AI in Consumer Behavior Analysis and Digital Marketing: A Strategic Approach
Nane Davtyan
SBS Swiss Business School Research Conference (SBS-RC) from SBS Swiss Business School
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.
Keywords: Artificial Intelligence (AI); Consumer behavior analysis; Digital marketing; Predictive analytics; Natural language processing (NLP) (search for similar items in EconPapers)
Pages: 10 pages
Date: 2024-10
New Economics Papers: this item is included in nep-acc, nep-cmp, nep-inv, nep-mac and nep-mkt
References: View references in EconPapers View complete reference list from CitEc
Citations:
Published in book of proceedings of SBS Swiss Business School Research Conference 2024, pages 61-70
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https://research.sbs.edu/sbsrc/SBSRC24_Paper05.pdf (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:bfv:sbsrec:005
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