Building AI Driven Marketing Capabilities : Understand Customer Needs and Deliver Value Through AI

This book provides insight into technologies that offer competitive advantage in marketing. These technologies can help us with describing and predicting customer behavior with the help of analytics, designing of radical products, creating of meaningful value, optimization of distribution, informing and promoting solutions, and making marketing more effective overall by aligning marketing with business goals. A range of technologies, such as analytics, big data, artificial intelligence, IoT, machine learning are expected to transform future businesses. Understanding customer needs, matching them to solutions and delivering value can all be dramatically optimized with the help of technology. Businesses need to realize that AI has already made inroads in marketing and can be expected to wield its influence across functional areas in the foreseeable future. The business world is headed towards acceptance of technology to synthesize knowledge by interpreting diverse information and facilitating decision making. This book is an attempt to reflect deployment of technologies across businesses and sectors. As the functional discipline comes together, harnessing a gamut of technologies becomes indispensable to deliver a superior customer experience and driving profits. Marketers should thus adopt the concepts of openness, convergence, and creation of value through new emerging technologies. A resultant hyper connected market will thus have to adopt innovative changes in its existing processes and services. The proposed book offers its readers an insight into technological interventions in various aspects of marketing domain. From understanding various technologies as an enabler to marketing efforts and its impact on decision making and mapping of various facets of customer experience, this book is recommended for marketers and learners to understand the advantages of using technology. What You Will Learn The developments and applications of Artificial Intelligence in marketing The precise, practical framework necessary to discover, utilize, and embrace AI potential to optimize the outcomes for company growth Automation and optimization of media planning through AI Who This Book is For The book is designed for marketers, academicians, business professionals, data scientists, practitioners, and researchers. Contents About the Editors Chapter 1: Using Social Media for Improving Customer Engagement Introduction Important Social Media Platforms Important Studies on Social Media and Customer Engagement Impact of Social Media on Customer Engagement Advantage of Social Media Strategies for Customer Engagement Disadvantages of Social Media Strategies for Customer Engagement Social Media Engagement vs. Mainstream Media Engagement Innovative Technologies and AI in Social Media Personalization Frequently Used Online Tools for Customer Engagement Indian Companies Using Social Media Platforms for Better Customer Engagement Conclusion Chapter 2: Applying AI for Product Life Cycle Management Introduction Recent Trends in Product Life Cycle Management AI: What Is It? Product Life Cycle Management The Product Life Cycle Management Stages AI in PLCM AI in Product Design AI in the Production of Goods AI in Goods and Service Sales Building Smart Supply Chains Conclusion Chapter 3: Empowering Customer Experience with AI Tools and Technologies Introduction Customer Interaction and AI Technologies Empowering Customer Experience Significant Applications of Artificial Intelligence (AI) for Marketing Artificial Intelligence Tools Used for Engaging Customers Real-World Examples AI and Personalization AI and Hassle-Free Service AI and Service Quality Challenges Managerial Implications Conclusion Chapter 4: Interactive Fashion Textiles: Marketing New Technologies to Target Tech-Savvy Millennials Introduction Detection of Defects Pattern Inspection Color-Related Issues Garment Construction Defects Computer-Aided Design (CAD) Systems Production Scheduling and Flow Management Final Inspection Interactive Fashion Textiles New Earth-Friendly Textiles Rethinking “End-to-End” Design to Achieve Circularity Case Study Background Conclusion Chapter 5: AI-Based Decisive Model for Customer Segmentation in the Fashion Industry Introduction Fuzzy Logic History of Fuzzy Logic Fuzzy Set Theory The Essential Particulars of Fuzzy Logic Applications of Fuzzy Logic Design of the Model with Fuzzy Logic Fuzzy Logic Inference Mechanism The Fuzzy Inference System: Essential Decision-Making Component in Fuzzy Logic Step 1: Fuzzification Linear Membership Functions Nonlinear membership functions Singleton Membership Functions Step 2: Designing Rule Base Mamdani Systems Sugeno Systems Tsukamoto Models Step 3: Rule Evaluation Utilization of Fuzzy Operators in the Antecedent Deriving Consequences from Antecedent Aggregation of the Consequences Across the Rules Step 4: Defuzzification Maximum Membership Principle Centroid Method Weighted Average Method Mean-Max Method (Middle of Maxima) Design and Implementation of the System Fuzzification Rule Base Defuzzification Graphical User Interface Results Limitations of Fuzzy Logic Control Conclusion Chapter 6: Analyzing Customer Satisfaction of Hotel Booking Applications: A Sentimental Analysis Approach Introduction Overview of the Hotel Industry Related Work Research Methodology Empirical Result and Analysis Conclusion Chapter 7: Internet Trends and Customer Sentiment Analysis on Different Online Platforms Introduction Research Methodology Indian Websites for Online Shopping CSS: Contextual Semantic Search Applications: Business Intelligence Sentiment Analysis Sentiment analysis is Being Used by Businesses to Enhance Customer Experience Brand Sentiment Analysis Competitor Analysis Customer Sentiment Analysis by Different Online Platforms Sentiment Trend Chart Conclusion Chapter 8: Role of Artificial Intelligence for Value Chain Creation in Healthcare Marketing Introduction AI