Prelims
ISBN: 978-1-83549-002-0, eISBN: 978-1-83549-001-3
Publication date: 11 November 2024
Citation
(2024), "Prelims", Dadwal, S.S., Jahankhani, H. and Revett, K. (Ed.) Market Grooming, Emerald Publishing Limited, Leeds, pp. i-xxxiv. https://doi.org/10.1108/978-1-83549-001-320241014
Publisher
:Emerald Publishing Limited
Copyright © 2025 Sumesh Singh Dadwal, Hamid Jahankhani and Kenneth Revett. Published under exclusive licence by Emerald Publishing Limited
Half Title Page
Market Grooming
Editorial Advisory Board
Dr Farooq Habib
Cranfield University, UK, farooqhabib1969@gmail.com
Dr Wilson Ozuem
Associate Professor in Management, Anglia Ruskin University, UK, Wilson.Ozuem@aru.ac.uk
Dr Bilan Sahidi
University of Sunderland in London, UK, Sahidi.Bilan@sunderland.ac.uk
Dr Zhewen Tang
Northumbria University London, UK, zhewen.tang@northumbria.ac.uk
List of Reviewers
Dr Gordon Bowen
Anglia Ruskin University, UK, gordon.bowen@aru.ac.uk
Dr Sonal Jain
Northumbria University London, UK, sonal3.jain@northumbria.ac.uk
Dr Pawan Kumar
LPU, India, pawan.19867@lpu.co.in
Dr Vipin Nadda
University of Sunderland in London, UK, vipin.nadda@sunderland.ac.uk
Dr Imad Nawaz
Northumbria University London, UK, Archana.shankar@northumbria.ac.uk
Dr Archana Shankar
Northumbria University London, UK
Title Page
Market Grooming: The Dark Side of AI Marketing
Edited by
Sumesh Singh Dadwal
London South Bank University, UK
Hamid Jahankhani
Northumbria University London, UK
And
Kenneth Revett
Champlain College, USA
United Kingdom – North America – Japan – India – Malaysia – China
Copyright Page
Emerald Publishing, Floor 5, Northspring, 21-23 Wellington Street, Leeds LS1 4DL
First edition 2025
Editorial matter and selection © 2025 Sumesh Singh Dadwal, Hamid Jahankhani and Kenneth Revett.
Individual chapters © 2025 The authors.
Published under exclusive licence by Emerald Publishing Limited.
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A catalogue record for this book is available from the British Library
ISBN: 978-1-83549-002-0 (Print)
ISBN: 978-1-83549-001-3 (Online)
ISBN: 978-1-83549-003-7 (Epub)
List of Figures and Tables
| Figures | ||
| Fig. 1.1. | Concept of Market Grooming. | 6 |
| Fig. 1.2. | Sales Funnel of Market Grooming vs Political or Radical Grooming. | 7 |
| Fig. 1.3. | Sales Flywheel Strategic Model. | 8 |
| Fig. 3.1. | Patient Grooming Framework. | 69 |
| Fig. 4.1. | Dark Side of ChatGPT Integration With Marketing 5.0. | 87 |
| Fig. 5.1. | Gender vs Department. | 106 |
| Fig. 5.2. | Gender vs Previous Year Rating. | 106 |
| Fig. 5.3. | Gender vs Awards Won. | 107 |
| Fig. 5.4. | Correlation Matrix. | 108 |
| Fig. 5.5. | Model Bias Analysis. | 109 |
| Fig. 6.1. | An Overview of Machine Learning. | 122 |
| Fig. 6.2. | A Classification Task of the Neural Network. | 129 |
| Fig. 6.3. | The Elbow Method. | 130 |
| Fig. 6.4. | K- Clusters. | 130 |
| Fig. 7.1. | Branches of AI. | 141 |
| Fig. 9.1. | AI & Digital Marketing in Consumer Behaviour. | 176 |
| Fig. 10.1. | Correlation Matrix Between Continuous Variables. | 211 |
| Fig. 10.2. | Boxplot Distribution of Highest Correlated Parameters. | 212 |
| Fig. 10.3. | Regression Analyses in Total Score Vs Talent & Total Score Vs Infrastructure. | 213 |
| Fig. 10.4. | Average Total Score by Region and Average Total by Cluster. | 213 |
| Fig. 10.5. | Average Total Vs Political Regime and Average Total Score Vs Income Group. | 213 |
| Fig. 10.6. | Pair Plot of Indicators. | 214 |
| Fig. 10.7. | Assessing Assumptions of the Regression Model, Linearity, Homoscedasticity and Normality. | 215 |
| Fig. 10.8. | Features Importance Proportion of Categorial Variables in Descending Order that Influence Overall AI Index Score. | 216 |
| Fig. 10.9. | Distribution of Continuous Variables in Each Parameter. | 217 |
| Fig. 10.10. | Multivariate Correlation Analysis With Numeric Variables. | 218 |
| Fig. 10.11. | Country Proportion by Region (Continent). | 219 |
| Fig. 10.12. | Number of Countries in Report by Cluster. | 219 |
| Fig. 10.13. | Overall Country's Income Group as a Proportion. | 220 |
| Fig. 10.14. | Overall Country's Political Regime as a Proportion. | 221 |
| Fig. 10.15. | Number of Countries by Region, Cluster and Income Group. | 222 |
| Fig. 10.16. | Number of Countries by Region Vs Cluster Variations Count. | 223 |
| Fig. 10.17. | Number of Countries by Region, Income Group and Political Regime. | 224 |
| Fig. 10.18. | Number of Countries by Region, Cluster and Political Regime. | 225 |
| Fig. 10.19. | Choropleth Map Visualisation of AI Total Score Across the Globe. | 226 |
| Fig. 10.20. | Proportion of Countries by Region, Income Group and Political Regime. | 227 |
| Fig. 12.1. | Conceptual Model of Factors Determining User Stickiness to Short Video Platforms (by Authors). | 258 |
| Fig. 12.2. | Themes of Arithmetic, Element and Interactivity Driving the User Stickiness of Short Videos. | 259 |
| Tables | ||
| Table 1.1. | Key Unethical Issues Related to Unethical Practices and Customer Manipulation While Using a Range of Marketing Models and Practices. | 19 |
| Table 2.1. | Definitions of Algorithmic Trading Systems. | 43 |
| Table 5.1. | Gender Differences for the First Dataset. | 105 |
| Table 5.2. | Difference Between Genders for the Second Data Set. | 111 |
| Table 6.1. | Customer Dataset. | 130 |
| Table 6.2. | Silhouette Scores for Clusters. | 131 |
| Table 10.1. | Automation's Role in Human AI Interaction With Drawbacks. | 201 |
About the Editors
