THE ROLE OF AI AND MASS CUSTOMIZATION
in marketing strategies
Artificial intelligence, or ai , was first coined by John McCarthy in 1956. Eventually, ai was treated as part of computer science engineering which promoted the role of intelligent machines capable of perceiving their environment and taking a suitable action to maximize success in doing various tasks (Singh et al., 2013). Over the years, the application of ai has extended to various disciplines, including marketing. As competition increased, ai had been successfully used as a tool to tailor marketing strategies. Assimilating the insights from Big data analytics, ai had assisted companies to maintain a competitive edge in crm strategies of customization and personalization (Kamel, 2023). Companies which were using ai tools had been able to effectively change their marketing strategies in real time, making their messages more relevant for the customers, this lead to higher customer engagement and conversion rates (Iyelolu et al., 2024). Furthermore, through personalization, this technology lead to enhanced customer experience and customer loyalty (Ifekanandu et al., 2023).
ai tried to emulate human beings in doing physical tasks, cognitive thinking, and emotions. These capabilities of ai had been conceptualized as part of a marketing strategy framework proposed by Huang and Rust (2021). According to this framework, mechanical ai could collect and process data for market research; segmenting customers on basis of their preferences; standardization of 4 P’s —product, price, place, and promotion— through automation in making the product available at a certain price; facilitated through payment gateways at websites; and promoting to a group of customers. The cognitive ai could identify competition through market analytics; target the customers; and personalize products, prices and promotion through interactions. The emotional feeling ai would be capable of understanding customer needs, position the products, negotiate price, and personalize the customer
Ekasari, S., Judijanto, L., & Vandika, A. Y. (2024). The role of artificial intelligence and machine learning in precision targeting: revolutionizing marketing strategies. Jurnal Ekonomi dan Bisnis, 2(3), 347-361.
Huang, M. H. & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
Ifekanandu, C. C., Anene, J. N., Iloka, C. B., & Ewuzie, C. O. (2023). Influence of artificial intelligence (ai ) on customer experience and loyalty: mediating role of personalization. Journal of Data Acquisition and Processing, 38(3), p.1936.
Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024). Leveraging artificial intelligence for personalized marketing campaigns to improve conversion rates. International Journal of Engineering Research and Development, 20(8), 253-270.
experience, leading to higher customer engagements and tailoring customer emotional preferences.
According to Piller and Euchner (2024), mass customization had been perfected with products tailored to the customer expectations based on traces of online data left behind by the customer, thereby ruling out customer’s direct involvement. Thus, precision marketing or data driven marketing facilitated predictive analysis of customer needs and could become part of business differentiation strategies (Ekasari et al., 2024). On the flip side, protecting customer data, security and ethical concerns had to be addressed by companies (Mishra and Triptahi, 2021). Companies would also face challenges of upgrading technology infrastructure, training employees, and gaining customer trust (Wisetsri et al., 2022).
In conclusion, like any form of innovation, ai needs to be used with caution so that it does not promote consumerism or unethical practices of companies, but rather sustainable consumption in benefit of the consumers, companies, and the environment.
Kamel, M. A. (2023). Big data analytics and market performance: the roles of customization and personalization strategies and competitive intensity. Journal of Enterprise Information Management, 36(6), 1727-1749.
Mishra, S. & Tripathi, A. R. (2021). ai business model: an integrative business approach. Journal of Innovation and Entrepreneurship, 10(1), 18.
Piller, F. & Euchner, J. (2024). Mass customization in the age of ai : a conversation with Frank Piller. Research-Technology Management, 67(4), 14-20.
Singh, G., Mishra, A., & Sagar, D. (2013). An overview of artificial intelligence. SBIT Journal of Sciences and Technology, 2(1), 1-4.
Wisetsri, W., Vijai, C., Chueinwittaya, K., & Jirayus, P. (2022). Artificial Intelligence in Human Resources Management-An Overview. Journal of Positive School Psychology, 6(2), 26882693.
