AI-Driven Algorithms: Transforming Customer Engagement with AI and Ethical Data Privacy


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.

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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.

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