at a Glance History of AI in Healthcare System AI in Value Chain of a Healthcare Industry AI in Healthcare Wearables Health Tech Wearable Devices Robotic Surgery AI in Manufacturing and Development of Pharmaceuticals Marketing Techniques and Current State 2022–2023 Marketing Value Forecast Due to AI Integration in the Medical Industry Challenges Faced Due to Machine Learning Integration with Healthcare System Conclusion Chapter 9: Potential Roles of Cyber-Ethical Awareness, Artificial Intelligence, and Chatbot Technologies Among Students Introduction Literature Review Cyber-Ethics Plagiarism Chatbot Technologies Chatbot Technologies and Academic Integrity Factors Influencing Plagiarism in Chatbot Technology Use Prevalence of Plagiarism Among Nigerian Undergraduate Students The Relationship Between Cyber-Ethical Awareness and Plagiarism Cyber-Ethical Awareness Among Nigerian Undergraduate Students The Role of Cyber-Ethical Awareness in Reducing Plagiarism Strategies to Promote Cyber-Ethical Awareness Theoretical Framework: Deontological Theory of Ethics Recommendations Future Research Area Conclusion Chapter 10: Content Generated by Netflix: Scoping Review and Analysis Introduction Netflix Content Trend Shift from TV to Web Series Netflix (Demand and Subscription) Literature Review Social Media Twitter Netflix on Twitter Purpose Content Analysis Sentiment Analysis Thematic Analysis Research Methodology: Data Collection Result and Discussion: Gathering Information Content Analysis TFA (Term Frequency Analysis) Sentiment Analysis Thematic Analysis Limitations Conclusion Chapter 11: Unveiling AI’s Ethical Impact in Marketing Through Social Media’s Darker Influence Introduction Defining Artificial Intelligence How Morality and Ethics Relate to Artificial Intelligence Ethics in Artificial Intelligence Tort Law and Marketing AI Literature Review Significance of AI in Marketing Theoretical Background on Artificial Intelligence in Marketing Ethical Concerns of AI in Marketing Uncovering the Negative Impact of AI on Social Media Applying AI Education on Social Media Platforms to Exert Influence Ethical Implications Of AI in Marketing Importance of Responsible AI Practices Findings of the Study Specific Challenges in Social Media Marketing Need for Responsible and Ethical Practices Promoting Awareness of Ethical Concerns Implications for AI in Marketing Recommendations for Responsible AI Practices Future Directions for Research Conclusion Chapter 12: Strategic Insights Through Customer Value Modeling: Unveiling the Key Drivers of Customer Success Introduction Literature Drivers of Customer Success Methodology Discussion and Results Insights and Recommendations Conclusion Chapter 13: Exploration of Artificial Intelligence (AI) in Banking Sector: A Bibliometric Analysis Introduction Methodology Analysis: Description of Literature Published Annual Scientific Production Triple Analysis Thematic Map Analysis Most Relevant Sources Word Cloud Most Relevant Sources Conclusion Chapter 14: Developing a Marketing Strategy While Maintaining Focus on Customer Value Introduction Value for the Customer and Why It Matters Customer Value Determinants How to Develop a Strategy for Marketing That Is Centered on the Customer Marketing Approaches That Continue to Prioritize the Needs of the Consumer Value They Are Targeting Conclusion Chapter 15: Boom of Artificial Intelligence in the Food Industry Introduction Use of AI in the Food Sector Expert System Based on Knowledge in the Food Industry The Use of Fuzzy Logic in the Food Industry Methods of Learning Through Machine Learning (ML) Food Manufacturing: ANN Technique AI-Based Compensation Within the Food Manufacturing Sector Emerging AI Implementation Ideas in the Food Manufacturing Sector Conclusion Chapter 16: Unlocking Emotional Intelligence with AI Marketing: Connecting Brands to Hearts Defining Emotional Intelligence in the Context of Marketing Emotional Intelligence and Consumer Behavior The Impact of Technology and AI The Significance of Emotional Connections Between Brands and Consumers Impact on Consumer Decision-Making Understanding Consumer Emotions with AI Utilizing AI to Gather and Analyze Emotional Data from Various Sources Sentiment Analysis and Its Applications in Understanding Consumer Sentiment Natural Language Processing (NLP) for Deciphering Emotions from Customer Interactions Case Studies and Examples of Successful Emotional Data Analysis Case Study 1: Coca-Cola’s “Share a Coke” Campaign Case Study 2: Spotify’s “Wrapped” Campaign Case Study 3: Nike’s “Dream Crazy” Ad Case Study 4: Airbnb’s “Belong Anywhere” Campaign Case Study 5: Always’ “#LikeAGirl” Campaign Case Study 6: Google’s “Year in Search” Videos Case Study 7: Dove’s “Real Beauty” Campaign AI-Driven Personalization for Emotional Resonance Leveraging AI Algorithms to Match Emotional Triggers with Individual Consumers The Potential of AI in Emotional Personalization Balancing Personalization and Privacy Concerns The Risk of Emotional Manipulation Emotional Storytelling Through AI-Generated Content The Fusion of AI Visual Recognition and Emotional Branding: A Critical Examination Case Studies of Emotionally Driven Brand Visuals and Their Effectiveness: A Critical Examination Case Study 1: Apple’s “Shot on iPhone” Campaign Case Study 2: Dove’s “Real Beauty” Campaign Case Study 3: Nike’s “Just Do It” Campaign with Colin Kaepernick Developing AI-Powered Metrics for Emotional Engagement: A Critical Examination Assessing the ROI of Emotionally Driven Marketing Campaigns: A Critical Examination Integrating Emotional Metrics with Traditional Performance Indicators: A Critical Examination The Ethical Implications of Using AI for Emotional Engagement: A Critical Examination Conclusion Emphasizing the Transformative Potential of AI in Connecting Brands to Hearts: A Critical Examination Striking the Balance Between Technology and Human Emotions: A Critical Conclusion Conclusion References Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Chapter 15 Chapter 16 Index