AI Marketing

How AI Is Transforming Marketing and Business Growth
1. Auflage 2025
ISBN: 978-1-041-03806-1
Verlag: CRC Press

Buch, Englisch, 240 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 449 g

This book explores the dynamic intersection of Artificial Intelligence (AI) technologies and marketing practices, offering a comprehensive guide to how AI is reshaping the way businesses connect with customers, optimize strategies, and drive sustainable growth. It presents an in-depth analysis of the latest AI applications in marketing, from personalized customer experiences to data-driven decision-making, predictive analytics, and intelligent automation.

Drawing on real-world examples and the latest research, the book examines key innovations such as AI-enhanced personalization, AI-driven content creation, campaign optimization, and the strategic use of predictive analytics. It highlights practical strategies for selecting and integrating AI tools effectively, addresses the ethical challenges surrounding AI use in marketing, and discusses future trends that will shape business success in the digital era.

AI Marketing is written for marketing professionals, business leaders, entrepreneurs, and students who want to stay ahead in a rapidly evolving field. It serves as an essential resource for anyone seeking to understand not just the potential of AI in marketing, but how to strategically apply it to achieve measurable results and long-term business growth.

Zielgruppe

Postgraduate, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Taherdoost, Hamed

Madanchian, Mitra

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Marketing

Inhaltsverzeichnis

Chapter 1. The Role of Machine Learning in Targeted Advertising

Mitra Madanchian, Hamed Taherdoost

Abstract
1.1. Introduction
1.2. Understanding Machine Learning in Advertising
1.3. Evolution of Ad Targeting
1.4. Key Applications of Machine Learning in Targeted Advertising
1.5. Benefits of Machine Learning in Advertising
1.6. Challenges and Ethical Considerations
1.7. Future Trends in Machine Learning for Advertising
1.8. Conclusion
Reference

Chapter 2. AI-Enhanced Personalisation: Crafting Tailored Experiences for Every Customer

A. GHAYATHRI, NIRMALA MOHAN

2.1. Introduction
2.2. Benefits of AI-Enhanced Personalisation  2.2.1. Enhanced Customer Engagement  2.2.2. Enhanced Conversion Rates  2.2.3. Enhanced Customer Retention  2.2.4. Enhanced Decision Support  2.2.5. Super Relevant Experiences  2.2.6. Saves Time & Lessens Overwhelm  2.2.7. More Engagement & Conversion  2.2.8. Smart Automation  2.2.9. Hyper-Personalized Communication  2.2.10. Continuous Learning
2.3. Objectives of The Study  2.3.1. To Analyse the Role of AI in Personalized Marketing  2.3.2. To Identify AI Techniques and Tools Enabling Personalization  2.3.3. To Assess the Impact of AI-Enhanced Personalization on Customer Engagement and Retention  2.3.4. To Understand the Challenges and Limitations of AI-Enhanced Personalization
2.4. Significance of The Study
2.5. Scope of The Study
2.6. Review of Literature
2.7. Research Methodology
2.8. Research Data
2.9. Sample Size
2.10. Sampling Technique
2.11. Statistical Tools
2.12. Hypothesis of The Study
2.13. Data Analysis and Interpretation
2.14. Findings of The Study
2.15. Suggestions from The Study  2.15.1. Real-Time AI-Powered Personalization by Customer Behaviour  2.15.2. Quantifying the Effect of AI Personalization: Cross-Channel Integration and Customer Journey Mapping  2.15.3. Determining Effective AI Customization Methods to Engage Consumers  2.15.4. Enforcing Ethical AI Practices in Order to Establish Consumer Trust  2.15.5. Prioritizing Privacy Compliance to Avoid Legal and Ethical Pitfalls
2.16. Conclusion
References

Chapter 3. Marketing-Finance Collaboration in the Age of AI: Toward a Reinvented Era Where Predictive Analysis in Cash Management Drives Marketing Performance

BADRANE NOHAYLA, BARZI GHIZLANE, BADRANE HASNAA

Abstract
3.1. Introduction
3.2. Objective and Methodology
3.3. Results Analysis  3.3.1. Evolution of the Relationship between Marketing and Finance: From Divergence to Convergence  3.3.2. When AI Redraws Modern Finance: A New Horizon for Cash Flow Management and Decision-Making  3.3.3. AI-Augmented Cash Management: Toward Intelligent and Proactive Financial Management  3.3.4. Marketing and Cash Management in the AI Era: A Reinvented Strategic Alliance
3.4. Discussion
3.5. Conclusion
References