Dr Sumesh Singh Dadwal has 23 years of experience in teaching, academic research, eLearning and educational quality management, associated with various UK universities. Currently, he is working as a Senior Lecturer in Strategy at London South Bank University, UK. Previously Dr Dadwal has worked at a number of British Universities such as the Northumbria University, University of Glyndwr, UWL, Birkbeck College, University of London, University of Plymouth, University of Falmouth, Ulster University, University of Roehampton, and Buckinghamshire New University, UK. He has previously worked as a Project Engineer in construction projects and Quality Annalist in the supply chain. He has also been associated with QAA UK, the higher education quality assurance agency of the United Kingdom. Sumesh specialises in international strategies, technological strategy and business models, innovation and technology in marketing, digital marketing, entrepreneurship and business in emerging markets. He is an active researcher undertaking analysis in the service sector, promotional strategies in emerging markets, augmented reality marketing and consumer behaviour, utilising various qualitative and quantitative techniques. He has authored various research papers, recently edited two books, authored many book chapters in other edited books and has led research activities at various levels. His recent publications include many book chapters and journal articles, and he has edited several research books.
Professor Hamid Jahankhani gained his PhD from Queen Mary College, University of London. In 1999, he moved to the University of East London (UEL) and became the first Professor of Information Security and Cyber Criminology at the university in 2010. Professor Hamid has been working with Northumbria University London, UK since 2016. Hamid's principal research area for several years has been in the field of cybersecurity, information security and digital forensics. In partnership with the key industrial sectors, he has examined and established several innovative research projects that are of direct relevance to the needs of the UK and European information security, digital forensics industries, Critical National Infrastructure and law enforcement agencies. Professor Jahankhani is the Editor-in-Chief of the International Journal of Electronic Security and Digital Forensics, www.inderscience.com/ijesdf, International Journal of Electronic Democracy, www.inderscience.com/ijed, both published by Inderscience, and the general Chair of the annual International Conference on Global Security, Safety and Sustainability (ICGS3). Hamid has edited and contributed to over 15 books and has over 150 conference and journal publications together with various BBC radio interviews. Hamid has supervised the completion of 13 PhD and professional doctorate students and overseen 67 PhD students progressing. In summer 2017, Hamid was trained as the GCHQ ‘cyber is’ to train the next generation of cybersecurity experts through GCHQ CyberFirst initiative.
Dr Kenneth Revett has a Doctor of Philosophy (PhD) (Neural and Cognitive Science) from the University of Maryland College Park. Kenneth has 20+ years in the domain of Computational Neuroscientist focusing on designing and developing applications that utilise affective inputs such as emotions, pupillometry for neuropsychological investigations, HCI, BCI, robotics, recommender systems and novel biometric solution. As an academic and as a developer utilising state-of-the-art machine learning algorithms (reinforcement learning, deep learning, recurrent NN, rule-based systems such as rough sets and fuzzy sets), Kenneth has published over 170 scientific papers (and three books) on a variety of topics ranging from basic data classification techniques to deploying real-world neuropsychological applications for the sentiment analysis, locked in subjects (BCI) and user-specific biometric person identification solutions. He also has a significant amount of AI/machine learning experience spanning more than 30 years. He has utilised neural networks, GAs, L-Systems, AIS, swarm technologies as well as more traditional machine learning algorithms, such as LVQ, tree-based methods, clustering, gene sequencing strategies, computer vision analysis of medical imaging datasets, among a host of other technologies. More recently, he has focused on deep learning within the document imaging domain, focusing on mortgage documents (4+ years).
About the Contributors
Sumit Agarwal is a Professor at Delhi Institute of Higher Education, Greater Noida West, India. He has an MBA and a PhD. He has more than 20 years of experience working with various universities. He has published various research papers in reputed journals and participated in conferences/seminars on critical issues relating to management.
Md Salehin Ahmadi is an MBA HR graduate from Jamia Hamdard University. He has emerged as a seasoned professional. Currently working as an Associate – HR Shared Service at Genpact India Pvt. Ltd. in Gurgaon, India. Salehin has also served in the healthcare industry, where he showcased exceptional proficiency in customer relationship and operations management. Salehin has a keen interest in the areas of AI in HR, organisational change and development, people management and workplace culture. He has contributed a few research papers in journals.
Osama Akram Amin Metwally Hussien is a dedicated and accomplished academic with a strong background in information engineering and technology, specialising in network engineering. He is a certified solution architect from AWS and cybersecurity certified from (ISC)^2; he completed his BSc at the German University in Cairo, Egypt, with a grade of UK equivalent to distinction, and his thesis was on smart city – car movement analysis using machine learning. Currently, Osama is pursuing an MSc in Cybersecurity with advanced practice at Northumbria University in London, UK. Osama's research interests include applied cryptography, blockchain, IoT and edge computing, network protocols, localisation, AI and information security. He has made significant contributions to these fields, as evidenced by his numerous publications. In addition to his academic pursuits, Osama has gained practical experience at Pearson PLC, the Egyptian Banks Company and IBM. These roles have allowed him to apply his theoretical knowledge to real-world scenarios, further enhancing his skills and expertise. Osama has also demonstrated his commitment to his field through participation in competitions and conferences such as NCSC Innovators Challenge, ICGS3 Conference and the ISACA London cybersecurity competition where he won an award for his university. His technical skills include network engineering, applied cryptography, cloud computing, AI and machine learning, cybersecurity frameworks, computer architecture, low-level programming, databases and software development.
