AI for marketing and product innovation : powerful new tools for predicting trends, connecting with customers, and closing sales

Intro -- AI For Marketing and Product Innovation -- Contents -- Preface -- Acknowledgments -- Introduction -- Chapter 1: Major Challenges Facing Marketers Today -- Living in the Age of the Algorithm -- Chapter 2: Introductory Concepts for Artificial Intelligence and Machine Learning for Marketing -- Concept 1: Rule-based Systems -- Concept 2: Inference Engines -- Concept 3: Heuristics -- Concept 4: Hierarchical Learning -- Concept 5: Expert Systems -- Concept 6: Big Data -- Concept 7: Data Cleansing -- Concept 8: Filling Gaps in Data -- Concept 9: A Fast Snapshot of Machine Learning -- Areas of Opportunity for Machine Learning -- Application 1: Localization and Local Brands -- Application 2: Value and Rationalization of Social Media Cost -- Application 3: Rationalization of Advertising Cost -- Application 4: Merging of Innovation and Marketing and R&D -- Application 5: Co-creation -- Chapter 3: Predicting Using Big Data - Intuition Behind Neural Networks and Deep Learning -- Intuition Behind Neural Networks and Deep Learning Algorithms -- Let It Go: How Google Showed Us That Knowing How to Do It Is Easier Than Knowing How You Know It -- Chapter 4: Segmenting Customers and Markets - Intuition Behind Clustering, Classification, and Language Analysis -- Intuition Behind Clustering and Classification Algorithms -- Intuition Behind Forecasting and Prediction Algorithms -- Intuition Behind Natural Language Processing Algorithms and Word2Vec -- Intuition Behind Data and Normalization Methods -- Chapter 5: Identifying What Matters Most - Intuition Behind Principal Components, Factors, and Optimization -- Principal Component Analysis and Its Applications -- Intuition Behind Rule-based and Fuzzy Inference Engines -- Intuition Behind Genetic Algorithms and Optimization -- Intuition Behind Programming Tools