,Contents
1. Cover
2. Title Page
3. Foreword
4. Preface
1. AI IN A NUTSHELL
2. THIS IS YOUR MARKETING ON AI
5. Acknowledgments
6. CHAPTER 1: Welcome to the Future
1. WELCOME TO AUTONOMIC MARKETING
2. WELCOME TO ARTIFICIAL INTELLIGENCE FOR MARKETERS
3. WHOM IS THIS BOOK FOR?
4. THE BRIGHT, BRIGHT FUTURE
5. IS AI SO GREAT IF IT'S SO EXPENSIVE?
6. WHAT'S ALL THIS AI THEN?
7. THE AI UMBRELLA
8. THE MACHINE THAT LEARNS
9. ARE WE THERE YET?
10. AI‐POCALYPSE
11. MACHINE LEARNING'S BIGGEST ROADBLOCK
12. MACHINE LEARNING'S GREATEST ASSET
13. ARE WE REALLY CALCULABLE?
14. NOTES
7. CHAPTER 2: Introduction to Machine Learning
1. THREE REASONS DATA SCIENTISTS SHOULD READ THIS CHAPTER
2. EVERY REASON MARKETING PROFESSIONALS SHOULD READ THIS
CHAPTER
3. WE THINK WE'RE SO SMART
4. DEFINE YOUR TERMS
5. ALL MODELS ARE WRONG
6. USEFUL MODELS
7. TOO MUCH TO THINK ABOUT
8. MACHINES ARE BIG BABIES
9. WHERE MACHINES SHINE
10. STRONG VERSUS WEAK AI
11. THE RIGHT TOOL FOR THE RIGHT JOB
12. MAKE UP YOUR MIND
13. ONE ALGORITHM TO RULE THEM ALL?
14. ACCEPTING RANDOMNESS
15. WHICH TECH IS BEST?
16. FOR THE MORE STATISTICALLY MINDED
17. WHAT DID WE LEARN?
18. NOTES
8. CHAPTER 3: Solving the Marketing Problem
, 1. ONE‐TO‐ONE MARKETING
2. ONE‐TO‐MANY ADVERTISING
3. THE FOUR PS
4. WHAT KEEPS A MARKETING PROFESSIONAL AWAKE?
5. THE CUSTOMER JOURNEY
6. WE WILL NEVER REALLY KNOW
7. HOW DO I CONNECT? LET ME COUNT THE WAYS
8. WHY DO I CONNECT? BRANDING
9. MARKETING MIX MODELING
10. ECONOMETRICS
11. CUSTOMER LIFETIME VALUE
12. ONE‐TO‐ONE MARKETING—THE MEME
13. SEAT‐OF‐THE‐PANTS MARKETING
14. MARKETING IN A NUTSHELL
15. WHAT SEEMS TO BE THE PROBLEM?
16. NOTES
9. CHAPTER 4: Using AI to Get Their Attention
1. MARKET RESEARCH: WHOM ARE WE AFTER?
2. MARKETPLACE SEGMENTATION
3. RAISING AWARENESS
4. SOCIAL MEDIA ENGAGEMENT
5. IN REAL LIFE
6. THE B2B WORLD
7. NOTES
10. CHAPTER 5: Using AI to Persuade
1. THE IN‐STORE EXPERIENCE
2. ON THE PHONE
3. THE ONSITE EXPERIENCE—WEB ANALYTICS
4. MERCHANDISING
5. CLOSING THE DEAL
6. BACK TO THE BEGINNING: ATTRIBUTION
7. NOTES
11. CHAPTER 6: Using AI for Retention
1. GROWING CUSTOMER EXPECTATIONS
2. RETENTION AND CHURN
3. MANY UNHAPPY RETURNS
4. CUSTOMER SENTIMENT
5. CUSTOMER SERVICE
6. PREDICTIVE CUSTOMER SERVICE
7. NOTES
12. CHAPTER 7: The AI Marketing Platform
1. SUPPLEMENTAL AI
2. MARKETING TOOLS FROM SCRATCH
3. A WORD ABOUT WATSON
4. BUILDING YOUR OWN
5. NOTES
, 13. CHAPTER 8: Where Machines Fail
1. A HAMMER IS NOT A CARPENTER
2. MACHINE MISTAKES
3. HUMAN MISTAKES
4. THE ETHICS OF AI
5. SOLUTION?
6. WHAT MACHINES HAVEN'T LEARNED YET
7. NOTES
14. CHAPTER 9: Your Strategic Role in Onboarding AI
1. GETTING STARTED, LOOKING FORWARD
2. AI TO LEVERAGE HUMANS
3. COLLABORATION AT WORK
4. YOUR ROLE AS MANAGER
5. KNOW YOUR PLACE
6. AI FOR BEST PRACTICES
7. NOTES
15. CHAPTER 10: Mentoring the Machine
1. HOW TO TRAIN A DRAGON
2. WHAT PROBLEM ARE YOU TRYING TO SOLVE?
3. WHAT MAKES A GOOD HYPOTHESIS?
4. THE HUMAN ADVANTAGE
5. NOTES
16. CHAPTER 11: What Tomorrow May Bring
1. THE PATH TO THE FUTURE
2. MACHINE, TRAIN THYSELF
3. INTELLECTUAL CAPACITY AS A SERVICE
4. DATA AS A COMPETITIVE ADVANTAGE
5. HOW FAR WILL MACHINES GO?
6. YOUR BOT IS YOUR BRAND
7. MY AI WILL CALL YOUR AI
8. COMPUTING TOMORROW
9. NOTES
17. About the Author
18. Index
19. End User License Agreement
List of Tables
1. Chapter 4
1. Table 4.1 A spreadsheet was the start of database marketing
List of Illustrations
1. Chapter 1
