{"product_id":"ai-for-marketing-and-product-innovation-isbn-9781119484066","title":"AI for Marketing and Product Innovation","description":"\u003cp\u003e\u003cb\u003eGet on board the next massive marketing revolution\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAI for Marketing and Product Innovation\u003c\/i\u003e 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. \u003c\/p\u003e \u003cp\u003eMore 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUnderstand AI and ML technology in layman’s terms\u003c\/li\u003e \u003cli\u003eHarness the twin technologies unparalleled power to transform marketing\u003c\/li\u003e \u003cli\u003eLearn which skills and resources you need to use AI and ML effectively\u003c\/li\u003e \u003c\/ul\u003e \u003cul\u003e \u003cli\u003eEmploy AI and ML in ways that resonate meaningfully with customers\u003c\/li\u003e \u003cli\u003eLearn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eDiscover 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. \u003ci\u003eAI for Marketing and Product Innovation\u003c\/i\u003e shows you everything you need to know to get on board.\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003eIntroduction xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Major Challenges Facing Marketers Today 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eLiving in the Age of the Algorithm 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Introductory Concepts for Artificial Intelligence and Machine Learning for Marketing 7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eConcept 1: Rule-based Systems 8\u003c\/p\u003e \u003cp\u003eConcept 2: Inference Engines 10\u003c\/p\u003e \u003cp\u003eConcept 3: Heuristics 11\u003c\/p\u003e \u003cp\u003eConcept 4: Hierarchical Learning 12\u003c\/p\u003e \u003cp\u003eConcept 5: Expert Systems 14\u003c\/p\u003e \u003cp\u003eConcept 6: Big Data 16\u003c\/p\u003e \u003cp\u003eConcept 7: Data Cleansing 18\u003c\/p\u003e \u003cp\u003eConcept 8: Filling Gaps in Data 19\u003c\/p\u003e \u003cp\u003eConcept 9: A Fast Snapshot of Machine Learning 19\u003c\/p\u003e \u003cp\u003eAreas of Opportunity for Machine Learning 22\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Predicting Using Big Data – Intuition Behind Neural Networks and Deep Learning 29\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntuition Behind Neural Networks and Deep Learning Algorithms 29\u003c\/p\u003e \u003cp\u003eLet It Go: How Google Showed Us That Knowing How to Do It Is Easier Than Knowing How You Know It 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Segmenting Customers and Markets – Intuition Behind Clustering, Classification, and Language Analysis 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntuition Behind Clustering and Classification Algorithms 45\u003c\/p\u003e \u003cp\u003eIntuition Behind Forecasting and Prediction Algorithms 54\u003c\/p\u003e \u003cp\u003eIntuition Behind Natural Language Processing Algorithms and Word2Vec 61\u003c\/p\u003e \u003cp\u003eIntuition Behind Data and Normalization Methods 70\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Identifying What Matters Most – Intuition Behind Principal Components, Factors, and Optimization 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003ePrincipal Component Analysis and Its Applications 78\u003c\/p\u003e \u003cp\u003eIntuition Behind Rule-based and Fuzzy Inference Engines 83\u003c\/p\u003e \u003cp\u003eIntuition Behind Genetic Algorithms and Optimization 87\u003c\/p\u003e \u003cp\u003eIntuition Behind Programming Tools 92\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Core Algorithms of Artificial Intelligence and Machine Learning Relevant for Marketing 99\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSupervised Learning 100\u003c\/p\u003e \u003cp\u003eUnsupervised Learning 102\u003c\/p\u003e \u003cp\u003eReinforcement Learning 105\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Marketing and Innovation Data Sources and Cleanup of Data 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eData Sources 108\u003c\/p\u003e \u003cp\u003eWorkarounds to Get the Job Done 112\u003c\/p\u003e \u003cp\u003eCleaning Up Missing or Dummy Data 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Applications for Product Innovation 119\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInputs and Data for Product Innovation 120\u003c\/p\u003e \u003cp\u003eAnalytical Tools for Product Innovation 122\u003c\/p\u003e \u003cp\u003eStep 1: Identify Metaphors – The Language of the Non-conscious Mind 123\u003c\/p\u003e \u003cp\u003eStep 2: Separate Dominant, Emergent, Fading, and Past Codes from Metaphors 124\u003c\/p\u003e \u003cp\u003eStep 3: Identify Product Contexts in the Non-conscious Mind 125\u003c\/p\u003e \u003cp\u003eStep 4: Algorithmically Parse Non-conscious Contexts to Extract Concepts 126\u003c\/p\u003e \u003cp\u003eStep 5: Generate Millions