{"product_id":"mastering-marketing-data-science-isbn-9781394258710","title":"Mastering Marketing Data Science","description":"\u003cp\u003e\u003cb\u003eUnlock the Power of Data: Transform Your Marketing Strategies with Data Science\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eIn the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In \u003ci\u003eMastering Marketing Data Science: A Comprehensive Guide for Today's Marketers,\u003c\/i\u003e Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively. \u003c\/p\u003e\u003cul\u003e \u003cli\u003e\n\u003cb\u003eComprehensive Coverage:\u003c\/b\u003e From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science.\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003ePractical Applications:\u003c\/b\u003e Engage with real-world examples, hands-on exercises in both Python \u0026amp; SAS, and actionable insights to apply in your marketing campaigns.\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003eExpert Guidance:\u003c\/b\u003e Benefit from Dr. Iain Brown's decade of experience as he shares cutting-edge techniques and ethical considerations in marketing data science.\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003eFuture-Ready Skills:\u003c\/b\u003e Learn about the latest advancements, including generative AI, to stay ahead in the rapidly evolving marketing landscape.\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003eAccessible Learning:\u003c\/b\u003e Tailored for both beginners and seasoned professionals, this book ensures a smooth learning curve with a clear, engaging narrative.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eMastering Marketing Data Science\u003c\/i\u003e is designed as a comprehensive how-to guide, weaving together theory and practice to offer a dynamic, workbook-style learning experience. Dr. Brown's voice and expertise guide you through the complexities of marketing data science, making sophisticated concepts accessible and actionable. \u003c\/p\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eAcknowledgments xiii\u003c\/p\u003e \u003cp\u003eAbout the Author xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Introduction to Marketing Data Science 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 What Is Marketing Data Science? 2\u003c\/p\u003e \u003cp\u003e1.2 The Role of Data Science in Marketing 4\u003c\/p\u003e \u003cp\u003e1.3 Marketing Analytics Versus Data Science 5\u003c\/p\u003e \u003cp\u003e1.4 Key Concepts and Terminology 7\u003c\/p\u003e \u003cp\u003e1.5 Structure of This Book 9\u003c\/p\u003e \u003cp\u003e1.6 Practical Example 1: Applying Data Science to Improve Cross-Selling in a Retail Bank Marketing Department 11\u003c\/p\u003e \u003cp\u003e1.7 Practical Example 2: The Impact of Data Science on a Marketing Campaign 13\u003c\/p\u003e \u003cp\u003e1.8 Conclusion 15\u003c\/p\u003e \u003cp\u003e1.9 References 15\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Data Collection and Preparation 17\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 18\u003c\/p\u003e \u003cp\u003e2.2 Data Sources in Marketing: Evolution and the Emergence of Big Data 19\u003c\/p\u003e \u003cp\u003e2.3 Data Collection Methods 23\u003c\/p\u003e \u003cp\u003e2.4 Data Preparation 25\u003c\/p\u003e \u003cp\u003e2.5 Practical Example: Collecting and Preparing Data for a Customer Churn Analysis 39\u003c\/p\u003e \u003cp\u003e2.6 Conclusion 41\u003c\/p\u003e \u003cp\u003e2.7 References 41\u003c\/p\u003e \u003cp\u003eExercise 2.1: Data Cleaning and Transformation 43\u003c\/p\u003e \u003cp\u003eExercise 2.2: Data Aggregation and Reduction 45\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Descriptive Analytics in Marketing 49\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 50\u003c\/p\u003e \u003cp\u003e3.2 Overview of Descriptive Analytics 51\u003c\/p\u003e \u003cp\u003e3.3 Descriptive Statistics for Marketing Data 52\u003c\/p\u003e \u003cp\u003e3.4 Data Visualization Techniques 56\u003c\/p\u003e \u003cp\u003e3.5 Exploratory Data Analysis in Marketing 60\u003c\/p\u003e \u003cp\u003e3.6 Analyzing Marketing Campaign Performance 65\u003c\/p\u003e \u003cp\u003e3.7 Practical Example: Descriptive Analytics for a Beverage Company’s Social Media Marketing Campaign 68\u003c\/p\u003e \u003cp\u003e3.8 Conclusion 70\u003c\/p\u003e \u003cp\u003e3.9 References 71\u003c\/p\u003e \u003cp\u003eExercise 3.1: Descriptive Analysis of Marketing Data 72\u003c\/p\u003e \u003cp\u003eExercise 3.2: Data Visualization and Interpretation 76\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Inferential Analytics and Hypothesis Testing 81\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 