Predictive Analytics and Generative AI for Data-Driven Marketing Strategies

Hemachandran K, Debdutta Choudhury, Raul Villamarin Rodriguez, Jorge A. Wise, Revathi T

• Publisher: Chapman and Hall/CRC
• Year: 2024
• eBook ISBN: 9781040188835
• Edition: 0
• Topic: Economics
• Subtopic: Business Strategy
• Index: Economics

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

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• About the Editors
• Contributors
• Preface
• 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 Personalized Marketing and Recommendation Systems
• Chapter 8 Pricing Optimisation 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 Systematic 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
• Index