Chapter 4. Data-Driven Decision-making and Predictive Analytics

Mostafa Ahmadi

Abstract
4.1. Introduction
4.2. Evolution of AI in Predictive Analytics  4.2.1. Growth of Data and Advanced Analytics
4.3. Rise of ML Algorithms
4.4. AI Applications in Marketing and Predictive Analytics  4.4.1. Customer Segmentation  4.4.2. Customer Behavior Prediction  4.4.3. Personalization and Campaign Optimization  4.4.4. Customer Relationship Enhancement
4.5. Dynamic Pricing Strategies  4.5.1. AI-driven Content Generation  4.5.2. Real-Time Sentiment Analysis  4.5.3. AI in Predictive Supply Chain Management  4.5.4. AI in Customer Retention Strategies
4.6. Ethical Considerations in AI-Driven Marketing  4.6.1. Privacy Concerns  4.6.2. Algorithmic Bias  4.6.3. Transparency and Explainability
4.7. Ethical Implications of Data Ownership
4.8. Consumer Trust and Brand Reputation
4.9. Future Developments in AI and Predictive Analytics  4.9.1. Generative AI in Marketing  4.9.2. Collaboration between Marketing and Technical Teams  4.9.3. Ethical AI Adoption  4.9.4. AI and Real-Time Decision Making  4.9.5. Future-Proofing Businesses through AI
4.10. Conclusion

Reference

Chapter 5. AI-Driven Finance Function and Marketing: A Close Partnership for Performance
Barzi Ghizlane, Badrane Nohayla, Badrane Hasnaa

Abstract

5.1. Introduction
5.2. Methodology
5.3. Results  5.3.1. Towards a More Agile, Automated, Intelligent, and Strategic Finance Function  5.3.2. Importance of Artificial Intelligence in Financial Activities  5.3.3. The Evolution of the Marketing Department in an Intelligent Environment  5.3.4. The Interaction Between the Financial Function and Marketing Through AI  5.3.5. Challenges and Issues of Artificial Intelligence in Financial and Marketing Activities
5.4. Discussion
5.5. Conclusion

Reference

Chapter 6. AI-Driven Content Creation and Curation
Mitra Madanchian, Alireza Rafiee, Hamed Taherdoost

Abstract
6.1. Introduction
6.2. AI-Powered Content Creation  6.2.1. AI-Generated Blogs and Articles  6.2.2. Product Descriptions and Marketing Content  6.2.3. AI in Video, Image, and Audio Content Generation
6.3. AI in Content Curation and Personalization
6.4. Enhancing Creativity and Efficiency with AI  6.4.1. AI-Assisted Brainstorming and Idea Generation  6.4.2. AI-Driven Content Optimization Tools  6.4.3. Automated A/B Testing for Marketing Content  6.4.4. Role of AI in Improving SEO and Content Discoverability
6.5. AI in Visual and Multimedia Content Marketing
6.6. Ethical and Legal Considerations in AI-Driven Content
6.7. AI and the Future of Content Marketing
6.8. Conclusion
References

Chapter 7. Optimizing Marketing Campaigns with AI Automation
T. Shirley Devakirubai

Abstract

7.1. Introduction
7.2. Review of Literature
7.3. Research Questions
7.4. Customer Profiling and Predictive Analysis in Targeted Marketing
7.5. Real-Time Data Analysis and Predictive Modelling in Effective Campaign Performance
7.6. Challenges in AI Marketing Campaigns
7.7. Conclusion

Reference

Chapter 8. Enhancing Customer Loyalty with AI Solutions
Mitra Madanchian, Alireza Rafiee

Abstract
8.1. Introduction
8.2. AI Technologies Powering Customer Loyalty
8.3. Personalization and Customer Engagement
8.4. Predictive Analytics for Customer Retention
8.5. Conversational AI and Customer Support
8.6. Ethical Considerations and Data Privacy
8.7. Future Trends and Strategic Implications
8.8. Conclusion

Reference

Chapter 9. Strategic Selection and Integration of AI Tools in Data-Driven Marketing
Mitra Madanchian, Hamed Taherdoost

Abstract
9.1. Introduction
9.2. Understanding Data-Driven Marketing
9.3. The Role of AI in Data-Driven Marketing
9.4. Criteria for Selecting AI Tools for Marketing
9.5. Data Infrastructure and Preparation
9.6. Developing a Data-Driven AI Marketing Strategy
9.7. Challenges and Considerations
9.8. Conclusion
Reference

Chapter 10. AI-Driven Marketing Strategies in the Digital Era
Jash Khatri, Hamed Taherdoost

Abstract
10.1. Introduction  10.1.1. Background  10.1.2. Problem Statement  10.1.3. Research Questions  10.1.4. Objectives  10.1.5. Scope
10.2. Defining Key Terms  10.2.1. Artificial Intelligence  10.2.2. Marketing
10.3. AI-Driven Marketing Strategies  10.3.1. Customer Segmentation and Targeting  10.3.2. Personalization, Automation, and Customer Experience
10.4. Challenges and Ethical Considerations  10.4.1. Real World Case: Target
10.5. Methodology
10.6. Analysis  10.6.1. AI-Driven Marketing Strategies  10.6.2. Challenges and Ethical Considerations
10.7. Discussion
10.8. Future Research
10.9. Conclusion
References

Über Autor(innen)

Dr. Hamed Taherdoost is an award-winning leader in research and development, known for his contributions across both industry and academia. He is the founder of Hamta Business Corporation, Associate Professor and Chair of RSAC at University Canada West, & Director of R&D at Q Minded Quark Minded Technology Inc. He has over 20 years of experience in both industry and academic sectors. He has worked at international companies from Cyprus, the UK, Malta, Iran, Malaysia, and Canada and has been highly involved in development of several projects in different industries, healthcare, transportation, residential, oil and gas and IT. Additionally, he has served as a trusted technical and technology consultant for multiple companies, providing advisory and mentorship.