Nitish Arora is an Assistant Professor at Chitkara Business School, Chitkara University, Punjab, India. He has more than 7 years of experience in teaching. He has an MBA and PhD in Management from Central University of Himachal Pradesh. He is an expert in strategic marketing and strategic management, advertisement and consumer behaviour.
Ajit Bansal is a Professor and Assistant Dean at Chitkara Business School, Chitkara University, Punjab, India, responsible for mentoring and administering courses since 2018. He was awarded a doctorate by HPU Shimla in 2011, and he has Master's degrees in management and commerce. He has over 25 years of experience working with various reputed industries and educational institutions like Graphic Era University, Dehradun, Shoolini University Solan, MAU, Solan, etc. imparting management education in India. His research interests are in the fields of corporate finance, taxation, cultural tourism and microfinance. He has published various research papers in reputed journals and participated in conferences/seminars on critical issues relating to management.
Gordon Bowen has a doctorate in Business (University of Hull) and is a Chartered Marketer from the Chartered Institute of Marketing (UK). He is an Associate Professor in Management at Anglia Ruskin University and works as an Associate Lecturer at various universities and higher education institutions, including Warwick University, University of Gloucestershire, Northumbria University, Cumbria University, Regent's University London, Ulster University, University of Hertfordshire, University of Wales Trinity St. David and Grenoble Graduate Business School. His research interests are strategy, marketing, digital marketing and small and medium enterprises (SMEs), and he supervises PhD and DBA students in these areas. Gordon has many completions at PhD and DBA. Gordon has reviewed articles for journals and conferences including MDPI Sustainability, European Academy of Management Conference and International Journal of Technology Management. He has published edited books on social media and cybersecurity and artificial intelligence (AI), which are recognised internationally. Educational consultancy is another area of expertise, and he works with national and international organisations to develop degree programmes and partnerships. Gordon is also involved as an external examiner (national and international) for doctoral theses. Gordon has held senior positions in the telecommunications industry, including strategy development, business development, technical training and director of sales training. He has also advised SMEs on business matters.
Richard Bowen has worked at some of the largest and fastest growing technology companies and start-ups, including Amazon, Microsoft, Facebook and Instacart. He now plies his trade at Chime after working at Robomart, a Silicon Valley startup, as Interim Chief Operating Officer and now board member. Richard is also an early-stage start-up advisor and mentor, investor, board member, research author and visiting lecturer, with over 15 years of industry diverse operations experience, with a balance of business experience and academia. Richard holds a first class with honours BA in Business and Management and is a doctoral candidate. Rich was recently nominated to attend Stanford University Executive Education Programme, focused on the Emergence of Chief Operating Officers.
Deidre Bowen holds a Master's in Applied Management (Henley Business School) with distinction, is a qualified solicitor and completed her degree at the University of Oxford. She is currently the Director of Delivery at Mental Health UK, responsible for leading and developing all UK-wide programmes. Her research interests are strategy, organisational culture, SMEs sustainability and leadership. More recently, Deidre has explored the impact of the pandemic has on the mental health of both young people and adults. Deidre plays an active role in promoting women and leadership in business; she was a keynote speaker at an event held at the University of Sheffield.
Dr Sonia Chawla is currently working as a Professor at the Department of Humanities and Management, Dr BR Ambedkar National Institute of Technology, Jalandhar. She received her PhD from Guru Nanak Dev University, Amritsar, in 2008. Her primary research interests are in the areas of service quality measurement, financial economics, portfolio management, cost accounting, blockchain and cryptocurrency. Specifically, she works on issues related to financial intermediation, portfolio management and corporate governance. She published 02 books and more than 30 research papers in different international journals of repute. She has supervised 06 PhD students, and 07 are still pursuing their PhD.
Sara El-Deeb is a scholar in Digital Marketing at the Faculty of Management Technology at the German University in Cairo (GUC), Egypt. She teaches a wide range of topics in Digital Marketing and Media Psychology at both GUC in Egypt and GIU in Germany. She is particularly interested in cross-cultural studies and AI; she has worked on various projects, including aerospace. Additionally, she serves as a Researcher, Practitioner and an Advisor to the Ministry of Justice on responsible AI. She delivers corporate training and audits for start-ups and multinational firms. She is also an expert in quantitative techniques using SPSS, AMOS and PLS, as well as qualitative software programs such as MAXQDA. Furthermore, she serves as a reviewer for several journals, including the International Journal of Consumer Studies, International Journal of Sociology and Social Policy and International Journal of Internet Marketing and Advertising.
Shikha Gera is a certified International PPA Practitioner and Trainer. She has over 7 years of experience in research, teaching and training undergraduate and postgraduate management students and corporate professionals. She is currently working as an Assistant Professor in Jamia Hamdard, Department of Management. She has been awarded her PhD degree from Faculty of Management Studies, University of Delhi, in the year 2018. She holds an MBA in Human Resource Management from Guru Gobind Singh Indraprastha University and BCom (Hons) from University of Delhi, Lakshmi Bai College, India. She has been a regular contributor in presenting and publishing papers in national and international conferences and journals. She has been awarded some best paper awards. Her areas of interests are virtual leadership, psychological capital, emotional intelligence and mindfulness.
Krison Hasanaj is a dedicated cybersecurity specialist with comprehensive expertise in securing web applications, conducting network infrastructure redesign and implementing robust security measures to safeguard sensitive data. With a strong academic background in cybersecurity and computer engineering, coupled with practical experience in IT consulting and network engineering, Krison excels in identifying vulnerabilities, mitigating risks and implementing effective security solutions. Known for strong communication and presentation skills, Krison is adept at collaborating with diverse teams and stakeholders to achieve organisational security objectives.
