Artificial intelligence for marketing practical applications
A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Art...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
Wiley
2017.
|
| Edición: | 1st edition |
| Colección: | THEi Wiley ebooks.
|
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630139706719 |
Tabla de Contenidos:
- 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.