82\u003c\/p\u003e \u003cp\u003e4.2 Inferential Analytics in Marketing 82\u003c\/p\u003e \u003cp\u003e4.3 Confidence Intervals 92\u003c\/p\u003e \u003cp\u003e4.4 A\/B Testing in Marketing 95\u003c\/p\u003e \u003cp\u003e4.5 Hypothesis Testing in Marketing 101\u003c\/p\u003e \u003cp\u003e4.6 Customer Segmentation and Processing 106\u003c\/p\u003e \u003cp\u003e4.7 Practical Examples: Inferential Analytics for Customer Segmentation and Hypothesis Testing for Marketing Campaign Performance 115\u003c\/p\u003e \u003cp\u003e4.8 Conclusion 119\u003c\/p\u003e \u003cp\u003e4.9 References 120\u003c\/p\u003e \u003cp\u003eExercise 4.1: Bayesian Inference for Personalized Marketing 122\u003c\/p\u003e \u003cp\u003eExercise 4.2: A\/B Testing for Marketing Campaign Evaluation 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Predictive Analytics and Machine Learning 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 130\u003c\/p\u003e \u003cp\u003e5.2 Predictive Analytics Techniques 132\u003c\/p\u003e \u003cp\u003e5.3 Machine Learning Techniques 135\u003c\/p\u003e \u003cp\u003e5.4 Model Evaluation and Selection 144\u003c\/p\u003e \u003cp\u003e5.5 Churn Prediction, Customer Lifetime Value, and Propensity Modeling 150\u003c\/p\u003e \u003cp\u003e5.6 Market Basket Analysis and Recommender Systems 154\u003c\/p\u003e \u003cp\u003e5.7 Practical Examples: Predictive Analytics and Machine Learning in Marketing 158\u003c\/p\u003e \u003cp\u003e5.8 Conclusion 164\u003c\/p\u003e \u003cp\u003e5.9 References 165\u003c\/p\u003e \u003cp\u003eExercise 5.1: Churn Prediction Model 167\u003c\/p\u003e \u003cp\u003eExercise 5.2: Predict Weekly Sales 170\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Natural Language Processing in Marketing 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.0 Beginner-Friendly Introduction to Natural Language Processing in Marketing 174\u003c\/p\u003e \u003cp\u003e6.1 Introduction to Natural Language Processing 174\u003c\/p\u003e \u003cp\u003e6.2 Text Preprocessing and Feature Extraction in Marketing Natural Language Processing 178\u003c\/p\u003e \u003cp\u003e6.3 Key Natural Language Processing Techniques for Marketing 182\u003c\/p\u003e \u003cp\u003e6.4 Chatbots and Voice Assistants in Marketing 188\u003c\/p\u003e \u003cp\u003e6.5 Practical Examples of Natural Language Processing in Marketing 192\u003c\/p\u003e \u003cp\u003e6.6 Conclusion 196\u003c\/p\u003e \u003cp\u003e6.7 References 197\u003c\/p\u003e \u003cp\u003eExercise 6.1: Sentiment Analysis 199\u003c\/p\u003e \u003cp\u003eExercise 6.2: Text Classification 200                                                      \u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Social Media Analytics and Web Analytics 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 204\u003c\/p\u003e \u003cp\u003e7.2 Social Network Analysis 204\u003c\/p\u003e \u003cp\u003e7.3 Web Analytics Tools and Metrics 212\u003c\/p\u003e \u003cp\u003e7.4 Social Media Listening and Tracking 221\u003c\/p\u003e \u003cp\u003e7.5 Conversion Rate Optimization 227\u003c\/p\u003e \u003cp\u003e7.6 Conclusion 232\u003c\/p\u003e \u003cp\u003e7.7 References 233\u003c\/p\u003e \u003cp\u003eExercise 7.1: Social Network Analysis (SNA) in Marketing 235\u003c\/p\u003e \u003cp\u003eExercise 7.2: Web Analytics for Marketing Insights 238\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Marketing Mix Modeling and Attribution 243\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 244\u003c\/p\u003e \u003cp\u003e8.2 Marketing Mix Modeling Concepts 244\u003c\/p\u003e \u003cp\u003e8.3 Data-Driven Attribution Models 251\u003c\/p\u003e \u003cp\u003e8.4 Multi-Touch Attribution 256\u003c\/p\u003e \u003cp\u003e8.5 Return on Marketing Investment 261\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 266\u003c\/p\u003e \u003cp\u003e8.7 References 266\u003c\/p\u003e \u003cp\u003eExercise 8.1: Marketing Mix Modeling (MMM) 268\u003c\/p\u003e \u003cp\u003eExercise 8.2: Data- Driven Attribution 271\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Customer Journey Analytics 275\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 276\u003c\/p\u003e \u003cp\u003e9.2 Customer Journey Mapping 276\u003c\/p\u003e \u003cp\u003e9.3 Touchpoint Analysis 280\u003c\/p\u003e \u003cp\u003e9.4 Cross-Channel Marketing Optimization 286\u003c\/p\u003e \u003cp\u003e9.5 Path to Purchase and Attribution Analysis 291\u003c\/p\u003e \u003cp\u003e9.6 Conclusion 296\u003c\/p\u003e \u003cp\u003e9.7 References 296\u003c\/p\u003e \u003cp\u003eExercise 9.1: Creating a Customer Journey Map 298\u003c\/p\u003e \u003cp\u003eExercise 9.2: Touchpoint Effectiveness Analysis 