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Shaping the Future of Brand Management by AI-Powered Predictions
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Author(s): Mohamed Badouch (Ibn Zohr University, Morocco), Hasna Mahmoud (Ibn Zohr University, Morocco)and Mehdi Boutaounte (National School of Commerce and Management, Morocco)
Copyright: 2025
Pages: 16
Source title:
Strategic Brand Management in the Age of AI and Disruption
Source Author(s)/Editor(s): Zahid Hussain (Khadim Ali Shah Institute of Technology, Karachi, Pakistan), Mohamad-Noor Salehhuddin Sharipudin (Universiti Putra Malaysia, Malaysia), Ahmad Albattat (Management and Science University, Malaysia)and Arman Khan (Shaheed Benazir Bhutto University, Pakistan)
DOI: 10.4018/979-8-3693-9461-8.ch014
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Abstract
This chapter explores the transformative potential of recommender systems for predictive analytics in brand management, emphasizing the crucial role of data-driven insights in shaping strategic decisions and driving sustainable growth. We analyze how AI-powered recommender systems can be leveraged to forecast consumer demand, identify emerging market trends, and proactively opportunities in a dynamic business environment. We will delve into the mathematical underpinnings of predictive analytics, exploring time series modeling and machine learning algorithms used in recommender systems. We will also discuss the role of big data and data visualization in informing strategic brand decisions, showcasing how these techniques can reveal hidden patterns, identify customer segments, and optimize resource allocation. Finally, this chapter will address the ethical considerations of predictive analytics, examining the potential for algorithmic bias and the erosion of consumer trust, and proposing strategies for ensuring fairness and accountability in AI-driven brand management.
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