Make personalized marketing a reality with this practical guide to predictive analytics
Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience.
Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today.
- Implement predictive marketing at any size organization
- Deliver a more personalized marketing experience
- Automate predictive analytics with machine learning technology
- Base marketing decisions on concrete data rather than unproven ideas
Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.
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About the Author
ÖMER ARTUN, PHD is the founder and CEO of AgilOne. He aims to help marketers understand and predict customer behavior and make marketing personal again. He previously held executive roles in marketing at Best Buy, CDW and was a consultant with McKinsey & Company. He holds a PhD in Physics and Computational Neuroscience from Brown University.
DOMINIQUE LEVIN is a business and consumer marketing executive and an early adopter of data-driven marketing. Before building the marketing efforts of numerous startups, often from the ground up, she was an executive at Philips Consumer Electronics and Nippon Telegraph and Telephone. She holds an MBA with distinction from Harvard University.
Table of Contents
Introduction: Who Should Read This Book ix
PART 1 A Complete Predictive Marketing Primer 1
Chapter 1 Big Data and Predictive Analytics Are Now Easily Accessible to All Marketers 3
Chapter 2 An Easy Primer to Predictive Analytics for Marketers 23
Chapter 3 Get to Know Your Customers First: Build Complete Customer Profiles 43
Chapter 4 Managing Your Customers as a Portfolio to Improve Your Valuation 63
PART 2 Nine Easy Plays to Get Started with Predictive Marketing 75
Chapter 5 Play One: Optimize Your Marketing Spending Using Customer Data 77
Chapter 6 Play Two: Predict Customer Personas and Make Marketing Relevant Again 93
Chapter 7 Play Three: Predict the Customer Journey for Life Cycle Marketing 103
Chapter 8 Play Four: Predict Customer Value and Value-Based Marketing 115
Chapter 9 Play Five: Predict Likelihood to Buy or Engage to Rank Customers 123
Chapter 10 Play Six: Predict Individual Recommendations for Each Customer 137
Chapter 11 Play Seven: Launch Predictive Programs to Convert More Customers 145
Chapter 12 Play Eight: Launch Predictive Programs to Grow Customer Value 155
Chapter 13 Play Nine: Launch Predictive Programs to Retain More Customers 169
PART 3 How to Become a True Predictive Marketing Ninja 183
Chapter 14 An Easy-to-Use Checklist of Predictive Marketing Capabilities 185
Chapter 15 An Overview of Predictive (and Related) Marketing Technology 197
Chapter 16 Career Advice for Aspiring Predictive Marketers 209
Chapter 17 Privacy and the Difference Between Delightful and Invasive 215
Chapter 18 The Future of Predictive Marketing 221
Appendix: Overview of Customer Data Types 229