1. Cover
2. Title Page
3. Foreword
4. Preface
1. AI IN A NUTSHELL
2. THIS IS YOUR MARKETING ON AI
5. Acknowledgments
6. CHAPTER 1: Welcome to the Future
1. WELCOME TO AUTONOMIC MARKETING
2. WELCOME TO ARTIFICIAL INTELLIGENCE FOR MARKETERS
3. WHOM IS THIS BOOK FOR?
4. THE BRIGHT, BRIGHT FUTURE
5. IS AI SO GREAT IF IT'S SO EXPENSIVE?
6. WHAT'S ALL THIS AI THEN?
7. THE AI UMBRELLA
8. THE MACHINE THAT LEARNS
9. ARE WE THERE YET?
10. AI‐POCALYPSE
11. MACHINE LEARNING'S BIGGEST ROADBLOCK
12. MACHINE LEARNING'S GREATEST ASSET
13. ARE WE REALLY CALCULABLE?
14. NOTES
7. CHAPTER 2: Introduction to Machine Learning
1. THREE REASONS DATA SCIENTISTS SHOULD READ THIS CHAPTER
2. EVERY REASON MARKETING PROFESSIONALS SHOULD READ THIS
CHAPTER
3. WE THINK WE'RE SO SMART
4. DEFINE YOUR TERMS
5. ALL MODELS ARE WRONG
6. USEFUL MODELS
7. TOO MUCH TO THINK ABOUT
8. MACHINES ARE BIG BABIES
9. WHERE MACHINES SHINE
10. STRONG VERSUS WEAK AI
11. THE RIGHT TOOL FOR THE RIGHT JOB
12. MAKE UP YOUR MIND
13. ONE ALGORITHM TO RULE THEM ALL?
14. ACCEPTING RANDOMNESS
15. WHICH TECH IS BEST?
16. FOR THE MORE STATISTICALLY MINDED
17. WHAT DID WE LEARN?
18. NOTES
8. CHAPTER 3: Solving the Marketing Problem
, 1. ONE‐TO‐ONE MARKETING
2. ONE‐TO‐MANY ADVERTISING
3. THE FOUR PS
4. WHAT KEEPS A MARKETING PROFESSIONAL AWAKE?
5. THE CUSTOMER JOURNEY
6. WE WILL NEVER REALLY KNOW
7. HOW DO I CONNECT? LET ME COUNT THE WAYS
8. WHY DO I CONNECT? BRANDING
9. MARKETING MIX MODELING
10. ECONOMETRICS
11. CUSTOMER LIFETIME VALUE
12. ONE‐TO‐ONE MARKETING—THE MEME
13. SEAT‐OF‐THE‐PANTS MARKETING
14. MARKETING IN A NUTSHELL
15. WHAT SEEMS TO BE THE PROBLEM?
16. NOTES
9. CHAPTER 4: Using AI to Get Their Attention
1. MARKET RESEARCH: WHOM ARE WE AFTER?
2. MARKETPLACE SEGMENTATION
3. RAISING AWARENESS
4. SOCIAL MEDIA ENGAGEMENT
5. IN REAL LIFE
6. THE B2B WORLD
7. NOTES
10. CHAPTER 5: Using AI to Persuade
1. THE IN‐STORE EXPERIENCE
2. ON THE PHONE
3. THE ONSITE EXPERIENCE—WEB ANALYTICS
4. MERCHANDISING
5. CLOSING THE DEAL
6. BACK TO THE BEGINNING: ATTRIBUTION
7. NOTES
11. CHAPTER 6: Using AI for Retention
1. GROWING CUSTOMER EXPECTATIONS
2. RETENTION AND CHURN
3. MANY UNHAPPY RETURNS
4. CUSTOMER SENTIMENT
5. CUSTOMER SERVICE
6. PREDICTIVE CUSTOMER SERVICE
7. NOTES
12. CHAPTER 7: The AI Marketing Platform
1. SUPPLEMENTAL AI
2. MARKETING TOOLS FROM SCRATCH
3. A WORD ABOUT WATSON
4. BUILDING YOUR OWN
5. NOTES
, 13. CHAPTER 8: Where Machines Fail
1. A HAMMER IS NOT A CARPENTER
2. MACHINE MISTAKES
3. HUMAN MISTAKES
4. THE ETHICS OF AI
5. SOLUTION?
6. WHAT MACHINES HAVEN'T LEARNED YET
7. NOTES
14. CHAPTER 9: Your Strategic Role in Onboarding AI
1. GETTING STARTED, LOOKING FORWARD
2. AI TO LEVERAGE HUMANS
3. COLLABORATION AT WORK
4. YOUR ROLE AS MANAGER
5. KNOW YOUR PLACE
6. AI FOR BEST PRACTICES
7. NOTES
15. CHAPTER 10: Mentoring the Machine
1. HOW TO TRAIN A DRAGON
2. WHAT PROBLEM ARE YOU TRYING TO SOLVE?
3. WHAT MAKES A GOOD HYPOTHESIS?
4. THE HUMAN ADVANTAGE
5. NOTES
16. CHAPTER 11: What Tomorrow May Bring
1. THE PATH TO THE FUTURE
2. MACHINE, TRAIN THYSELF
3. INTELLECTUAL CAPACITY AS A SERVICE
4. DATA AS A COMPETITIVE ADVANTAGE
5. HOW FAR WILL MACHINES GO?
6. YOUR BOT IS YOUR BRAND
7. MY AI WILL CALL YOUR AI
8. COMPUTING TOMORROW
9. NOTES
17. About the Author
18. Index
19. End User License Agreement
List of Tables
1. Chapter 4
1. Table 4.1 A spreadsheet was the start of database marketing
List of Illustrations
1. Chapter 1