301\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Experimental Design in Marketing 305\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 306\u003c\/p\u003e \u003cp\u003e10.2 Design of Experiments 306\u003c\/p\u003e \u003cp\u003e10.3 Fractional Factorial Designs 310\u003c\/p\u003e \u003cp\u003e10.4 Multi-Armed Bandits 315\u003c\/p\u003e \u003cp\u003e10.5 Online and Offline Experiments 320\u003c\/p\u003e \u003cp\u003e10.6 Conclusion 324\u003c\/p\u003e \u003cp\u003e10.7 References 325\u003c\/p\u003e \u003cp\u003eExercise 10.1: Analyzing a Simple A\/B Test 327\u003c\/p\u003e \u003cp\u003eExercise 10.2: Fractional Factorial Design in Ad Optimization 328\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Big Data Technologies and Real-Time Analytics 331\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 332\u003c\/p\u003e \u003cp\u003e11.2 Big Data 332\u003c\/p\u003e \u003cp\u003e11.3 Distributed Computing Frameworks 336\u003c\/p\u003e \u003cp\u003e11.4 Real-Time Analytics Tools and Techniques 343\u003c\/p\u003e \u003cp\u003e11.5 Personalization and Real-Time Marketing 348\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 353\u003c\/p\u003e \u003cp\u003e11.7 References 354\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Generative Artificial Intelligence and Its Applications in Marketing 357\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 358\u003c\/p\u003e \u003cp\u003e12.2 Understanding Generative Artificial Intelligence: Basics and Principles 359\u003c\/p\u003e \u003cp\u003e12.3 Implementing Generative Artificial Intelligence in Content Creation and Personalization 364\u003c\/p\u003e \u003cp\u003e12.4 Generative Artificial Intelligence in Predictive Analytics and Customer Behavior Modeling 367\u003c\/p\u003e \u003cp\u003e12.5 Ethical Considerations and Future Prospects of Generative Artificial Intelligence in Marketing 372\u003c\/p\u003e \u003cp\u003e12.6 Conclusion 375\u003c\/p\u003e \u003cp\u003e12.7 References 376\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Ethics, Privacy, and the Future of Marketing Data Science 379\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 380\u003c\/p\u003e \u003cp\u003e13.2 Ethical Considerations in Marketing Data Science 380\u003c\/p\u003e \u003cp\u003e13.3 Data Privacy Regulations 386\u003c\/p\u003e \u003cp\u003e13.4 Bias, Fairness, and Transparency 391\u003c\/p\u003e \u003cp\u003e13.5 Emerging Trends and the Future of Marketing Data Science 395\u003c\/p\u003e \u003cp\u003e13.6 Conclusion 399\u003c\/p\u003e \u003cp\u003e13.7 References 400\u003c\/p\u003e \u003cp\u003eAbout the Website 403\u003c\/p\u003e \u003cp\u003eIndex 405\u003c\/p\u003e \u003cp\u003e\u003cb\u003eDR IAIN BROWN, \u003c\/b\u003eis the Head of Data Science for Northern Europe at SAS Institute Inc. and Adjunct Professor of Marketing Data Science at the University of Southampton. With over a decade of experience spanning various sectors, he is a thought leader in Data Science, Marketing, AI, and Machine Learning.\u003cbr\u003eHis work has not only contributed to significant projects and innovations but also enriched the academic and professional communities through publications in prestigious journals and presentations at internationally renowned conferences.\u003c\/p\u003e  \u003cp\u003eIn the rapidly evolving landscape of marketing, the fusion of analytics and creativity has heralded a new era of data-driven strategies. \u003ci\u003eMastering Marketing Data Science: A Comprehensive Guide for Today’s Marketers \u003c\/i\u003estands at the forefront of this revolution, offering a comprehensive guide that bridges the gap between complex data science techniques and practical marketing applications. Authored by Dr. Iain Brown, a renowned expert in data science, this book distills over a decade of professional experience and academic insight into a pivotal resource for the modern marketer. \u003c\/p\u003e\u003cp\u003eThe journey begins with an exploration of the foundational elements of marketing data science, setting the stage for a deep dive into the methodologies that have transformed the marketing industry. From the intricacies of data collection and preparation to the advanced realms of predictive analytics, natural language processing, and beyond, Dr. Brown elucidates the core principles that underpin effective marketing strategies in the digital age. Each chapter is meticulously designed to not only impart theoretical knowledge but also to offer practical examples and exercises that enable readers to apply these insights in real-world scenarios. \u003c\/p\u003e\u003cp\u003eAs we traverse the landscape of marketing data science, the book unveils