & Norton, M. F. (2014). Analytics Across The Enterprise: How IBM Realizes Business Value from Big Data and Analytics. Crawfordsville, Indianna, United States of America: Pearson Education Inc.
Erl, T., Khattak, W., & Buhler, P. (2015). Big Data Fundamentals: Concepts, Drivers & Techniques. Indianna: Prentice Hall.
Feinleib, D. (2014). Big Data Bootcamp. [electronic resource]: What Managers Need to Know to Profit from the Big Data Revolution: Apress.
France, S. L., & Ghose, S. (2019). Marketing Analytics: Methods, Practice, Implementation, and Links to Other Fields. Expert Systems with Applications, 119, 456-475. doi:10.1016/j.eswa.2018.11.002
Hajli, N., Tajvidi, M., Gbadamosi, A., & Nadeem, W. (2020). Understanding Market Agility for New Product Success with Big Data Analytics. Industrial Marketing Management, 86, 135-143. doi:10.1016/j.indmarman.2019.09.010
Haywood, M. E., & Mishra, A. (2019). Building a Culture of Business Analytics: A Marketing Analytics Exercise. International Journal of Educational Management, 33(1), 86-97. doi:10.1108/IJEM-03-2018-0107
Hua, H. (2019). Mobile Marketing Management: Case Studies from Successful Practices. New York: Routledge/Productivity Press.
Hung, J. L., He, W., & Shen, J. (2020). Big Data Analytics for Supply Chain Relationship in Banking. Industrial Marketing Management, 86, 144-153. doi:10.1016/j.indmarman.2019.11.001
Jobsdb.com. (2019). Essential Skills in Your Resume to Apply for Marketing Jobs with Guaranteed Results. Retrieved from https://th.jobsdb.com/th-th/articles/%e0%
Kerin, R. A., & Hartley, S. W. (2020). Marketing The Core (8th Edition ed.). New York: McGraw-Hill.
Kermally, S. (2016). Marketing & Economics. Spain: Vernon Press.
Kim, Y. (2019). Developing a Work‐Ready Social Media Marketing Analytics Course: A Model to Cultivate Data‐Driven and Multiperspective Strategy Development Skills. Decision Sciences Journal of Innovative Education, 17(2), 163-188. doi:10.1111/dsji.12175
Mela, C. F., & Moorman, C. (2018). Why Marketing Analytics Hasn't Lived Up to Its Promise. Harvard Business Review Digital Articles, 2-6.
Ogrean, C. (2019). Relevance of Big Data for Business and Management. Exploratory Insights (Part II). Studies in Business and Economics, 14(1), 169-180. doi:10.2478/sbe-2019-0013
Sathi, A. (2014). Engaging Customers Using Big Data. [electronic resource]: How Marketing Analytics are Transforming Business: Palgrave Macmillan US.
Struhl, S. M. (2017). Artificial Intelligence Marketing and Predicting Consumer Choice: An Overview of Tools and Techniques. New York: Kogan Page.
SCB Economic Intelligence Center. (2018). Business Outlook Quarter 1/2018. Retrieved from www.scbeic.com
Weathers, D., & Aragón, O. (2019). Integrating Analytics into Marketing Curricila: Challenges and Effective Practices for Developing Six Critical Competencies. Marketing Education Review, 29(4), 266-282. doi:10.1080/10528008.2019.1673664
Wedel, M., & Kannan, P. K. (2016). Marketing Analytics for Data-Rich Environments. Journal of Marketing, 80(6), 97-121. doi:10.1509/jm.15.0413
Wilson, E. J., McCabe, C., & Smith, R. S. (2018). Curriculum Innovation for Marketing Analytics. Marketing Education Review, 28(1), 52-66. doi:10.1080/10528008.2017.1419431
Xu, Z., Frankwick, G. L., & Ramirez, E. (2016). Effects of Big Data Snalytics and Traditional Marketing Analytics on New Product Success: A Knowledge Fusion Perspective. Journal of Business Research, 69(5), 1562-1566. doi:10.1016/j.jbusres.2015.10.017