of Product Concept Ideas Based on Combinations 126\u003c\/p\u003e \u003cp\u003eStep 6: Validate and Prioritize Product Concepts Based on Conscious Consumer Data 127\u003c\/p\u003e \u003cp\u003eStep 7: Create Algorithmic Feature and Bundling Options 128\u003c\/p\u003e \u003cp\u003eStep 8: Category Extensions and Adjacency Expansion 129\u003c\/p\u003e \u003cp\u003eStep 9: Premiumize and Luxury Extension Identification 130\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Applications for Pricing Dynamics 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eKey Inputs and Data for Machine-based Pricing Analysis 132\u003c\/p\u003e \u003cp\u003eA Control Th eoretic Approach to Dynamic Pricing 135\u003c\/p\u003e \u003cp\u003eRule-based Heuristics Engine for Price Modifi cations 136\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Applications for Promotions and Offers 139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTiming of a Promotion 141\u003c\/p\u003e \u003cp\u003eTemplates of Promotion and Real Time Optimization 143\u003c\/p\u003e \u003cp\u003eConvert Free to Paying, Upgrade, Upsell 144\u003c\/p\u003e \u003cp\u003eLanguage and Neurological Codes 145\u003c\/p\u003e \u003cp\u003ePromotions Driven by Loyalty Card Data 147\u003c\/p\u003e \u003cp\u003ePersonality Extraction from Loyalty Data – Expanded Use 148\u003c\/p\u003e \u003cp\u003eCharity and the Inverse Hierarchy of Needs from Loyalty Data 149\u003c\/p\u003e \u003cp\u003ePlanogram and Store Brand, and Store-Within-a-Store Launch from Loyalty Data 150\u003c\/p\u003e \u003cp\u003eSwitching Algorithms 151\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Applications for Customer Segmentation 153\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInputs and Data for Segmentation 154\u003c\/p\u003e \u003cp\u003eAnalytical Tools for Segmentation 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Applications for Brand Development, Tracking, and Naming 161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBrand Personality 162\u003c\/p\u003e \u003cp\u003eMachine-based Brand Tracking and Correlation to Performance 169\u003c\/p\u003e \u003cp\u003eMachine-based Brand Leadership Assessment 170\u003c\/p\u003e \u003cp\u003eMachine-based Brand Celebrity Spokesperson Selection 171\u003c\/p\u003e \u003cp\u003eMachine-based Mergers and Acquisitions Portfolio Creation 172\u003c\/p\u003e \u003cp\u003eMachine-based Product Name Creation 173\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Applications for Creative Storytelling and Advertising 177\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCompression of Time – The Real Budget Savings 178\u003c\/p\u003e \u003cp\u003eWeighing the Worth of Programmatic Buying 183\u003c\/p\u003e \u003cp\u003eNeuroscience Rule-based Expert Systems for Copy Testing 185\u003c\/p\u003e \u003cp\u003eCapitalizing on Fading Fads and Micro Trends That Appear and Then Disappear 188\u003c\/p\u003e \u003cp\u003eCapitalizing on Past Trends and Blasts from the Past 189\u003c\/p\u003e \u003cp\u003eRFP Response and B2B Blending News and Trends with Stories 189\u003c\/p\u003e \u003cp\u003eSales and Relationship Management 190\u003c\/p\u003e \u003cp\u003eProgrammatic Creative Storytelling 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 The Future of AI-enabled Marketing, and Planning for It 193\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Does This Mean for Strategy? 194\u003c\/p\u003e \u003cp\u003eWhat to Do In-house and What to Outsource 195\u003c\/p\u003e \u003cp\u003eWhat Kind of Partnerships and the Shifting Landscapes 195\u003c\/p\u003e \u003cp\u003eWhat Are Implications for Hiring and Talent Retention, and HR? 196\u003c\/p\u003e \u003cp\u003eWhat Does Human Supervision Mean in the Age of the Algorithm and Machine Learning? 199\u003c\/p\u003e \u003cp\u003eHow to Question the Algorithm and Know When to Pull the Plug 200\u003c\/p\u003e \u003cp\u003eNext Generation of Marketers – Who Are They, and How to Spot Them 201\u003c\/p\u003e \u003cp\u003eHow Budgets and Planning Will Change 201\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Next-Generation Creative and Research Agency Models 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Does an ML- and AI-enabled Market Research or Marketing Services Agency Look Like? 206\u003c\/p\u003e \u003cp\u003eWhat an ML- and AI-enabled Research Agency or Marketing Services Company Can Do That\u003c\/p\u003e \u003cp\u003eTraditional Agencies Cannot Do 207\u003c\/p\u003e \u003cp\u003eThe New Nature of Partnership 208\u003c\/p\u003e \u003cp\u003eIs There a Role for a CES or Cannes-like Event for AI and ML Algorithms and Artificial Intelligence Programs? 209\u003c\/p\u003e \u003cp\u003eChallenges and Solutions 210\u003c\/p\u003e \u003cp\u003eBig Data 215\u003c\/p\u003e \u003cp\u003eAI- and ML-powered Strategic Development 215\u003c\/p\u003e \u003cp\u003eCreative Execution 217\u003c\/p\u003e \u003cp\u003eBeam Me Up 218\u003c\/p\u003e \u003cp\u003eWill Retail Be a Remnant? 