Marketing to machine customers: a paradigm shift in consumer dynamics
DOI:
https://doi.org/10.34140/bjbv6n3-018Palavras-chave:
machine customers, artificial intelligence, consumer behavior, marketing strategies, economic models, internet of things (IoT), predictive algorithmsResumo
In the digital age, artificial intelligence (AI) is not only revolutionizing industries but also transforming the very concept of consumerism. This paper explores the emergence of machine customers—autonomous entities that make purchasing decisions independently of human intervention. These AI-driven consumers, powered by advancements in machine learning and the Internet of Things (IoT), represent a significant shift from traditional human-centric models of consumer behavior. The study delves into the technological advancements propelling this phenomenon, the impact on traditional economic models, and the implications for marketing strategies. By examining the evolution of AI in consumer markets, this paper provides a comprehensive understanding of how businesses can adapt to and thrive in an increasingly automated landscape. It also addresses the ethical considerations and regulatory frameworks necessary to ensure that AI-driven consumerism benefits society equitably. The rise of machine customers challenges existing paradigms, compelling a reevaluation of supply and demand dynamics and necessitating innovative approaches to customer engagement and market participation.
Referências
Adams, A., Smith, B., & Clark, C. (2012) 'Towards Autonomic Marketing'. Available at: https://dx.doi.org/10.2139/ssrn.878617 (Accessed: 31 July 2024).
Aftab, M., Ahmad, U., Khalid, S., Saud, A., Hassan, A., & Farooq, M., 2021. Sentiment Analysis of Customer for Ecommerce by Applying AI. 2021 International Conference on Innovative Computing (ICIC), pp. 1-7. https://doi.org/10.1109/icic53490.2021.9693026 (Accessed: 11 July 2024).
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2022) 'Algorithmic bias in machine learning-based marketing models', Journal of Business Research, 131, pp. 145-157. Available at: https://doi.org/10.1016/j.jbusres.2022.01.083 (Accessed: 31 July 2024).
Becker, William, et al. “Research on High School Economic Education.” The Journal of Economic Education, vol. 21, no. 3, 1990, pp. 231–45. JSTOR, https://doi.org/10.2307/1182242 (Accessed: 31 July 2024).
Belanche, D., Casaló, L., & Flavián, C., 2019. Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers. Ind. Manag. Data Syst., 119, pp. 1411-1430. https://doi.org/10.1108/IMDS-08-2018-0368 (Accessed: 11 July 2024).
Biswas, K., & b, D., 2023. Role of Artificial Intelligence (AI) in Changing Consumer Buying Behaviour. International Journal of Research Publication and Reviews. https://doi.org/10.55248/gengpi.2023.4227 (Accessed: 11 July 2024).
Dong, Y. (2024). Potential Customer Prediction of Telecom Marketing based on Machine Learning. Highlights in Science, Engineering and Technology, 92, 138-145. https://doi.org/10.54097/bbqe4m48 (Accessed: 31 July 2024).
Fu-guo, Z. (2020) 'Target Customers and Marketing Innovation', Journal of Business Strategy, 32(2), pp. 187-201. Available at: https://dx.doi.org/10.2139/ssrn.878617 (Accessed: 31 July 2024).
Galitsky, B., 2020. Artificial Intelligence for Customer Relationship Management: Keeping Customers Informed. Artificial Intelligence for Customer Relationship Management. https://doi.org/10.1007/978-3-030-52167-7 (Accessed: 11 July 2024).
Gans, J., 2022. AI Adoption in a Competitive Market. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4098318 (Accessed: 11 July 2024).
Gupta, S. and Raju, J. (2006) 'Mass Marketing to Micro Marketing: Democratization of Goods', Marketing Science, 25(6), pp. 595-599. Available at: https://dx.doi.org/10.2139/ssrn.878617 (Accessed: 31 July 2024).
Gkikas, D., & Theodoridis, P., 2019. Artificial Intelligence (AI) Impact on Digital Marketing Research. Strategic Innovative Marketing and Tourism. https://doi.org/10.1007/978-3-030-12453-3_143 (Accessed: 11 July 2024).
Jain, M., & Khurana, J., 2022. An Investigation into the relationship between AI enabled Chabot Interface and Online buying behavior of Consumers in Delhi NCR Region. Asian Journal of Management. https://doi.org/10.52711/2321-5763.2022.00003 (Accessed: 11 July 2024).
Kaponis, A., & Maragoudakis, M., 2022. Data Analysis in Digital Marketing using Machine learning and Artificial Intelligence Techniques, Ethical and Legal Dimensions, State of the Art.. Proceedings of the 12th Hellenic Conference on Artificial Intelligence. https://doi.org/10.1145/3549737.3549756 (Accessed: 31 July 2024).
