AI in Consumer Behavior Analysis and Digital Marketing: A Strategic Approach

The rapid advancement of Artificial Intelligence (AI) has revolutionized consumer behavior analysis and digital marketing strategies by enabling personalized and efficient data-driven approaches. AI-driven tools like predictive analytics, natural language processing (NLP), machine learning, and programmatic advertising allow marketers to process vast amounts of real-time consumer data, facilitating optimized campaign performance and precise targeting. This paper explores the integration of AI in marketing, highlighting its role in enhancing predictive analytics, sentiment analysis, and real-time segmentation. Compared to traditional methods, AI-driven insights significantly improve engagement, accuracy, and return on investment (ROI). AI also plays a vital role in marketing automation, allowing dynamic adjustments in campaigns, ad placements, and content creation, improving efficiency and reducing costs. However, AI’s reliance on consumer data raises concerns regarding data privacy and algorithmic bias, especially in targeting. This paper stresses the importance of ensuring transparency, fairness, and regular audits in AI systems to maintain consumer trust and promote ethical AI use. Future research directions are discussed, focusing on enhancing transparency and algorithmic accountability while navigating the ethical challenges of AI in marketing.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.70301/conf.sbs-jabr.2024.1/1.5
Citations
6
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
2.94
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article

AI in Consumer Behavior Analysis and Digital Marketing: A Strategic Approach

Nane Davtyan
6 citations
Impact of AI and Big Data on Business and Society
2.94
article

AI in Consumer Behavior Analysis and Digital Marketing: A Strategic Approach

Nane Davtyan
article en
6 citations

Abstract

The rapid advancement of Artificial Intelligence (AI) has revolutionized consumer behavior analysis and digital marketing strategies by enabling personalized and efficient data-driven approaches. AI-driven tools like predictive analytics, natural language processing (NLP), machine learning, and programmatic advertising allow marketers to process vast amounts of real-time consumer data, facilitating optimized campaign performance and precise targeting. This paper explores the integration of AI in marketing, highlighting its role in enhancing predictive analytics, sentiment analysis, and real-time segmentation. Compared to traditional methods, AI-driven insights significantly improve engagement, accuracy, and return on investment (ROI). AI also plays a vital role in marketing automation, allowing dynamic adjustments in campaigns, ad placements, and content creation, improving efficiency and reducing costs. However, AI’s reliance on consumer data raises concerns regarding data privacy and algorithmic bias, especially in targeting. This paper stresses the importance of ensuring transparency, fairness, and regular audits in AI systems to maintain consumer trust and promote ethical AI use. Future research directions are discussed, focusing on enhancing transparency and algorithmic accountability while navigating the ethical challenges of AI in marketing.

Openalex Percentile: Top 8%
Impact of AI and Big Data on Business and Society
2.94
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