Details

AI for Marketing and Product Innovation

Powerful New Tools for Predicting Trends, Connecting with Customers, and Closing Sales
1. Aufl.

von: A. K. Pradeep, Andrew Appel, Stan Sthanunathan
18,99 €
Verlag:	Wiley
Format:	PDF
Veröffentl.:	26.11.2018
ISBN/EAN:	9781119484080
Sprache:	englisch
Anzahl Seiten:	272

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Beschreibungen

Titelbeschreibung

Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. <ul> <li>Understand AI and ML technology in layman’s terms</li> <li>Harness the twin technologies unparalleled power to transform marketing</li> <li>Learn which skills and resources you need to use AI and ML effectively</li> </ul> <ul> <li>Employ AI and ML in ways that resonate meaningfully with customers</li> <li>Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI</li> </ul> Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.

Inhaltsverzeichnis

Preface xiii Acknowledgments xvii Introduction xix 1 Major Challenges Facing Marketers Today 1 Living in the Age of the Algorithm 3 2 Introductory Concepts for Artificial Intelligence and Machine Learning for Marketing 7 Concept 1: Rule-based Systems 8 Concept 2: Inference Engines 10 Concept 3: Heuristics 11 Concept 4: Hierarchical Learning 12 Concept 5: Expert Systems 14 Concept 6: Big Data 16 Concept 7: Data Cleansing 18 Concept 8: Filling Gaps in Data 19 Concept 9: A Fast Snapshot of Machine Learning 19 Areas of Opportunity for Machine Learning 22 3 Predicting Using Big Data – Intuition Behind Neural Networks and Deep Learning 29 Intuition Behind Neural Networks and Deep Learning Algorithms 29 Let It Go: How Google Showed Us That Knowing How to Do It Is Easier Than Knowing How You Know It 37 4 Segmenting Customers and Markets – Intuition Behind Clustering, Classification, and Language Analysis 45 Intuition Behind Clustering and Classification Algorithms 45 Intuition Behind Forecasting and Prediction Algorithms 54 Intuition Behind Natural Language Processing Algorithms and Word2Vec 61 Intuition Behind Data and Normalization Methods 70 5 Identifying What Matters Most – Intuition Behind Principal Components, Factors, and Optimization 77 Principal Component Analysis and Its Applications 78 Intuition Behind Rule-based and Fuzzy Inference Engines 83 Intuition Behind Genetic Algorithms and Optimization 87 Intuition Behind Programming Tools 92 6 Core Algorithms of Artificial Intelligence and Machine Learning Relevant for Marketing 99 Supervised Learning 100 Unsupervised Learning 102 Reinforcement Learning 105 7 Marketing and Innovation Data Sources and Cleanup of Data 107 Data Sources 108 Workarounds to Get the Job Done 112 Cleaning Up Missing or Dummy Data 113 8 Applications for Product Innovation 119 Inputs and Data for Product Innovation 120 Analytical Tools for Product Innovation 122 Step 1: Identify Metaphors – The Language of the Non-conscious Mind 123 Step 2: Separate Dominant, Emergent, Fading, and Past Codes from Metaphors 124 Step 3: Identify Product Contexts in the Non-conscious Mind 125 Step 4: Algorithmically Parse Non-conscious Contexts to Extract Concepts 126 Step 5: Generate Millions of Product Concept Ideas Based on Combinations 126 Step 6: Validate and Prioritize Product Concepts Based on Conscious Consumer Data 127 Step 7: Create Algorithmic Feature and Bundling Options 128 Step 8: Category Extensions and Adjacency Expansion 129 Step 9: Premiumize and Luxury Extension Identification 130 9 Applications for Pricing Dynamics 131 Key Inputs and Data for Machine-based Pricing Analysis 132 A Control Th eoretic Approach to Dynamic Pricing 135 Rule-based Heuristics Engine for Price Modifi cations 136 10 Applications for Promotions and Offers 139 Timing of a Promotion 141 Templates of Promotion and Real Time Optimization 143 Convert Free to Paying, Upgrade, Upsell 144 Language and Neurological Codes 145 Promotions Driven by Loyalty Card Data 147 Personality Extraction from Loyalty Data – Expanded Use 148 Charity and the Inverse Hierarchy of Needs from Loyalty Data 149 Planogram and Store Brand, and Store-Within-a-Store Launch from Loyalty Data 150 Switching Algorithms 151 11 Applications for Customer Segmentation 153 Inputs and Data for Segmentation 154 Analytical Tools for Segmentation 156 12 Applications for Brand Development, Tracking, and Naming 161 Brand Personality 162 Machine-based Brand Tracking and Correlation to Performance 169 Machine-based Brand Leadership Assessment 170 Machine-based Brand Celebrity Spokesperson Selection 171 Machine-based Mergers and Acquisitions Portfolio Creation 172 Machine-based Product Name Creation 173 13 Applications for Creative Storytelling and Advertising 177 Compression of Time – The Real Budget Savings 178 Weighing the Worth of Programmatic Buying 183 Neuroscience Rule-based Expert Systems for Copy Testing 185 Capitalizing on Fading Fads and Micro Trends That Appear and Then Disappear 188 Capitalizing on Past Trends and Blasts from the Past 189 RFP Response and B2B Blending News and Trends with Stories 189 Sales and Relationship Management 190 Programmatic Creative Storytelling 191 14 The Future of AI-enabled Marketing, and Planning for It 193 What Does This Mean for Strategy? 194 What to Do In-house and What to Outsource 195 What Kind of Partnerships and the Shifting Landscapes 195 What Are Implications for Hiring and Talent Retention, and HR? 196 What Does Human Supervision Mean in the Age of the Algorithm and Machine Learning? 199 How to Question the Algorithm and Know When to Pull the Plug 200 Next Generation of Marketers – Who Are They, and How to Spot Them 201 How Budgets and Planning Will Change 201 15 Next-Generation Creative and Research Agency Models 203 What Does an ML- and AI-enabled Market Research or Marketing Services Agency Look Like? 206 What an ML- and AI-enabled Research Agency or Marketing Services Company Can Do That Traditional Agencies Cannot Do 207 The New Nature of Partnership 208 Is There a Role for a CES or Cannes-like Event for AI and ML Algorithms and Artificial Intelligence Programs? 209 Challenges and Solutions 210 Big Data 215 AI- and ML-powered Strategic Development 215 Creative Execution 217 Beam Me Up 218 Will Retail Be a Remnant? 219 Getting Real 220 It Begins – and Ends – with an “A” Word 221 About the Authors 225 Index 229

