Authors :
Laila Arzuman Ara; MD Ishtiyak Rahman
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/myw47ya7
Scribd :
https://tinyurl.com/dkhe5n96
DOI :
https://doi.org/10.5281/zenodo.14603644
Abstract :
Artificial Intelligence (AI) is revolutionizing
marketing through advanced person- alization, enhanced
customer engagement, and optimized strategies. This
study explores AI’s impact on metrics like click-through
rates (CTR), conversion rates, and customer retention
while addressing ethical concerns, including data privacy,
consumer autonomy, and algorithmic bias. Employing a
mixed-method approach, the research integrates machine
learning for predictive analytics, sentiment anal- ysis of
customer feedback, and corporate content analysis.
Quantitative results reveal significant gains, such as a
150% increase in CTR and a 140% rise in conversion
rates due to AI-driven personalization. However,
qualitative findings highlight consumer concerns about
intrusiveness, data misuse, and corporate transparency
gaps. The study emphasizes AI’s dual role in enhancing
experi- ences and posing ethical dilemmas. It advocates
for transparent systems, robust privacy safeguards, and
explainable algorithms to build trust and equity. These
insights offer a road map for leveraging AI to balance
innovation with ethical responsibility, fostering
sustainable, consumer-centred marketing practices.
Keywords :
Artificial Intelligence in Marketing; Explainable AI (XAI) in Marketing; Hybrid AI Models in Marketing; Personalized Customer Engagement; Data Privacy in Marketing; Ethical AI in Advertising; Predictive Analytics in Marketing.
References :
- Nalini, M., Radhakrishnan, D.P., Yogi, G., Santhiya, S., Harivardhini, V., et al.: Impact of artificial intelligence (ai) on marketing. Int. J. of Aquatic Science 12(2), 3159–3167 (2021)
- Barari, M., Casper Ferm, L.-E., Quach, S., Thaichon, P., Ngo, L.: The dark side of artificial intelligence in marketing: meta-analytics review. Marketing Intelligence Planning 42 (2024) https://doi.org/10.1108/MIP-09-2023-0494
- Masnita, Y., Kasuma, J., Zahra, A., Wilson, N., Murwonugroho, W.: Artificial intelligence in marketing: Literature review and future research agenda. Journal of System and Management Sciences 14, 120–140 (2024) https://doi.org/10.33168/ JSMS.2024.0108
- Wang, J.F.: The impact of artificial intelligence (ai) on customer relationship management: A qualitative study. Int. J. Manag. Account 5(5), 74–88 (2023)
- Verma, S., Sharma, R., Deb, S., Maitra, D.: Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Infor- mation Management Data Insights 1(1), 100002 (2021) https://doi.org/10.1016/ j.jjimei.2020.100002
- Dias, T., Gon¸calves, R., Costa, R.L., Pereira, L.F., Dias, A´.: The impact of arti- ficial intelligence on consumer behaviour and changes in business activity due to pandemic effects. Human Technology 19(1), 121–148 (2023)
- Wilson, G., Johnson, O., Brown, W.: The impact of artificial intelligence on customer relationship management (2024)
- Khrais, L.T.: Role of artificial intelligence in shaping consumer demand in e- commerce. Future Internet 12(12), 226 (2020)
- Xie, T.: Artificial intelligence and automatic recognition application in b2c e- commerce platform consumer behavior recognition. Soft Computing-A Fusion of Foundations, Methodologies & Applications 27(11) (2023)
- Babu, S.M., Kumar, P.P., Devi, S., Reddy, K.P., Satish, M., et al.: Predicting consumer behaviour with artificial intelligence. In: 2023 IEEE 5th Interna- tional Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), pp. 698–703 (2023). IEEE
- Abrardi, L., Cambini, C., Rondi, L.: Artificial intelligence, firms and consumer behavior: A survey. Journal of Economic Surveys 36(4), 969–991 (2022)
- Khan, S., Tomar, S., Fatima, M., Khan, M.Z.: Impact of artificial intelligent and industry 4.0 based products on consumer behaviour characteristics: A meta- analysis-based review. Sustainable Operations and Computers 3, 218–225 (2022)
- Shaik, M.: Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research 2(3), 993–1004 (2023)
- Huang, M.-H., Rust, R.T.: A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science 49, 30–50 (2021)
- Safdar, N.M., Banja, J.D., Meltzer, C.C.: Ethical considerations in artificial intelligence. European journal of radiology 122, 108768 (2020)
- Malgieri, G., Custers, B.: Pricing privacy – the right to know the value of your personal data. Computer Law Security Review 34(2), 289–303 (2018) https://doi.org/10.1016/j.clsr.2017.08.006