Dr Sonal Jain, a Professor of Management at Northumbria University, concurrently holds the positions of Associate Dean and Head of the Department for undergraduate programmes. Her research expertise encompasses corporate social responsibility, sustainability, anti-corruption strategies, the intersection of corruption with organisation and AI. Sonal also has a decade of industry experience in management and internal communications in France. Dr Jain seamlessly integrates practical insights into her academic pursuits, contributing significantly to the intersection of theory and real-world application.
Lokesh Jasrai is a Professor (Marketing) at Mittal School of Business, Lovely Professional University, India.
K.A.Y.R Oshadi Karunanayaka is a graduate of the University of Kelaniya, Sri Lanka and a postgraduate from Northumbria University, UK. Her expertise is in technology and cybersecurity.
Pawandeep Kaur is a Research Scholar at Dr B R Ambedkar National Institute of Technology, Jalandhar. Her research interests include behavioural studies on ICT interventions. Her research has been published in the Brazilian Business Review and International Journal of Business and Economics Review.
Anil Kaya has an undergraduate education in Electrical and Electronics Engineering from Hacettepe University, Türkiye and a Master of Cyber Security programme at Northumbria University, UK. He has worked in various roles in the IT sector, including network engineering, network security engineering and VOIP system engineering.
Dr Maryam Kiani is a highly motivated PhD graduate from Cardiff Metropolitan University, UK. Her research focused on the influence of materialistic and hedonic values on compulsive buying behaviours. She has over 10 years of teaching and management experience, focusing on NGOs, the education sector and the private sector. She holds two MBA degrees, one in International Business from the United Kingdom and the other in HRM from Pakistan. Currently, Dr Kiani works at the University College of London (UCL) Global Business School for Health as the Lead Employer Engagement and Career Education Manager. She has previously served as the Head of three departments at the University of Lahore, including Director of Career Services and Corporate Linkages, and Director of the Executive Development Centre. Kiani has also worked as the Head of the Marketing Department at the University Central Punjab and as the Head of Academic Support and a Senior Lecturer at the LSST (London School of Science and Technology, UK). Her exciting experience at Explora Security (UK) has helped her understand the international management system. With her vast experience in business development, operations, marketing and management, Dr Kiani is a visionary product developer with a deep education in research and analytics. She is an effective communicator and motivator who identifies and leverages assets in teammates to reach organisational goals. A relentless optimist, she believes that there is no failure, only feedback.
Pawan Kumar is a Doctor of Philosophy from Punjabi University, Patiala with specialisation in the field of marketing and currently works as a Professor in Mittal School of Business, Lovely Professional University, Phagwara, Punjab. He has 16 years of experience in business academic research. His areas of interest in research include sustainability, entrepreneurship, e-commerce, consumer behaviour and marketing research. He has more than 40 publications in reputed journals, particularly in Q1 and Q2 journals to his credit, in various research papers in Scopus-indexed journals, namely The TQM (Total Quality Management) Journal from Emerald, Visions: Journal of Business Perspectives from Sage, International Journal of Business and Globalisation, International Journal of Business Information Systems from Inderscience and other national/international journals of repute.
Shani Kumar is a Research Scholar in the Department of Humanities and Management at Dr B R Ambedkar National Institute of Technology, Jalandhar. He has completed his BCom (H) from Dyal Singh College (Evening), Delhi University. He has completed his MCom in Business Management from Jamia Millia Islamia, Delhi. He has also qualified UGC NET examination with JRF. He is working in the area of digital payments, cryptocurrencies, blockchain and adoption and its continuous usage.
Dr Vipin Nadda is a Senior Lecturer and Programme Manager (BSc Tourism and Hospitality/BSc Events/FdA Tourism) at the Department of Tourism, Hospitality and Events, in the University of Sunderland in London. Vipin does research in tourism, hospitality and marketing.
Isuru Sandakelum Will Arachchige is an information security professional pursuing an MSc in Cybersecurity with Advanced Practice at Northumbria University London. With a BEng in Computer Networks and Network Security from Staffordshire University, he delves into the ethical and societal impacts of AI, particularly its influence on human–AI interaction and personalisation. His passion lies in the interplay between technology and human connections. He actively contributes to discussions on responsible AI development and implementation, aiming to bridge the gap between technology and ethical considerations. Beyond cybersecurity, Isuru is passionate about safeguarding digital assets through research, with publications focusing on quantum cryptography and strengthening security mechanisms. Recognised for their achievements, Isuru has won accolades in cybersecurity competitions and participated in global initiatives like the NASA SpaceApps Challenge, showcasing their commitment to innovation and excellence in computing sciences.
Dr Mushtaq Ahmad Shah is a highly ambitious and hardworking person who encourages student's participation and enthusiasm while facilitating learning in the areas of accounts, finance and economics. She has a PhD in Infrastructure Finance. She has published more than 10 research papers in reputed journals, attended various national and international conferences and has more than 6 years of teaching and research experience.
Archana Shankar completed a doctorate in Organisational Behaviour from Faculty of Management Studies (FMS), University of Delhi, New Delhi, India, 2015. She also holds a BE in Computer Science Engineering (2006, Anna University, Chennai, India) and an MBA in Human Resource and Systems (2008, Anna University, Chennai, India). She was awarded (Senior Fellow – Higher Education Academy, UK, Dec 2023; FHEA, April 2021) and completed CIPD Level 5 (Learning and Development (Dec 2021) and APM – PFQ (July 2023). She has over 14 years of teaching and research experience, with books and articles in leading publications. Her areas of interests include leadership, organisational culture, quality management, organisational development and change management. She currently works with Northumbria University, London Campus, UK, as the Deputy Associate Dean and the Head of the Department, MSc International Project Management, teaching postgraduate courses (Level 7) in Business Management.
