Produktbild: Artificial Intelligence for Marketing

Artificial Intelligence for Marketing Practical Applications

Aus der Reihe SAS Institute Inc

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.10.2017

Verlag

John Wiley & Sons Inc

Seitenzahl

368

Maße (L/B/H)

23,5/15,7/2,4 cm

Gewicht

544 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-40633-4

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.10.2017

Verlag

John Wiley & Sons Inc

Seitenzahl

368

Maße (L/B/H)

23,5/15,7/2,4 cm

Gewicht

544 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-40633-4

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Artificial Intelligence for Marketing
  • Foreword by Davenport
     
    Preface
     
    Acknowledgments
     
    Chapter 1: Welcome to the Future
     
    Welcome to Autonomic Marketing
     
    Welcome to Artificial Intelligence for Marketers
     
    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
     
    Are We There Yet?
     
    AI-Pocalypse
     
    Machine Learning's Biggest Roadblock
     
    Machine Learning's Greatest Asset
     
    Are We Really Calculable?
     
    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
     
    Strong versus Weak AI
     
    The Right Tool for the Right Job
     
    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?
     
    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
     
    Market Mix Modeling (MMM)
     
    Econometrics
     
    Customer Lifetime Value
     
    One-to-One Marketing--The MemeSeat-of the-Pants Marketing
     
    Marketing in a Nutshell
     
    What Seems to Be the Problem?
     
    Chapter 4: Using AI to Get Their Attention
     
    Market Research: Whom Are We After?
     
    Marketplace Segmentation
     
    Raising Awareness
     
    Social Media Engagement
     
    In Real Life
     
    The B2B World
     
    Chapter 5: Using AI to Persuade
     
    The In-store Experience
     
    The On-site Experience--Web Analytics
     
    Merchandising
     
    Closing the Deal
     
    Back to the Beginning: Attribution
     
    Chapter 6: Using AI for Retention
     
    Growing Customer Expectations
     
    Retention and Churn
     
    Many Unhappy Returns
     
    Voice of the Customer
     
    Customer Service
     
    Predictive Customer Service
     
    Chapter 7: The AI Marketing Platform
     
    Supplemental AI
     
    Marketing Tools from Scratch
     
    A Word about Watson
     
    Building Your Own
     
    Chapter 8: Where Machines Fail
     
    A Hammer Is Not a Carpenter
     
    Machine Mistakes
     
    Human Mistakes
     
    The Ethics of AI
     
    Solution?
     
    What Machines Haven't Learned Yet
     
    Chapter 9: Your Strategic Role Onboarding AI
     
    Getting Started, Looking Forward
     
    AI to Leverage Humans
     
    Collaboration at Work
     
    Your Role as Manager
     
    Know Your Place
     
    AI for Best Practices
     
    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
     
    Chapter 11: What Tomorrow May Bring
     
    The Path to the Future
     
    Machine, Train Thyself
     
    Intellectual Capacity as a Service
     
    Data as a Competitive Advantage
     
    How Far Will Machines Go?
     
    Your Bot Is Your Brand
     
    My AI Will Ca