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 behaviour AI-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 strategie.

Qualification, experience, competence and personality -how should a manager weigh these while recruiting? Does it pay to take on a 'star' performer? What, indeed, is the secret of good hiring? There's no organizational process more important than recruitment. However, traditional resume- and interview-based hiring often does not account for the most important factor: personality. But what individual traits must one measure, and how? Skilled interviewers know that the trick lies in not just asking questions that challenge the candidate, but in figuring out whether his or her answer reveals a fit between the company's expectations and the personality of the interviewee.