MARKETING IN THE AGE OF AI: HARNESSING TECHNOLOGY TO UNDERSTAND CONSUMER BEHAVIOR
DOI:
https://doi.org/10.31539/costing.v7i6.14284Keywords:
Artificial Intelligence, Consumer Behavior, Personalization, Marketing StrategyAbstract
The integration of artificial intelligence (AI) in marketing has significantly altered how businesses understand and interact with consumers. This study aims to explore how AI can enhance consumer behavior analysis and optimize marketing strategies through advanced predictive and personalization technologies. Employing a qualitative approach, data were collected through semi-structured interviews with marketing professionals and secondary data from industry reports. Thematic analysis was used to analyze findings, revealing that AI enables marketers to predict consumer needs, segment audiences more effectively, and provide highly personalized interactions. The results indicate that AI-driven personalization not only increases customer engagement but also fosters long-term loyalty. Furthermore, this research highlights the need for ethical considerations in AI use, such as data privacy, to maintain consumer trust. These findings offer valuable insights for businesses aiming to leverage AI for more effective and consumer-centered marketing strategies. Future research is suggested to examine the ethical implications of AI in marketing across diverse industries.
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Varadarajan, R. (2018). Toward the sustainable growth of business and marketing strategy research: A commentary. Journal of the Academy of Marketing Science, 46(1), 7–10. https://doi.org/10.1007/s11747-017-0566-y
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Bock, D., Wolter, J., & Ferrell, O. C. (2021). The marketing implications of artificial intelligence. Journal of Marketing Theory and Practice, 29(2), 135–147. https://doi.org/10.1080/10696679.2020.1820561
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, 95(4), 3-11. https://doi.org/10.2139/ssrn.3000753
Chen, J., & Zhang, Y. (2020). Artificial intelligence in marketing: Evolution, current applications, and future directions. Journal of Marketing Science, 8(2), 37–55. https://doi.org/10.1177/2158244020914645
Chen, M., Zhang, X., & Li, Y. (2021). The impact of artificial intelligence on customer engagement: Evidence from big data analysis. Journal of Business Research, 123, 105-115. https://doi.org/10.1016/j.jbusres.2020.09.037
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0
Doyle, G., McNamara, M., & O’Doherty, P. (2021). Predictive analytics in digital marketing: A systematic review. Journal of Marketing Analytics, 9(1), 45–58. https://doi.org/10.1057/s41270-021-00126-8
Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2021). The future of technology and marketing: A multidisciplinary perspective. Journal of Marketing, 85(1), 1-17. https://doi.org/10.1177/0022242920952863
Gupta, S., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049-1064. https://doi.org/10.1016/j.im.2016.07.004
Gursoy, D., & Chi, C. G. (2020). Effects of artificial intelligence on brand loyalty: A comprehensive analysis. Tourism Management Perspectives, 33, 100610. https://doi.org/10.1016/j.tmp.2020.100610
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2), 46–55. https://doi.org/10.18267/j.cebr.213
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
Kumar, V., & Pansari, A. (2016). Competitive advantage through engagement. Journal of Marketing Research, 53(4), 497–514. https://doi.org/10.1509/jmr.15.0044
Marinchak, C., Forrest, E., & Hoanca, B. (2018). An assessment of artificial intelligence in online customer service. Journal of Marketing Development and Competitiveness, 12(1), 10-16. https://doi.org/10.33423/jmdc.v12i1.682
Martin, K. D., & Murphy, P. E. (2020). The ethics of data and analytics in consumer research. Journal of Business Ethics, 167(2), 301-314. https://doi.org/10.1007/s10551-019-04177-3
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716679679
Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice. Sage Publications.
Rai, A., & Tang, X. (2017). Customer behavior in the age of AI: Understanding the impact of AI-driven recommendations. Marketing Science Review, 15(2), 35–47. https://doi.org/10.1111/msre.12375
Rust, R. T., & Huang, M.-H. (2021). The AI marketing canvas: A framework for implementing artificial intelligence in marketing. California Management Review, 63(2), 72–94. https://doi.org/10.1177/0008125620978140
Saldana, J. (2016). The coding manual for qualitative researchers. Sage Publications.
Schwartz, S., McNaughton, D., & Cargill, R. (2021). Long-term impacts of AI on brand loyalty: A marketing perspective. Marketing Theory and Practice, 19(3), 275-288. https://doi.org/10.1080/10422579.2021.1893165
Syam, N., & Sharma, A. (2018). Waiting for a breakthrough: An AI revolution in marketing. Journal of Marketing Research, 55(5), 563–575. https://doi.org/10.1509/jmr.16.0170
Tang, Y., & Wang, X. (2019). Consumers’ perceptions of AI-driven recommendations. International Journal of Consumer Studies, 43(5), 485-493. https://doi.org/10.1111/ijcs.12550
Turow, J., Hennessy, M., & Draper, N. (2018). The tradeoff fallacy: How marketers are misrepresenting American consumers and opening them up to exploitation. Journal of Marketing Behavior, 4(1), 9–29. https://doi.org/10.1561/107.00000031
Varadarajan, R. (2018). Toward the sustainable growth of business and marketing strategy research: A commentary. Journal of the Academy of Marketing Science, 46(1), 7–10. https://doi.org/10.1007/s11747-017-0566-y
Wirtz, J., & Zeithaml, V. (2018). Cost-effectiveness of artificial intelligence: Comparing human and AI-based service provision. Journal of Service Research, 21(3), 267-284. https://doi.org/10.1177/1094670518770030
Yuan, H., & Chen, X. (2020). Understanding artificial intelligence applications in marketing. Journal of Business Research, 108, 305-316. https://doi.org/10.1016/j.jbusres.2019.10.056
Zhou, Y., Liu, L., & Zhou, J. (2019). Big data analytics and marketing: Exploring new opportunities. Marketing Science Review, 18(1), 45–57. https://doi.org/10.1111/msre.12189
Zuboff, S. (2019). Surveillance capitalism and the challenge of privacy. Journal of Information Technology, 34(1), 105-119. https://doi.org/10.1177/0268396218819131
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2024-12-31
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