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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.





Understand AI and ML technology in layman's terms

Harness the twin technologies unparalleled power to transform marketing

Learn which skills and resources you need to use AI and ML effectively






Employ AI and ML in ways that resonate meaningfully with customers

Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI



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.

AI for Marketing and Product Innovation: Powerful New Tools for Predicting Trends, Connecting with Customers, and Closing Sales

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