Predictive Analytics and Generative AI for Data-Driven Marketing Strategies
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Predictive Analytics and Generative AI for Data-Driven Marketing Strategies: (Artificial Intelligence, Machine Learning, Data Analytics and Automation for Business Management)

Predictive Analytics and Generative AI for Data-Driven Marketing Strategies: (Artificial Intelligence, Machine Learning, Data Analytics and Automation for Business Management)


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About the Book

In providing an in-depth exploration of cutting-edge technologies and how they are used to support data-driven marketing strategies and empower organizations to make the right decisions, Predictive Analytics and Generative AI for Data-Driven Marketing Strategies includes real-world case studies and examples from diverse marketing domains. This book demonstrates how predictive analytics and generative AI have been successfully applied to solve marketing challenges and drive tangible results. This book showcases emerging trends in predictive analytics and generative AI for marketing, and their potential impact on the future of data-driven marketing. This book is meant for professionals and scholars to gather the skills and resources to use predictive analytics and generative AI effectively for marketing strategies. This book: • Examines the different predictive analytics models and algorithms, such as regression analysis, decision trees, and neural networks, and demonstrates how they may be utilized to get insightful conclusions from marketing data. • Includes generative AI techniques, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), showcasing how these techniques can generate synthetic data for marketing insights and decision-making. • Highlights the importance of data-driven marketing choices and illustrates how generative AI and predictive analytics may be quite useful in this context. • Integrates the principles of data science with marketing concepts, offering a cohesive understanding of how predictive analytics and generative AI can power data-driven marketing decisions. • Presents the recent advances in predictive analytics and generative AI and discusses how they can affect the area of data-driven marketing.

Table of Contents:
Chapter 1: Introduction to Predictive Analysis and Generative AI. Chapter 2: Fundamentals of data-driven marketing. Chapter 3: Future trends in Predictive Analytics and Generative AI for Marketing. Chapter 4: Analytical Prospective on Fashion Industry: Data Driven Strategies. Chapter 5: Predictive analytics techniques for marketing. Chapter 6: Customer targeting and segmentation. Chapter 7: Personalised Marketing and Recommendation Systems. Chapter 8: Pricing Optimization Using Predictive Analytics. Chapter 9: Churn Prediction and Customer Retention. Chapter 10: Marketing Campaign Optimization. Chapter 11: Customer Retention Using Machine Learning Techniques in Human Resource Industry: A Systemic Literature. Chapter 12: A Persona-Based Approach for Churn Prediction and Retention Strategies Driven by Predictive Analytics and Generative AI. Chapter 13: Sentiment Analysis and Social Media Marketing. Chapter 14: Generative AI Techniques for Marketing. Chapter 15: Privacy and Ethical Considerations in Data-Driven Marketing. Chapter 16: Price Prediction and Optimization in Predictive Analytics and Generative AI for Data-Driven Marketing Strategies. Chapter 17: Synthetic Data Generation for Marketing Insights. Chapter 18: Measuring Marketing Effectiveness and Return on Investment. Chapter 19: Emerging Technologies Shaping the Future of Marketing. Chapter 20: Customer Segmentation Techniques in Predictive Analytics and Generative AI for Data-Driven Marketing Strategies. Chapter 21: Case Studies in Data-Driven Marketing. Chapter 22: Case Studies in Churn Prediction and Customer Retention. Chapter 23: Leveraging Generative AI for Personal Branding.