- Johnson, G.A., Shriver, S.K., Du, S.: Consumer privacy choice in online advertis- ing: Who opts out and at what cost to industry? Marketing Science 39(1), 33–51 (2020)
- Kavenna, J.: Shoshana zuboff:‘surveillance capitalism is an assault on human autonomy’. The Guardian 4 (2019)
- Park, G.: The changing wind of data privacy law: A comparative study of the euro- pean union’s general data protection regulation and the 2018 california consumer privacy act. UC Irvine L. Rev. 10, 1455 (2019)
- Leech, N.L., Onwuegbuzie, A.J.: A typology of mixed methods research designs. Quality & quantity 43, 265–275 (2009)
- Schoonenboom, J., Johnson, R.B.: How to construct a mixed methods research design. Kolner Zeitschrift fur Soziologie und Sozialpsychologie 69(Suppl 2), 107 (2017)
- Symonds, E.: A practical application of surveymonkey as a remote usability- testing tool. Library Hi Tech 29(3), 436–445 (2011)
- Asuncion, A., Newman, D., et al.: UCI machine learning repository. Irvine, CA, USA (2007)
- Snyder, R., Bish, D.L.: Quantitative analysis. Modern powder diffraction 20, 101–144 (1989)
- Andr´e, Q., Carmon, Z., Wertenbroch, K., Crum, A., Frank, D., Goldstein, W., Huber, J., Van Boven, L., Weber, B., Yang, H.: Consumer choice and autonomy in the age of artificial intelligence and big data. Customer needs and solutions 5, 28–37 (2018)
- Bjørlo, L., Moen, Ø., Pasquine, M.: The role of consumer autonomy in developing sustainable ai: A conceptual framework. Sustainability 13(4), 2332 (2021)
- Nijhawan, L.P., Janodia, M.D., Muddukrishna, B., Bhat, K.M., Bairy, K.L., Udupa, N., Musmade, P.B.: Informed consent: Issues and challenges. Journal of advanced pharmaceutical technology & research 4(3), 134–140 (2013)
- Manti, S., Licari, A.: How to obtain informed consent for research. Breathe 14(2), 145–152 (2018)
- Lippi, M., Contissa, G., Jablonowska, A., Lagioia, F., Micklitz, H.-W., Palka, P., Sartor, G., Torroni, P.: The force awakens: Artificial intelligence for consumer law. Journal of artificial intelligence research 67, 169–190 (2020)
- Westr´en-Doll, N.: The computer knows best: Ai-powered personalization in marketing through the lens of data privacy. Master’s thesis (2024)
- Jabl-onowska, A., Kuziemski, M., Nowak, A.M., Micklitz, H.-W., Pal-ka, P., Sartor, G.: Consumer law and artificial intelligence. EUI Department of Law Research Paper 11 (2018)
- Nystoriak, M.A., Bhatnagar, A.: Cardiovascular effects and benefits of exercise. Frontiers in cardiovascular medicine 5, 408204 (2018)
- Kumar, V., Rajan, B.: Customer lifetime value: What, how, and why. In: The Routledge Companion to Strategic Marketing, pp. 422–448. Routledge, ??? (2020)
- Arrieta, A.B., D´ıaz-Rodr´ıguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garc´ıa, S., Gil-L´opez, S., Molina, D., Benjamins, R., et al.: Explainable artifi- cial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai. Information fusion 58, 82–115 (2020)
Artificial Intelligence (AI) is revolutionizing
marketing through advanced person- alization, enhanced
customer engagement, and optimized strategies. This
study explores AI’s impact on metrics like click-through
rates (CTR), conversion rates, and customer retention
while addressing ethical concerns, including data privacy,
consumer autonomy, and algorithmic bias. Employing a
mixed-method approach, the research integrates machine
learning for predictive analytics, sentiment anal- ysis of
customer feedback, and corporate content analysis.
Quantitative results reveal significant gains, such as a
150% increase in CTR and a 140% rise in conversion
rates due to AI-driven personalization. However,
qualitative findings highlight consumer concerns about
intrusiveness, data misuse, and corporate transparency
gaps. The study emphasizes AI’s dual role in enhancing
experi- ences and posing ethical dilemmas. It advocates
for transparent systems, robust privacy safeguards, and
explainable algorithms to build trust and equity. These
insights offer a road map for leveraging AI to balance
innovation with ethical responsibility, fostering
sustainable, consumer-centred marketing practices.
Keywords :
Artificial Intelligence in Marketing; Explainable AI (XAI) in Marketing; Hybrid AI Models in Marketing; Personalized Customer Engagement; Data Privacy in Marketing; Ethical AI in Advertising; Predictive Analytics in Marketing.