Kiran Chaudhary - Böcker

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:Big data analytics and algorithmMarket basket analysisAnticipating consumer purchase behaviorVariation in shopping patternsBig data analytics for market intelligenceThe third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:Big data analytics and algorithmMarket basket analysisAnticipating consumer purchase behaviorVariation in shopping patternsBig data analytics for market intelligenceThe third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligenceData analytics and consumer behaviorThe role of big data analytics in organizational decision-makingThis book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analyticsWeb analytics for digital marketingSmart retailingLeveraging web analytics for optimizing digital marketing strategiesBig Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligenceData analytics and consumer behaviorThe role of big data analytics in organizational decision-makingThis book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analyticsWeb analytics for digital marketingSmart retailingLeveraging web analytics for optimizing digital marketing strategiesBig Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviourAI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviourAI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.

In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.

This book includes peer-reviewed contributions presented at the International Conference on Data Analytics in Business and Marketing, ICDABM 2022. The book covers topics in data analytics, intelligent data, data management in business and marketing, big data, computational intelligence, and communication networks.