219\u003c\/p\u003e \u003cp\u003eGetting Real 220\u003c\/p\u003e \u003cp\u003eIt Begins – and Ends – with an “A” Word 221\u003c\/p\u003e \u003cp\u003eAbout the Authors 225\u003c\/p\u003e \u003cp\u003eIndex 229\u003c\/p\u003e \t\t \u003cp\u003e\u003cb\u003eD\u003csmall\u003eR\u003c\/small\u003e. A.K. PRADEEP\u003c\/b\u003e 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 \u003ci\u003eThe Buying Brain\u003c\/i\u003e, also from Wiley.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eANDREW APPEL\u003c\/b\u003e 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.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSTAN STHANUNATHAN\u003c\/b\u003e is the Global EVP of Consumer and Market Insights for Unilever, one of the world's largest and most successful consumer packaged goods companies.\t   \u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eAI\u003c\/i\u003e\u003c\/b\u003e \u003ci\u003efor Marketing and Product Innovation\u003c\/i\u003e offers product innovators, creative talent and marketing professionals a hands-on and highly accessible guide to artificial intelligence (AI) and machine learning (ML). The authors (a team of experts at the intersection of neuroscience, technology, insights, and marketing) reveal how to harness AI and ML to accelerate product innovation and marketing. These two powerful new tools stand poised to revolutionize the way we sell products and make innovative breakthroughs. \u003c\/p\u003e\u003cp\u003eThis vital resource explores a wide range of business-related topics, from innovation, branding, pricing and promotions, creative storytelling to the future of market research and advertising agencies. All the techniques presented in the book have become algorithms and serve as real-life examples of AI and ML at work. In addition, the authors outline the resources, the skills, best practices, terminology, and metrics required to harness the unparalleled and rapidly expanding power of these twin technologies. \u003ci\u003eAI for Marketing and Product Innovation\u003c\/i\u003e provides an in-depth look at what AI is, what it can—and cannot—do, and contains practical ideas and insights on ways in which to apply that knowledge to your business and career development. \u003c\/p\u003e\u003cp\u003eThroughout the book, the authors neither resort to mathematical mumbo-jumbo nor do they present an endless array of irrelevant case studies. Instead, they challenge us to \"Think Different.\" \u003ci\u003eAI for Marketing and Product Innovation\u003c\/i\u003e is filled with the information needed to understand the practical business implications of Artificial Intelligence and Machine Learning. In clear terms, the book shows how to put them to work to gain a competitive advantage in today's increasingly digitally-driven economy.\t   \u003c\/p\u003e\u003cp\u003e\u003cb\u003ePRAISE FOR\u003c\/b\u003e \u003cb\u003eAI \u003csmall\u003eFOR\u003c\/small\u003e MARKETING \u003csmall\u003eAND\u003c\/small\u003e PRODUCT INNOVATION\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Keith Weed,\u003c\/b\u003e Chief Marketing and Communications Officer Unilever Plc  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Prat Vemana,\u003c\/b\u003e Chief Product and Customer Experience Officer, Home Depot  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Carlos Slim,\u003c\/b\u003e Mexican Business Magnate and Philanthropist  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Professor Rajiv Lal,\u003c\/b\u003e Harvard Business School  \u003c\/p\u003e\u003cp\u003e\"\u003ci\u003eAI for Marketing and Product Information\u003c\/i\u003e demonstrates how advertisers and agencies can harness data, analytics and speed to inform and align strategies to win with customers — and do it quickly!\" \u003cb\u003e—Irwin Gotlieb,\u003c\/b\u003e former Chairman of GroupM  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Jim Scholefield,\u003c\/b\u003e CIO Merck  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Raja Rajamannar,\u003c\/b\u003e Chief Marketing \u0026amp; Communications Officer and President, Healthcare Business, Mastercard  \u003c\/p\u003e\u003cp\u003e\"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.\" \u003cb\u003e—Stef Strack,\u003c\/b\u003e CEO Rag \u0026amp; Bone, New York  \u003c\/p\u003e\u003cp\u003e\"Now brands and retailers can think \u003ci\u003elike\u003c\/i\u003e a customer versus just thinking \u003ci\u003eabout\u003c\/i\u003e the customer \u003ci\u003eAI for Marketing and Product Innovation\u003c\/i\u003e arms leaders with the information they need for applying artificial intelligence and machine learning to win in today's digital era.\" \u003cb\u003e—Kevin Turner,\u003c\/b\u003e CEO of Core Scientific, and Vice Chairman, Albertsons Companies, LLC.?? 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