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Assistant Professor, Faculty of Management, SRM Institute of Science and Technology , Tiruchirappalli, Tamil Nadu , India
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Assistant Professor (Senior Grade), Faculty of Management, SRM Institute of Science and Technology , Vadapalani, Chennai, Tamil Nadu , India
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Assistant Professor, Department of Management Sciences, Velammal Engineering College , Surapet, Chennai, Tamil Nadu , India
Associate Professor, Department of Management Studies, St. Josephs Institute of Technology , OMR, Chennai, Tamil Nadu , India
This research paper examines how the strategic marketing analytics, which combines big data, artificial intelligence (AI), and knowledge management can be used to improve the competitive advantage in data-driven markets. The research tests the effectiveness of AI-driven analytics in enhancing the performance of the market, customer high retention and marketing responsiveness using a sample of five companies. The results demonstrate that AI-based strategies led to a 35% increase in market performance and a 25% rise in customer retention. Additionally, the implementation of data governance practices resulted in a 40% reduction in data processing time and a 30% improvement in data accuracy. The study also highlights the role of dynamic capabilities in enabling organizations to swiftly adapt to market changes, with companies using AI and data analytics achieving a 20% faster response to market shifts. The study highlights the significance of big data, AI, and knowledge management integration in propelling marketing strategies that do not just aim at maximizing customer engagements, but also business growth in the long term. The results indicate that companies that make use of such technologies are in a better position to make well-informed decisions, marketing efforts can be personalized, and responsiveness to changes in the market so that they can gain a sustainable competitive advantage. The paper presents empirical information concerning the efficiency of insight-driven strategies within the digital marketing environment and offers useful information to companies that would like to improve the functioning of their marketing enterprise through the use of data-driven innovations.
This is an open access article distributed under the Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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