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AI for marketing and product innovation: powerful new tools for predicting trends, connecting with customers, and closing sales
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Bibliographic Details
Main Authors: Pradeep, A. K. 1963- (Author), Appel, Andrew (Author), Sthanunathan, Stan (Author)
Format: Electronic eBook
Language:English
Published: Hoboken, New Jersey Wiley [2019]
Subjects:
Maschinelles Lernen
Künstliche Intelligenz
Technische Innovation
Marketing
Datenverarbeitung
Links:https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=5612944
http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030771158&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Item Description: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
Chapter 6: Core Algorithms of Artificial Intelligence and Machine Learning Relevant for Marketing -- Supervised Learning -- Unsupervised Learning -- Association -- Clustering -- Dimensionality Reduction -- Reinforcement Learning -- Chapter 7: Marketing and Innovation Data Sources and Cleanup of Data -- Data Sources -- Workarounds to Get the Job Done -- Cleaning Up Missing or Dummy Data -- Completing Consumer Purchase Data -- Filling In Geospatial Data -- Normalizing Temporal Scales Across Data -- Eliminating Seasonality from Data -- Normalizing Data Across Different Ranges -- Detecting Anomalies and Outliers -- Integrating Qualitative and Quantitative Data -- Weather and Environmental Data -- Chapter 8: Applications for Product Innovation -- Inputs and Data for Product Innovation -- Analytical Tools for Product Innovation -- Step 1: Identify Metaphors - The Language of the Non-conscious Mind -- Step 2: Separate Dominant, Emergent, Fading, and Past Codes from Metaphors -- Step 3: Identify Product Contexts in the Non-conscious Mind -- Step 4: Algorithmically Parse Non-conscious Contexts to Extract Concepts -- Step 5: Generate Millions of Product Concept Ideas Based on Combinations -- Step 6: Validate and Prioritize Product Concepts Based on Conscious Consumer Data -- Step 7: Create Algorithmic Feature and Bundling Options -- Step 8: Category Extensions and Adjacency Expansion -- Step 9: Premiumize and Luxury Extension Identification -- Chapter 9: Applications for Pricing Dynamics -- Key Inputs and Data for Machine-based Pricing Analysis -- A Control Theoretic Approach to Dynamic Pricing -- Rule-based Heuristics Engine for Price Modifications -- Chapter 10: Applications for Promotions and Offers -- Timing of a Promotion -- Templates of Promotion and Real Time Optimization -- Convert Free to Paying, Upgrade, Upsell -- Language and Neurological Codes
Promotions Driven by Loyalty Card Data -- Personality Extraction from Loyalty Data - Expanded Use -- Charity and the Inverse Hierarchy of Needs from Loyalty Data -- Planogram and Store Brand, and Store-Within-a-Store Launch from Loyalty Data -- Switching Algorithms -- Chapter 11: Applications for Customer Segmentation -- Inputs and Data for Segmentation -- Analytical Tools for Segmentation -- Step 1 : PCA and Clustering Techniques -- Step 2 : Metaphor-based Segmentation -- Step 3 : Algorithmic Facet-based Segmentation -- Step 4 : Segment Fusion Based on Plurality of Approaches -- Step 5 : Segment-specific Offerings -- Chapter 12: Applications for Brand Development, Tracking, and Naming -- Brand Personality -- Brand Personality Type 1: New Experiences and Openness -- Brand Personality Type 2: Orderly Progression and Conscientiousness -- Brand Personality Type 3: Positivity, Talkability, and Extraversion -- Brand Personality Type 4: Collaboration, Harmony, and Agreeableness -- Brand Personality Type 5: Emotional Volatility and Neuroticism -- Machine-based Brand Tracking and Correlation to Performance -- Machine-based Brand Leadership Assessment -- Machine-based Brand Celebrity Spokesperson Selection -- Machine-based Mergers and Acquisitions Portfolio Creation -- Machine-based Product Name Creation -- Chapter 13: Applications for Creative Storytelling and Advertising -- Compression of Time - The Real Budget Savings -- Template for Constructing a 30-Second Ad -- Template for Constructing a 15-Second Ad -- Template for Constructing an 8-Second Ad -- Template for Constructing a 5-Second Ad -- Template and Components for Constructing a Print Ad -- Template and Components for Constructing an Internet Banner Ad -- Template and Components for Retail POS -- Weighing the Worth of Programmatic Buying -- Programmatic Advertising Purchase Logic
Template and Components for Meme Construction -- Neuroscience Rule-based Expert Systems for Copy Testing -- Capitalizing on Fading Fads and Micro Trends That Appear and Then Disappear -- Capitalizing on Past Trends and Blasts from the Past -- RFP Response and B2B Blending News and Trends with Stories -- Sales and Relationship Management -- Programmatic Creative Storytelling -- Template for Programmatic Storytelling -- Chapter 14: The Future of AI-enabled Marketing, and Planning for It -- What Does This Mean for Strategy? -- What to Do In-house and What to Outsource -- What Kind of Partnerships and the Shifting Landscapes -- What Are Implications for Hiring and Talent Retention, and HR? -- What Does Human Supervision Mean in the Age of the Algorithm and Machine Learning? -- How to Question the Algorithm and Know When to Pull the Plug -- Next Generation of Marketers - Who Are They, and How to Spot Them -- How Budgets and Planning Will Change -- Chapter 15: Next-Generation Creative and Research Agency Models -- What Does an ML- and AI-enabled Market Research or Marketing Services Agency Look Like? -- What an ML- and AI-enabled Research Agency or Marketing Services Company Can Do That Traditional Agencies Cannot Do -- The New Nature of Partnership -- Is There a Role for a CES or Cannes-like Event for AI and ML Algorithms and Artificial Intelligence Programs? -- Challenges and Solutions -- Big Data -- AI- and ML-powered Strategic Development -- Creative Execution -- Beam Me Up -- Will Retail Be a Remnant? -- Getting Real -- It Begins - and Ends - with an "A" Word -- About the Authors -- A.K. Pradeep -- Andrew Appel -- Stan Sthanunathan -- Index -- EULA.
Physical Description:1 Online-Ressource (xxiv, 240 Seiten)
ISBN:9781119484080

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