In academia, Dr. Taherdoost has held teaching positions in Southeast Asia, the Middle East, Europe and North America since 2009. He began his academic career as a lecturer at AU & PNU and later served as an adjunct professor, dissertation chair and faculty fellow at Westcliff University, USA, & adjunct professor and thesis supervisor at Gisma University of Applied Sciences, Germany. His research tenure at IAU lasted over eight years, during which he supervised numerous students.

Dr. Taherdoost has a prolific publishing record, with over 350 scientific articles in top-tier journals and conference proceedings. His work is widely recognized, with a strong citation impact reflecting in a high h-index (>50), and his contributions span book chapters, edited volumes, and authored books focusing on technology and research methodology. His textbooks on E-Business and Digital Transformation are teaching at global institutions, including the University of Malta, Yarmouk University, University of Kerala, University of Macau, University Sains Islam Malaysia and University Canada West. His research accomplishments have earned him a place among the top 10 SSRN Business Authors from 2021 to 2024, as well as being featured in the Stanford-Elsevier list of the world's top 2% of Scientists in 2021, 2022 2023 and 2024.

Dr. Taherdoost has organized and chaired many workshops and conferences and has frequently been invited as a keynote speaker. He is an active member of the editorial, reviewer, and advisory boards for several prestigious journals published by Taylor & Francis. He has also participated as an organising, scientific and technical committee member in over 400 conferences held across Europe, America, Australia, Asia, and Africa.

Dr. Taherdoost's leadership and innovation have earned him numerous accolades, including THE BIZZ Business Excellence Award, PeerJ Award, and recognition at the Asia Corporate Excellence & Sustainability Awards. He was a finalist for the Innovation in Teaching of Research Methodology Excellence Awards and Southeast Asian Startup Awards by Global Startup Awards. Additionally, his research achievements also include winning several best paper awards, outstanding reviewer awards and best presentation awards like MLIS awards, CSA award, CSTFM Lecture award, the Outstanding Editorial Board Member award from Bilingual Publishing, Best Paper of the Year of Computers MDPI, Editor's Choice Articles of Algorithm Journal, and Best Interview Award of Encyclopedia.

Dr. Taherdoost is the Editor of a book series with Routledge (Taylor & Francis Group) titled Mastering Academic Excellence: Research, Teaching, Learning, and Publishing & Editor of a book series entitled “Quantum Computing”.

He is a Certified Cyber Security Professional and Certified Graduate Technologist. He is a GUS Fellow - GUS Institute Global University Systems, senior member of IEEE, and Working Group Member of International Federation for Information Processing - IFIP TC 11 - Human Aspects of Information Security and Assurance and Information Security Management. Currently, he is involved in several multidisciplinary research projects, including studying innovation in information technology, blockchain, cybersecurity, and technology acceptance.

Dr. Mitra Madanchian is a distinguished scholar, strategic leader, and industry expert with deep expertise in business management, leadership, human resources, and technology-driven innovation. She currently serves as Assistant Professor at University Canada West (UCW), where she is also the Vice Chair of the Department of Arts, Communications, and Social Sciences in the School of Arts, Science, and Technology. In addition, she holds an Adjunct Professorship at Fairleigh Dickinson University.

Dr. Madanchian is also an accomplished entrepreneur and R&D strategist, serving as Director of Quark Minded Technology Inc. and Hamta Business Corporation, where she leads initiatives focused on applied research and strategic innovation.

She holds a Ph.D. in Business Management and a Master of Administrative Science in Human Resources, with over 15 years of industry experience, including leadership roles in SMEs and one of the Big Four firms, KPMG. Her work bridges theory and practice in areas such as business strategy, HR development, marketing, and organizational innovation.

As a prolific academic, Dr. Madanchian has authored over 80 high-impact, peer-reviewed publications across top-tier journals published by Elsevier, Springer, IGI Global, and MDPI. She has also contributed to multiple book chapters and authored five books in the areas of leadership, and human resource management. Her interdisciplinary research spans business management, human resources, marketing, IT management, and emerging leadership models, earning her a strong citation record and h-index that reflect her influence within the global academic community.

Her recent research focuses on the integration of artificial intelligence (AI) in HR and marketing, exploring how digital tools are reshaping the future of workforce engagement and customer experience. She is a regular speaker and session chair at international conferences, an active member of the Chartered Professionals in Human Resources (CPHR), and a mentor to emerging scholars.