Kumar, V., Rajan, B., Gupta, S., & Pozza, I. D. (2021) 'Influence of new-age technologies on marketing: A research agenda', Journal of Business Research, 124, pp. 119-137. Available at: https://doi.org/10.1016/j.jbusres.2020.01.007 (Accessed: 31 July 2024).
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019) 'Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases', Marketing Science, 38(6), pp. 937-947. Available at: https://doi.org/10.1287/mksc.2019.1192 (Accessed: 31 July 2024).
Ma, L. & Sun, B. (2020) 'Machine learning and AI in marketing–Connecting computing power to human insights', International Journal of Research in Marketing, 37(1), pp. 1-12. Available at: https://doi.org/10.1016/j.ijresmar.2020.04.005 (Accessed: 31 July 2024).
Malthouse, E., & Copulsky, J., 2022. Artificial intelligence ecosystems for marketing communications. International Journal of Advertising, 42, pp. 128 - 140. https://doi.org/10.1080/02650487.2022.2122249 (Accessed: 11 July 2024).
MAHESWARI, D., 2023. The Transformative Power of AI in Marketing FMCG. International Journal For Multidisciplinary Research. https://doi.org/10.36948/ijfmr.2023.v05i03.3760 (Accessed: 11 July 2024).
Meepung, T., & Kannikar, P., 2022. Artificial Intelligence for Digital Business Performance. 2022 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), pp. 242-246. https://doi.org/10.1109/ECTIDAMTNCON53731.2022.9720418 (Accessed: 11 July 2024).
Mogaji, E., Soetan, T. O., & Kieu, T. A. (2021). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, 29(3), 235-242. https://doi.org/10.1016/j.ausmj.2020.05.003 (Accessed: 31 July 2024).
Mustak, M., Salminen, J., Plé, L., & Wirtz, J., 2020. Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2020.10.044 (Accessed: 11 July 2024).
Omarova, A., & Makarov, V. (2022) 'The Role and Importance of Vending Machines in Marketing Channels'. Available at: https://dx.doi.org/10.33920/nik-02-2212-04 (Accessed: 31 July 2024).
Overgoor, G., Chica, M., Rand, W., & Weishampel, A. (2019). Letting the Computers Take Over: Using AI to Solve Marketing Problems. California Management Review, 61(4), 156-185. https://doi.org/10.1177/0008125619859318 (Accessed: 1 July 2024).
Prakash, N., Singh, R., & Gupta, S. (2023) 'Predicting Consumer Behaviour with Artificial Intelligence', Journal of Consumer Behaviour, 22(2), pp. 241-256. Available at https://doi.org/10.1109/ICCCMLA58983.2023.10346916 (Accessed: 31 July 2024).
Ramkishen, R., & Abha, S. (2019) 'Customers’ Imprint about Cause-Related Marketing Driven through Experiential Marketing', Journal of Marketing Communications, 25(1), pp. 134-151. Available at: https://dx.doi.org/10.35219/eai158404096 (Accessed: 31 July 2024).
Sabbeh, Sahar F.. “Machine-Learning Techniques for Customer Retention: A Comparative Study.” International Journal of Advanced Computer Science and Applications 9 (2018).
Shameem, A., Ramachandran, K., Sharma, A., Singh, R., Selvaraj, F., & Manoharan, G., 2023. The Rising Importance of AI in Boosting the Efficiency of Online Advertising in Developing Countries. 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 1762-1766. https://doi.org/10.1109/icacite57410.2023.10182754 (Accessed: 1 July 2024).
Theodoridis, P., & Gkikas, D., 2019. How Artificial Intelligence Affects Digital Marketing. Strategic Innovative Marketing and Tourism. https://doi.org/10.1007/978-3-030-12453-3_151 (Accessed: 31 July 2024).
Volkmar, G., Jones, M., & Smith, A. (2022a) 'Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management', Journal of Business Research, 145, pp. 14-29. Available at: https://doi.org/10.1016/j.jbusres.2022.04.007 (Accessed: 31 July 2024).
Volkmar, G., Jones, M., & Smith, A. (2022b) 'Artificial intelligence ecosystems for marketing communications', Journal of Marketing, 86(2), pp. 122-141. Available at: https://doi.org/10.1016/j.jbusres.2022.04.007 (Accessed: 31 July 2024).
Zaman, K., 2022. Transformation of Marketing Decisions through Artificial Intelligence and Digital Marketing. Journal of Marketing Strategies. https://doi.org/10.52633/jms.v4i2.210 (Accessed: 11 July 2024).
Zulaikha, A., Rahman, M. M., & Khan, M. H. (2020) 'CUSTOMER PREDICTIVE ANALYTICS USING ARTIFICIAL INTELLIGENCE', International Journal of Business Intelligence and Data Mining, 16(2), pp. 151-168. Available at: https://doi.org/10.1142/s0217590820480021 (Accessed: 31 July 2024).