Ahmed Adel Tantawy is a Lecturer (Assistant Professor) in International Business at Sheffield Hallam University, UK. His main research areas are entrepreneurship, non-market strategies, political ties, legitimacy, new venture survival/failure, corporate entrepreneurship, innovation, emerging markets and firm performance. He has published in journals such as International Marketing Review, Industrial Marketing Management and Journal of Entrepreneurship in Emerging Economies.
Arpit Tiwari is an Assistant Professor at Mittal School of Business, Lovely Professional University.
Yifei Xiang is the Senior Vice President of Management and the Director of the Training Institute at a Chinese company. He has worked for several major property companies in China. He holds a Master of Science from Northumbria University and a Bachelor of Management from Sichuan University. His research focuses on business and human resource management.
Preface
AI, large language-based models (LLM), Internet of Things (IoT) and allied technologies have enabled machines to perform business activities that are normally performed by human beings (Ho & Chow, 2023; Werner et al., 2022). AI has become a crucial tool for enhancing corporate core competencies, steering towards agile corporate strategies and business models and understanding the challenges of internal (employee relationship management – ERM) and external customer relationship management (CRM) (Smith, 2018; Ventura, 2021). Technology and human interaction bring in a lot of opportunities and challenges in the management of the business in general and marketing in particular (Belanche et al., 2020; Dukes et al., 2020; Krafft et al., 2020). The use of technology also brings in issues related to trust, perceived risks and threats, ethical, security and social impacts, and so on (Chen et al., 2022). The most important is about misusing AI for market grooming and consumer grooming. The markets often stalk their consumers and slowly groom them by tracking, predicting, grooming and then selling the products of the services (Grogan, 2019). Studies have claimed that companies like Amazon could accurately predict that a particular woman is pregnant (even before those women knew it) (Grogan, 2019).
Using technologies, the markers send subliminal messages, neuromarketing, social constructive reasonings, cues and stimulus to the consumers and slowly and gradually condition consumers to ‘do what marketers want them to do’. This is market and consumer grooming, where a consumer is almost a novice, has not given informed consent and doesn't know that they are making decisions based on what others are telling them and not based on what they shall do undependably. This can compromise consumer independence, freedom and democracy. Such tools if used in politics can mar the whole democratic process of countries and political systems. The book touches on consumers' sides of issues where the consumers might be manipulating AI platforms (deliberately seeing other sites and products, putting products in baskets…. and complaining about being misfolded and waiting for offers). This area is also being not researched yet (Ventura, 2021).
Market Grooming: The Dark Side of AI Marketing will be a paradigm shift project in the field of marketing. The book explores how marketing is executed to attract customers (where customers are free to make decisions) from an opposite paradigm, i.e. where the customers, markets and communities are groomed, socially conditioned, subliminally marketed and influenced to passably ‘do what marketers want the consumers to do’. Such research work will have great implications in minimising the negative consequences of AI and technology-enabled marketing to individuals, communities, societies, governments and so on. This will reinforce the idea of ethical–sustainable marketing in the era of Industry 5.0. It answers to lean back’ experience of the stakeholders. The book will reinforce that Marketing 5.0 should be about technology for humanity and not the other way.
This book is a unique interdisciplinary project inculcating and integrating ideas of public policies, business and techno-entrepreneurs with those with a stream of technology. The book has inputs from fields of marketing, technologies, cybersecurity, AI, ChatGPT, ICT, IoT, big data analytics, etc. There is not much research in the areas of market grooming, and AI and new CRM models (Ledro et al., 2022; Smith, 2018), technology and new digital consumer behaviours and customer journey mapping (Ho & Chow, 2023) and lean back attitude (Darsi, 2022).
Acknowledgements
Artificial intelligence (AI), large language-based models (LLM), Internet of Things (IoT) and allied technologies have enabled machines to perform business activities that are normally performed by human beings. The book explores how marketing is executed to attract customers (where customers are free to make decisions) from an opposite paradigm, i.e. where the customers, markets and communities are groomed, socially conditioned, subliminally marketed and influenced to passably ‘do what marketers want the consumers to do’.
Bringing together the diverse expertise required for Market Grooming: The Dark Side of AI in Marketing has been a journey enriched by the generosity, talent and dedication of many individuals.
First and foremost, we extend our heartfelt gratitude to the contributing authors whose insightful chapters have lent depth and breadth to this edited volume. Your expertise and willingness to share your knowledge have been invaluable.
We are indebted to the editorial team members whose meticulous efforts ensured the coherence and quality of this publication. Your guidance and expertise have been instrumental in shaping this book. We further extend our sincere appreciation to the reviewers whose constructive feedback helped refine and strengthen the content of this book. We also acknowledge the researchers whose excellent works have inspired and informed the contributors.
We lovingly express our gratitude to the dedicated team at Emerald Publication for their support and professionalism throughout the publication process. Your commitment to excellence has been evident every step of the way.
Lastly, to our readers, we thank you for your interest in exploring the complex interplay between AI and marketing. Your engagement and curiosity are the driving force behind our endeavour.
The most important is about misusing AI for market grooming and consumer grooming. The markets often stalk their consumers and slowly groom them by tracking, predicting, grooming and then selling the products of the services. Together, we have illuminated the dark side of AI in marketing, fostering a deeper understanding of its implications and paving the way for future inquiry.
Thank you all for your invaluable contributions.
Warm regards,
Editors
Sumesh Singh Dadwal, Hamid Jahankhani, and and Kenneth Revett
Introduction
Audience
The book will also be a useful source for academics, researchers and technology-driven strategists and marketers to understand and apply the principles and the practices of artificial intelligence (AI), the Internet of Things (IoT), conversation services automation (chatbots) and allied technology-empowered strategies, new business models and AI, machine learning, digital marketing, AI-CRM models and associated personal, social, political–legal and ethical concerns in the marketing in the developed as well as in less developed countries. The book will also be of interest to regulators, law implementing agencies, professional bodies and IT technologists and consultants across sectors.
