Mitigating risk building customer (3 résultats)

Etat : New.

Buch. Etat : Neu. Neuware - The rapid advancement of artificial intelligence (AI) has attracted significant attention from researchers, practitioners, and policymakers seeking to address the complex challenges it presents, with privacy and trust emerging among the most critical concerns. These issues are particularly relevant in marketing, where AI increasingly shapes how organizations understand, reach, and engage consumers. As businesses and regulators work to keep pace with evolving technologies, questions surrounding data security, transparency, and ethical AI use continue to grow. AI-driven marketing relies heavily on vast amounts of consumer data to generate insights, personalize experiences, and support strategic decision-making. However, the extensive collection and use of such data also increase the risks associated with breaches, misuse, and loss of consumer confidence. When trust is compromised, customer relationships and brand reputation can be significantly affected. Despite the growing importance of these issues, there remains a need for a comprehensive, multidisciplinary resource that examines the intersection of AI, marketing, privacy, and trust. Mitigating Risk and Building Customer Trust Through Responsible AI Practices in Marketing advances a framework for responsible AI-driven marketing, positioning trust as a strategic outcome that organizations must intentionally cultivate rather than a byproduct of technological adoption. This book examines how AI is transforming marketing decision-making, customer analytics, and data-driven personalization while addressing the ethical, legal, and operational risks associated with extensive consumer data use. Covering topics such as algorithmic bias, consumer privacy, and human oversight, this book serves as an indispensable resource for graduate and doctoral students, digital marketing practitioners, data privacy and compliance professionals, chief marketing officers, brand executives, policymakers, researchers, and academics.…

Taschenbuch. Etat : Neu. Neuware - The rapid advancement of artificial intelligence (AI) has attracted significant attention from researchers, practitioners, and policymakers seeking to address the complex challenges it presents, with privacy and trust emerging among the most critical concerns. These issues are particularly relevant in marketing, where AI increasingly shapes how organizations understand, reach, and engage consumers. As businesses and regulators work to keep pace with evolving technologies, questions surrounding data security, transparency, and ethical AI use continue to grow. AI-driven marketing relies heavily on vast amounts of consumer data to generate insights, personalize experiences, and support strategic decision-making. However, the extensive collection and use of such data also increase the risks associated with breaches, misuse, and loss of consumer confidence. When trust is compromised, customer relationships and brand reputation can be significantly affected. Despite the growing importance of these issues, there remains a need for a comprehensive, multidisciplinary resource that examines the intersection of AI, marketing, privacy, and trust. Mitigating Risk and Building Customer Trust Through Responsible AI Practices in Marketing advances a framework for responsible AI-driven marketing, positioning trust as a strategic outcome that organizations must intentionally cultivate rather than a byproduct of technological adoption. This book examines how AI is transforming marketing decision-making, customer analytics, and data-driven personalization while addressing the ethical, legal, and operational risks associated with extensive consumer data use. Covering topics such as algorithmic bias, consumer privacy, and human oversight, this book serves as an indispensable resource for graduate and doctoral students, digital marketing practitioners, data privacy and compliance professionals, chief marketing officers, brand executives, policymakers, researchers, and academics. …