About the Author :
Dr. Hemachandran Kannan is a professor in the department of Artificial Intelligence & Business Analytics at School of Business, Woxsen University, India and holds the Zita Zoltay Paprika of Decision Sciences and Business Economics and Course5i- Chair Professor of Business Analytics and Machine Learning. He has been a passionate teacher with 15 years of teaching experience and 5 years of research experience. A strong educational professional with a scientific bent of mind, highly skilled in AI (Artificial Intelligence) & Business Analytics. After receiving a PhD in embedded systems, He started focusing on Interdisciplinary research. He served as an effective resource person at various national and international scientific conferences and panel discussions. He also gave lectures on topics related to Artificial Intelligence & Business Analytics. He was bestowed as best faculty at Woxsen University in 2021-2022 and in Ashoka Institute of Engineering & Technology in 2019 – 2020. He has rich working experience in Natural Language Processing, Computer Vision, Building Video recommendation systems, Building Chatbots for HR (Human Rights) policies and Education Sector, Automatic Interview processes, and Autonomous Robots. Dr. Hemachandran is currently working on various real-time use cases and projects in collaboration with Industries such as Advert flair, Nosh Technologies, Course5i and Apstek Corp. He has organized many International Conferences, Hackathons and Ideathon. He owed four patents to his credentials. He has a life membership in estimable professional bodies. An open-ended positive person who has a stupendous peer-reviewed publication record with more than 35 journals and international conference publications. As of now, he has authored 3 Books and edited 7 Books in CRC Press Taylor and Francis and IGI Global. Professor Debdutta Choudhury is an academician with 18 years of corporate experience spanning Manufacturing, BFSI, Technology and Education domain. Debdutta has spent most of his career in sales and marketing with exposure to sales strategy, sales management, corporate strategy, integrated marketing communication, corporate finance and general management. Debdutta teaches Marketing courses and has a research interest in technology in marketing, sustainability and pedagogical innovations. He has published several book chapters, cases and presented them in research conferences. At Woxsen, Debdutta handles various accreditations and new initiatives. Dr. Raul Villamarin Rodriguez is the Vice President, Woxsen University and holds the Steven Pinker Professor of Cognitive Psychology and Classavo Chair Professorship in Integrative Research and Digital Learning. Dr. Rodríguez is an Adjunct Professor at Universidad del Externado, Colombia and member of the International Advisory Board at IBS Ranepa, Russian Federation, and a member of the IAB, University of Pécs Faculty of Business and Economics. He is also part of the PRME i5 Expert Pedagogy Group - India representative. He holds a Ph.D. in Artificial Intelligence and Robotics Process Automation applications in Human Resources. Dr. Rodriguez's specific areas of expertise and interest are Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotic Process Automation, Multi-agent Systems, Knowledge Engineering, and Quantum Artificial Intelligence. He has the experience and feels comfortable using Prolog, Java, C++, Python, R/RStudio, Julia, Swift, Scala, MySQL, and Spark, among others. He is a registered expert in Artificial intelligence, Intelligent Systems, and Multi-agent Systems at the European Commission, a nominee for the Forbes 30 Under 30 Europe 2020 list, and awardee in the Europe India 40 under 40 Leaders. Alongside this, he is a member of the GRLI Deans and Directors cohort. He is a regular keynote speaker and panel moderator at various national and international conferences or summits such as ML (Machine Learning) Conference (Singapore). Additionally, he is a member of the Harvard Business Review Advisory Council, the ETS Business School Advisory Council (BSAC) in India, and the Institute for Robotics Process Automation & Artificial Intelligence. He has co-authored two reference books: "New Age Leadership: A Critical Insight" and "Retail Store'e" and has more than 70 publications to his credit. He is a weekly contributing writer to various magazines in the field of analytics and emerging technologies. Alongside this, he is a journal reviewer and associate editor in various publications such as IEEE (Institution of Electrical & Electronics Engineers). Dr. Jorge A. Wise got a PhD from EGADE Business School. He stands out in professional activities, from 1980-2000 working in national and international firms. In 1998 he joined the Monterrey Tech (ITESM) as professor of Marketing and International Business. In 2014 is appointed Director fo the Center or Excellence for Competitiveness and Entrepreneurship at CETYS University. Later, he is appointed as Dean of the brand new CETYS Graduate School of Business. In those years, he is recognized as a member of Mexican National Research System from CONACYT (The Mexican Council for Science and Technology). Dr. Wise is an international professor working in the USA, Latin America and Europe. His latest appointments are at CEIPA Business School, Colombia and at IESEG School of Management, France. He is also a visiting professor at WOXSEN University, Hyderabad, India and Pforzheim University, Germany. Recognized for his work in marketing, international business, strategic management, and family businesses. Revathi T is an academician with 7 years of research experience in computer vision and 3 years of teaching in universities. Revathi has spent most of his career in research with exposure to computer vision, applied mathematics, machine learning and deep learning.Revathi teaches data analytics courses and has a research interest in technology in artificial Intelligence. She has published several research papers in journals and conferences. At Woxsen, Revathi is one of the members in AI Research Centre.


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Product Details
  • ISBN-13: 9781040188767
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman and Hall
  • Language: English
  • ISBN-10: 1040188761
  • Publisher Date: 10 Dec 2024
  • Binding: Digital (delivered electronically)
  • Series Title: Artificial Intelligence, Machine Learning, Data Analytics and Automation for Business Management


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