Key Features of the Book
Several books are written for marketers to exploit or use AI to their advantage. Almost no books exist which highlight the agendas and issues of market grooming by marketers. The book put forward explores and analyses a range of unethical practices in marketing such as grooming your customers using AI, neuromarketing, subliminal marketing and customer stalking. Customers on the flywheel, navigating the dynamics of patient grooming on doctor–patient relationships, use ChatGPT in Marketing 5.0, AI shapes the hiring process through biased HR data, machine learning techniques to project customer behaviour, it also discusses areas on practices of ethical marketing, exploring AI frameworks of ethical marketing in the era of AI, ethical navigation paradigms in AI-driven marketing, the balance between personalisation and automation in human–AI interaction, AI in digital marketing and actions to improve the image of marketing.
Hence, it seems a unique research project with almost no competition or at least no direct competition, as this book focuses on a new paradigm of market grooming by marketers, a kind of negative side of marketing (how to avoid those negative personal, social, ethical and political legal impacts of AI in marketing) and will be interesting to a variety of stakeholders, regulations, marketing agencies, governments, consumers and so on. The book will explore a variety of interdisciplinary areas and will contribute chapters from authors from Europe and Asia, so the book will be more valuable for the readers. This book explores and analyses the principles and practices of AI, the IoT, ChatGPT, conversation services automation (chatbots) and allied technology strategies and digital marketing.
Organisation of This Book
The book has explored the concept, model and practice of the dark side of digital technology in general and AI in particular and its use in grooming the customers and grooming the market. The book explores the strategic side as well as practices of marketing companies in grooming customers using technology, AI and concepts of customer stalking. Flywheel model, neuromarketing, subliminal marketing ethical and unethical marketing and so. The book is organised to first analyse the concept, practices and models of market grooming, followed by a positive application of AI and machine learning; there are also sections on ethical marketing in the era of marketing, and towards the end, the book develops some arguments for improving the image and practices of marketing.
The first chapter explores and analyses a range of unethical practices in marketing such as grooming customers using AI, neuromarketing, subliminal marketing and customer stalking, customers on the flywheel, and Chapter 2 is on AI-Driven Trading: Navigating the Complex Landscape of Market Manipulation. Chapter 3 illustrates the dynamics of patient grooming in doctor–patient relationships. Chapter 4 is about the application of ChatGPT in Marketing 5.0. Chapter 5 analyses how AI is shaping the hiring process through biased HR data.
The second section discusses areas of practices of ethical marketing. Chapter 6 analyses the use of machine learning techniques to project customer behaviour. Chapter 7 explores the AI frameworks of ethical marketing in the era of AI. Chapter 8 is about ethical navigation paradigms in AI-driven marketing. Chapter 9 debates creating a balance between personalisation and automation in human–AI interaction. Chapter 9 is about AI and ethical digital marketing.
The third section is about balancing AI and marketing. Chapter 10 explores the balance between personalisation and automation in human interaction. Chapters 11–13 discuss a range of actions to improve the image of marketing, practices of Chinese short video platforms to enhance user stickiness and grooming and neuromarketing.
Though each chapter on its own has independent standing and relevance, however, as a whole, the book flows from exploring the concept of marketing and thorough ethical paradigms and closes with a positive set of recommendations.
This book is organised into 13 chapters. A brief description of the chapters is given in the following sections.
Chapter 1 – Market Grooming: Grooming Customers Using Artificial Intelligence
This opening chapter sets the scene and builds the framework of the book and the concept of market modelling and the use of AI. In the era of generative AI, big data analytics, business analytics and mega global digital corporations, the profession of marketing is at a crossroads between ‘Prosumer-Marketing’ and ‘Market Grooming’. ‘Market Grooming’ is a one-sided, unethical process of conditioning or influencing, deceiving or persuading or manipulating and even exploiting customers by the marketing organisations, without customers' voluntary consent, permissions, awareness, etc. As the consumers have asymmetric access to information, asymmetric and lesser favourable levels of control, and lesser power in the process of exchange, as customers trust the marketers or are dependent on popular brands; the markers tend to exploit the situation. The process of market grooming has become easier due to the power of AI, generative AI, ChatGPT, TikToketing, machine learning and big data analytics leading to the development of sophisticated predictive models and persuasive models. This chapter explores and analyses a range of techniques in marketing such as permission marketing, Flywheel marketing, subliminal marketing, neuromarketing, cyberstalking ethical marketing, etc. in the era of AI. The arguments for high concerns pertaining to potential market grooming are supported by theories of ethics, theories of digital marketing and models of AI. The chapter concludes with some strategic recommendations.
Chapter 2 – AI-Driven Trading: Navigating the Complex Landscape of Market Manipulation
Algorithmic trading has evolved beyond traditional methods by incorporating machine learning techniques to analyse extensive datasets. The integration of machine learning and ATS has helped in enhancing the decision-making process leading to more accurate predictions of market trends, risk assessments and optimal execution strategies. The opaque nature of artificial trading models can create challenges in understanding the decision-making process of these systems. This lack of clear understanding raises questions about accountability, and market participants lack transparency on whether movements are economic-driven or algorithmic trading strategies. The chapter explores the development of AI-driven trading and key characteristics of algorithmic trading systems. In conclusion, the integration of machine learning into capital markets represents a major shift in how investment decisions are made, risks are managed and how markets operate independent AI trading systems. Its increasing use highlights the need for careful ethical consideration, regulatory flexibility and ongoing monitoring.