the latest advancements in the field, including cutting-edge discussions on generative AI and its implications for content creation, customer engagement, and ethical marketing practices. Dr. Brown's narrative is both enlightening and empowering, urging readers to leverage the power of data science to innovate, optimize, and excel in their marketing endeavors. \u003c\/p\u003e\u003cp\u003e\u003ci\u003eMastering Marketing Data Science \u003c\/i\u003eis not just a book; it’s a manifesto for the future of marketing. It challenges readers to rethink traditional paradigms and embrace the potential of data science to drive growth, engagement, and value in an increasingly competitive marketplace. Whether you’re a student, a marketing professional, or a data scientist looking to specialize in marketing, this book is your gateway to mastering the art and science of marketing in the digital era.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eUnveil the future of marketing with data science as your guide, transforming insights into action and theory into practice\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn an era where data reigns supreme, \u003ci\u003eMastering Marketing Data Science: A Comprehensive Guide for Today’s Marketers \u003c\/i\u003eemerges as the quintessential guide for navigating the complex terrain of digital marketing analytics. Authored by Dr. Iain Brown, a leader in the field of data science, this comprehensive tome is meticulously crafted for students, professionals, and data scientists eager to unlock the transformative power of data in marketing. Through a unique blend of theoretical insights and practical applications, Brown demystifies the science behind data-driven marketing strategies that resonate in today’s digital-first world.\u003c\/p\u003e \u003cp\u003eWith chapters that traverse from the fundamentals of marketing data science to the cutting edge of generative AI, this guide is replete with real-world examples, hands-on exercises, and actionable insights. Readers are equipped to master the art of data collection, analysis, and application, paving the way for innovative marketing solutions that captivate and convert. Whether it’s through predictive analytics, NLP, or customer journey analytics, Brown’s expertise illuminates the path to leveraging data for strategic advantage.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eMastering Marketing Data Science \u003c\/i\u003eis more than a book; it’s a roadmap to the future of marketing. Dr. Brown invites readers to embark on a journey of discovery and transformation, where data science becomes the cornerstone of marketing excellence. Prepare to be empowered with knowledge that not only enlightens but also enables the application of data science principles to real-world marketing challenges, driving unparalleled business value and innovation.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePraise for MASTERING MARKETING DATA SCIENCE\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\"This book is an indispensable resource for marketers seeking to harness the power of data science to drive innovation, enhance customer engagement, and achieve competitive advantage in today’s digital landscape. A must-read for both seasoned professionals and those aspiring to transform their marketing strategies through data science.\"\u003cbr\u003e—\u003cb\u003eBernard Marr,\u003c\/b\u003e Bestselling Author and International Keynote Speaker on Business and Technology\u003c\/p\u003e \u003cp\u003e\"This is an outstanding and timely book on \u003ci\u003eMastering Marketing Data Science\u003c\/i\u003e as it provides a unique blend of foundational as well as emerging topics.\"\u003cbr\u003e—\u003cb\u003eProf. dr. Bart Baesens,\u003c\/b\u003e Professor KU Leuven, Lecturer Southampton Business School\u003c\/p\u003e \u003cp\u003e\"\u003ci\u003eMastering Marketing Data Science\u003c\/i\u003e redefines the landscape of modern marketing, offering a compelling roadmap for harnessing the power of data science.\"\u003cbr\u003e—\u003cb\u003eProfessor Ganna Pogrebna,\u003c\/b\u003e Lead for Behavioural Data Science at the Alan Turing Institute (UK); Executive Director at AI and Cyber Futures Institute and Honorary Professor at the University of Sydney Business School (Australia)\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989581119717,"sku":"NP9781394258710","price":75.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781394258710.jpg?v=1761784683","url":"https:\/\/k12savings.com\/es\/products\/mastering-marketing-data-science-isbn-9781394258710","provider":"K12savings","version":"1.0","type":"link"}