Artificial Intelligence for Marketing: Practical Applications

Cover -- Title Page -- Copyright -- Contents -- Foreword -- Preface -- Acknowledgments -- Chapter 1: Welcome to the Future -- Welcome to Autonomic Marketing -- Welcome to Artificial Intelligence for Marketers -- Detect -- Decide -- Develop -- Whom Is This Book For? -- The Bright, Bright Future -- Is AI So Great if It's So Expensive? -- What's All This AI Then? -- The AI Umbrella -- The Machine that Learns -- Guess the Animal -- The Machine that Programs Itself -- Are We There Yet? -- AI-pocalypse -- The AI that Ate the Earth -- Intentional Consequences Problem -- Unintended Consequences -- Will a Robot Take Your Job? -- Machine Learning's Biggest Roadblock -- Machine Learning's Greatest Asset -- How We Used to Dive into Data -- Variety of Data Is the Spice of Life -- Open Data -- Data for Sale -- But Wait-There's More -- A Collaboration of Datasets -- A Customer Data Taxonomy -- Are We Really Calculable? -- Notes -- Chapter 2: Introduction to Machine Learning -- Three Reasons Data Scientists Should Read This Chapter -- Every Reason Marketing Professionals Should Read This Chapter -- We Think We're So Smart -- Define Your Terms -- All Models Are Wrong -- Useful Models -- Too Much to Think About -- Machines Are Big Babies -- Where Machines Shine -- High Cardinality -- High Dimensionality -- Strong versus Weak AI -- The Right Tool for the Right Job -- Classification versus Regression -- Supervised Machine Learning -- Unsupervised Learning -- Neural Networks -- Reinforcement Learning -- Make Up Your Mind -- One Algorithm to Rule Them All? -- Accepting Randomness -- Which Tech Is Best? -- For the More Statistically Minded -- What Did We Learn? -- Notes -- Chapter 3: Solving the Marketing Problem -- One-to-One Marketing -- One-to-Many Advertising -- The Four Ps

What Keeps a Marketing Professional Awake? -- The Customer Journey -- We Will Never Really Know -- How Do I Connect? Let Me Count the Ways -- Why Do I Connect? Branding -- Marketing Mix Modeling -- Econometrics -- Customer Lifetime Value -- One-to-One Marketing-The Meme -- Seat-of-the-Pants Marketing -- Marketing in a Nutshell -- What Seems to Be the Problem? -- Notes -- Chapter 4: Using AI to Get Their Attention -- Market Research: Whom Are We After? -- Machine Learning in Market Research -- Marketplace Segmentation -- Social Media Monitoring -- Competitive Analysis -- Raising Awareness -- Public Relations -- Direct Response -- Database Marketing -- Advertising -- Pay-per-Click (PPC) Search -- Search Optimization (aka Content Marketing) -- Social Media Engagement -- Social Snooping -- Socialbots -- Social Posting -- In Real Life -- The B2B World -- Lead Scoring -- Sales Management Advisory -- DIY-Some Models Are Useful -- Notes -- Chapter 5: Using AI to Persuade -- The In-Store Experience -- Shopping Assistance -- Restaurants -- Store Operations -- On the Phone -- The Onsite Experience-Web Analytics -- Landing Page Optimization -- A/B and Multivariate Testing -- Onsite User Experience -- Recommendation Engines -- Personalization -- Merchandising -- Pricing -- Market Basket Analysis -- Closing the Deal -- Remarketing -- E-mail Marketing -- Back to the Beginning: Attribution -- Notes -- Chapter 6: Using AI for Retention -- Growing Customer Expectations -- Retention and Churn -- Many Unhappy Returns -- Customer Sentiment -- Customer Service -- Call Center Support -- Bots -- Predictive Customer Service -- Notes -- Chapter 7: The AI Marketing Platform -- Supplemental AI -- Salesforce -- Adobe -- Marketing Tools from Scratch -- Communicating Insightsâ€"Narratives from Data -- Customer Journey Journal -- Recommender in Chief

Build a Whole Website -- A Word about Watson -- Hey, Check This Out -- That Was Easy -- Lucy-Watson's Progeny -- Better Together -- Building Your Own -- Notes -- Chapter 8: Where Machines Fail -- A Hammer Is Not a Carpenter -- Target-A Cautionary Tale -- Machine Mistakes -- Data Is Difficult -- Just Following Orders -- Human Mistakes -- Unintended Consequences -- Optimizing the Wrong Thing -- Correlation Is Not Causation -- The Ethics of AI -- Privacy -- Follow Your Heart -- Intentional Manipulation -- Trumped-Up Charges? -- Unintended Bias -- Solution? -- What Machines Haven't Learned Yet -- Notes -- Chapter 9: Your Strategic Role in Onboarding AI -- Getting Started, Looking Forward -- Testing the Waters versus Boiling the Ocean -- Automate These Processes First -- How Much Should You Spend? -- AI to Leverage Humans -- Collaboration at Work -- Your Role as Manager -- Working with Data Scientists -- Taking the Right Steps -- Expressing the Value of Marketing -- Know Your Place -- AI for Best Practices -- Notes -- Chapter 10: Mentoring the Machine -- How to Train a Dragon -- What Problem Are You Trying to Solve? -- What Makes a Good Hypothesis? -- The Human Advantage -- Judgment -- Imagination -- Empathy -- Trust Your Gut -- The Smell Test -- Notes -- Chapter 11: What Tomorrow May Bring -- The Path to the Future -- Machine, Train Thyself -- Intellectual Capacity as a Service -- Conscience Support System -- What If We're All Just as Smart? -- Data as a Competitive Advantage -- Data as a Business -- Data as a Sideline -- Insight Automation -- How Far Will Machines Go? -- Like a Boss -- Pretending to Be a Human -- Beyond Human -- Your Bot Is Your Brand -- My AI Will Call Your AI -- Your Personal AI Ecosystem -- Your Personal Shopper -- Computing Tomorrow -- Notes -- About the Author -- Index -- EULA

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