Chapter 3 – The Dark Side of AI: Navigating the Dynamics of Patient Grooming on Doctor–Patient Relationships
The growth of AI-enabled marketing has led to motivating customers purchase goods and services where the customers are ‘nurtured’ or ‘groomed’ to make a purchase decision. Consumer grooming as the name suggests involves changing or influencing an individual's behaviour and decision-making abilities by repeated personalised messaging. We have entered an era where AI is driving marketing in almost all industries and influencing customer decision-making. The healthcare industry is quite a concern as it involves the health of the poor and vulnerable impacted by AI decision-making, also deeply affecting the conventional doctor–patient relationships. AI in healthcare marketing involves using marketing gimmicks by marketing organisations where individuals are targeted with individualised medical messaging, changing the trust dynamics between patients and doctors. The marketing gimmicks often impact the healthcare decision-making of the patients, leading to induced healthcare purchases through these marketing messages, rather on advisory of doctors or other healthcare professionals. As a result of this constant patient grooming or medical brainwashing, patients end up making a wrong decision regarding their healthcare. Therefore, it is required that stakeholders in the health ecosystem prioritise more transparency, authenticity and patient empowerment to mitigate the challenges of patient grooming in the healthcare sector. The establishment of more stringent controls on medical marketing techniques, the development of health literacy and the cultivation of open communication channels within the healthcare ecosystem are all necessary because of this. In the end, AI-driven marketing presents prospects for personalised healthcare experiences; yet its unregulated expansion raises substantial ethical and patient safety issues.
Chapter 4 – ChatGPT in Marketing 5.0: Gold Is Real or Just a Gold Plating
Organisations using advanced technology, like ChatGPT, for executing their marketing practices are proliferating, but such fast growth also comes with different adverse impacts of ChatGPT. This interaction of ChatGPT with the humanly implemented Marketing 5.0 approach complements the marketing effectiveness. However, while considering the brighter aspects of this techno-marketing integration, marketers should also keep its dark side in mind. Therefore, this chapter investigates the integration of AI-enabled ChatGPT into Marketing 5.0 practices. However, both the concepts under study are growing in terms of literature, and the research gap is even more extended when considering their associated views. Furthermore, significantly less literature is available emphasising the negative aspects of this advanced technology. This chapter bridges these gaps by reviewing the literature and presents the gold-plating effect of ChatGPT usage while implementing Marketing 5.0 practices. It also proposes a framework for showing the relationship between ChatGPT utilisation for practicing Marketing 5.0, depicting the dark side of this techno-marketing integration. It also emphasised the need for conscious and learnt association between the concepts under study.
Chapter 5 – Unpacking the Double-Edged Sword: How Artificial Intelligence Shapes Hiring Process Through Biased HR Data
This chapter discusses and explores how AI has transformed the field of hiring, enabling employers to collect and analyse massive amounts of data to understand and predict the suitability of candidates. However, AI can also have subconscious effects on candidates' and employers' needs through biased data, which can stem from human biases, algorithmic errors or external factors. For example, Amazon scrapped an AI-based recruitment program that favoured male candidates over female candidates due to the historical patterns in the resumes it analysed. This chapter examines how AI can shape a candidate's needs through biased data from various sources and types and what are the consequences for a candidate's welfare and rights. We review the literature on AI applications in hiring, the origins and kinds of bias in AI systems and the potential risks and benefits for candidates. We also suggest some guidelines for reducing bias in AI and enabling candidates to make informed and ethical choices online. We argue that AI can be a double-edged sword for candidate's needs and that more research and regulation are required to ensure its fair and accountable use.
Chapter 6 – Leveraging Machine Learning Techniques to Project Customer Behaviour Through Predictive Analysis and Ethical Marketing
This research investigates the intricate dynamics of consumer behaviour and the transformative impact of predictive machine learning algorithms. Employing a mixed-methods research design, combining quantitative and qualitative techniques, the study explores the application of unsupervised K-means clustering and supervised random forest algorithms. Through real-world case studies and data analysis, insights are gained into the predictive modelling of customer behaviour in diverse industries. Findings reveal the effectiveness of these techniques in segmenting customers based on income and spending behaviour, with a prediction accuracy of 84%. Furthermore, the study underscores the importance of integrating qualitative insights to enrich understanding and validity. The study also critically explores the potential risks associated with unethical marketing that leads customers to purchase products without their voluntary and fully informed consent.
Chapter 7 – Towards Responsible AI: Exploring AI Frameworks, Ethical Dimensions and Regulations
The field of AI is advancing far more rapidly than the establishment of rules and regulations, which is causing certain fear. However, slowing down this progression to avoid an economic crisis is not an option because of open-source AI, which facilitates faster development processes and collective contributions to codes and algorithms. Public policies, such as the ‘European Union AI Act (EU AI)’, ‘Whitehouse AI’ and the G7's ‘Hiroshima Artificial Intelligence Process’ (HAP), have already been drafted. Regulators need to adopt a dynamic approach given AI's rapid advancement, and they need to eventually strive for international harmonisation in their rules and regulations for better collaborations. The EU's AI Act is the ‘world's first comprehensive law’, and it focuses on five main pillars similar to other countries' drafts: ensuring AI usage is safe, transparent, traceable, non-discriminatory and environmentally friendly. They portray four risk categories against which citizens can file complaints: (1) unacceptable risk, (2) high risk, (3) generative AI, and (4) limited risk. The US AI policies include ‘The Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People’ and the ‘Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence’. This conceptual study extensively reviews the concept of AI and compares pioneering draft laws while providing recommendations on ethics and responsible AI.
Chapter 8 – Ethical Navigation Paradigms in AI-Driven Marketing: Insights and Perspectives
AI has several advantages for enhancing marketing strategies. It raises ethical problems about customer priority, market share consolidation and consumer manipulation. This study examines ethical issues from a modern viewpoint, using insights from AI and previous literature reviews. The implementation of AI in marketing may result in unanticipated ramifications, including the reinforcement of preexisting prejudices, infringement upon customer privacy, restriction of competitive forces and meddling with consumer conduct. This research seeks to enhance the industry by offering a contemporary viewpoint on the ethical issues related to AI utilisation in predictive marketing, based on insights from previous literature reviews in the field.
