{"product_id":"ai-for-marketing-and-product-innovation-9781119484066","title":"AI for Marketing and Product Innovation","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\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","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407064113495,"sku":"9781119484066","price":999.99,"currency_code":"GBP","in_stock":false}],"url":"https:\/\/bookcurl.com\/products\/ai-for-marketing-and-product-innovation-9781119484066","provider":"Book Curl","version":"1.0","type":"link"}