Autorenportrait

DR. A.K. PRADEEP is the Founder/CEO of machineVantage, a startup applying AI and Machine Learning to some of the most challenging marketing problems. Dr. Pradeep's clients during his career have ranged from Unilever to Coca-Cola, Nissan, Google, Facebook, Mondelez, Pepsi-Cola, Clorox, and dozens more. He is the author of The Buying Brain, also from Wiley. ANDREW APPEL is President and CEO of IRI, a global leader in technology solutions and services for consumer, retail and media companies and was previously a McKinsey senior partner. IRI works with some of the world's leading brands, retailers and media organizations including Anheuser-Busch InBev, Conagra, PepsiCo, Kroger, Costco and Walgreens as well as Google, Facebook and OmniCom Group, among other global companies. STAN STHANUNATHAN is the Global EVP of Consumer and Market Insights for Unilever, one of the world's largest and most successful consumer packaged goods companies.

Back cover copy

PRAISE FOR AI FOR MARKETING AND PRODUCT INNOVATION "The world of consumer marketing has never been more exciting than it is today. This book provides a solid framework for understanding how Artificial Intelligence illuminates consumer attitudes and preferences. It's a must-read for someone who wants to future proof their marketing career." —Keith Weed, Chief Marketing and Communications Officer Unilever Plc "It surprises people to learn that emotion and experience play a big part in the home improvement field, but they do. Machine learning, Artificial intelligence, and Metaphors help us to capture that emotional mind of the consumer. This book is full of innovative, and practical ways to accomplish that." —Prat Vemana, Chief Product and Customer Experience Officer, Home Depot "The new era we live in requires companies to work from the costumer to the company and not the other way around (as it has commonly been). AI helps decode customer interests, needs, motivations across cultures, habits and needs. This book is packed with innovative ideas and techniques to help do just that." —Carlos Slim, Mexican Business Magnate and Philanthropist "Brand and Retail marketing today is data intensive. ??Understanding the data, and extracting meaningful insights from it, requires not just algorithms and math, but a deep understanding of the mechanisms of motivation. This book contains numerous techniques that are both pragmatic, and innovative." —Professor Rajiv Lal, Harvard Business School "AI for Marketing and Product Information demonstrates how advertisers and agencies can harness data, analytics and speed to inform and align strategies to win with customers — and do it quickly!" —Irwin Gotlieb, former Chairman of GroupM "Successful brand marketing in today's culture means being able to detect and anticipate trends as early as possible. Artificial intelligence systems that are tailored for marketing, and especially for product innovation, are emerging to become key tools we need. This book digs deep into that." —Jim Scholefield, CIO Merck "Gaining a better understanding of how to develop innovative products and market them with meaningful messaging is a major challenge and always a top corporate priority. I found this to be a truly illuminating guidebook on how to use AI and machine learning for those purposes." —Raja Rajamannar, Chief Marketing & Communications Officer and President, Healthcare Business, Mastercard "Fashion defies prediction, but cost-effective delivery requires it. Applying AI to get at the non-conscious drivers that impact consumers gives companies like ours a competitive advantage. Reading this book is the first step to getting there." —Stef Strack, CEO Rag & Bone, New York "Now brands and retailers can think like a customer versus just thinking about the customer AI for Marketing and Product Innovation arms leaders with the information they need for applying artificial intelligence and machine learning to win in today's digital era." —Kevin Turner, CEO of Core Scientific, and Vice Chairman, Albertsons Companies, LLC.?? Former COO, Microsoft