Chapter 9 – Artificial Intelligence in Digital Marketing: The Ethical Implications of Digital Influence on Markets and Consumer
This research, titled ‘AI in Digital Marketing: The Ethical Implications of Digital Influence on Markets and Consumers’, conducts a comprehensive examination of the nuanced role played by AI in shaping consumer behaviour and influencing decision-making processes. While the incorporation of AI in marketing offers commendable advantages, such as providing personalised content and optimising strategies to enhance customer experiences and market efficiency, it concurrently introduces ethical considerations. This study meticulously scrutinises the latent potential for market grooming, wherein AI subtly guides consumers towards decisions that may not align with their best interests. By delving into instances of data privacy breaches, algorithmic biases and the unintended consequences of hyper-personalisation, this research contributes substantively to the ongoing discourse on the responsible utilisation of AI. The study underscores the imperative need for regulatory frameworks aimed at ensuring ethical practices in the dynamically shifting digital landscape. It endeavours to strike an equitable balance between the constructive contributions and potential pitfalls of AI in the realm of marketing. Through this research, we aim to shed light on the ethical dimensions associated with the digital manipulation of markets and consumers, providing insights that can inform industry practices, policymaking and public awareness.
Chapter 10 – Exploring the Balance Between Personalisation and Automation in Human–AI Interaction
This study investigates the intricate relationship between personalisation and automation in AI, focusing on their impact on human interactions. The purpose is to discern patterns significantly influencing modern society, using notable examples from e-commerce, social media and digital advertising. The research employs a multifaceted approach, drawing insights from real-world examples of AI implementation. Noteworthy instances include Amazon's use of AI algorithms for personalised product recommendations, Netflix's application of AI in content recommendations and Tesla's Full Self-Driving feature in autonomous vehicles. The findings reveal the dual nature of personalisation and automation. In e-commerce, personalised recommendations, such as those on Amazon, can lead to impulse buying and potential financial strain. Similarly, social media algorithms, like Facebook's echo chamber and advertising strategies, exemplified by Google's ‘skippable’ and ‘non-skippable’ ads, strategically influence user behaviour and decision-making. The research also highlights the success of Netflix's personalised content delivery and the potential safety challenges in Tesla's Full Self-Driving feature. The study underscores the importance of a balanced approach to personalisation and automation, especially in ethical considerations, user privacy and data security.
Chapter 11 – Improving the Image of Marketing: AI Has the Potential to Assist in Marketing Decisions and Change Perceptions
Marketing is sometimes viewed as manipulative and as enticing consumers to live beyond their means. AI-powered systems can change the image of the marketing discipline and improve the marketing decision-making process. This chapter argues that embedding AI in the marketing process can help to alleviate public and consumer concerns about the marketing discipline. AI has the potential to make the marketing process transparent, but this is dependent on trust and privacy variables. Openness about using AI in the customer experience and how it is applied will put marketing on an objective framework. However, marketing decisions will be a mix of data and information mediated by intuition, reasoning, experience and empathy and these are qualities that are associated with marketers. AI customer experience requires decisions that are objective (personalisation) and those that are empathy related.
Chapter 12 – Exploring the Practices of Chinese Short Video Platforms to Enhance User Stickiness and Grooming the Customers: A Case Study of DOUYIN China (TikTok)
The global popularity of short video platforms has surged with the rapid development of mobile internet and 5G technology. DOUYIN, among other platforms, has amassed a massive user base in China. This study presents a theoretical framework based on media dependency theory and user stickiness perspectives. It identifies three key factors that affect user stickiness: platform algorithms, content resources and user interaction. An interpretive philosophy and inductive qualitative approach were adopted to conduct an in-depth case study of DOUYIN. Thematic analysis of secondary data from various sources was used. The findings demonstrate DOUYIN's innovative approach to utilising advanced algorithms, diverse content and social interactions to enhance user engagement. DOUYIN utilises machine learning techniques to create user profiles and comprehend video content. It subsequently provides real-time personalised recommendations and optimises the algorithms based on user feedback. DOUYIN also incorporates PGC, UGC and PUGC generated content, supported by a creator incentive system. Moreover, DOUYIN enables interactions between users, creators and the platform through commenting, sharing and live streaming features.
Chapter 13 – Market Grooming: How Neuromarketing Influences Consumers' Purchase Decisions?
Neuromarketers use methods like eye tracking, biometrics, brain imaging (fMRI and EEG) and eye tracking to try to understand how consumers make decisions, what grabs their attention and how they emotionally interact with companies, products and ads. Market grooming is the process of creating and manipulating the existing market towards a specific product, service or idea. It is the practice which helps the marketer to groom the product through various stages of marketing, be it market research, product development, advertising campaigns or creating favourable conditions for the product, all practices are performed to groom the market for a specific product; when it is combined with neuromarketing, it becomes a perfect blend for the success of the product in the actual market. The study concludes that market grooming along with neuromarketing can present a significant potential for enhancing the understanding of consumer decision behaviour by increasing the validity and precision of assessing customer responses to marketing activities.
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- Prelims
- Chapter 1 Market Grooming: Grooming Customers Using Artificial Intelligence
- Chapter 2 AI-Driven Trading: Navigating the Complex Landscape of Market Manipulation
- Chapter 3 The Dark Side of AI: Navigating the Dynamics of Patient Grooming on Doctor–Patient Relationships
- Chapter 4 ChatGPT in Marketing 5.0: Gold Is Real or Just a Gold Plating
- Chapter 5 Unpacking the Double-Edged Sword: How Artificial Intelligence Shapes Hiring Process Through Biased HR Data
- Chapter 6 Leveraging Machine Learning Techniques to Project Customer Behaviour Through Predictive Analysis and Ethical Marketing
- Chapter 7 Towards Responsible AI: Exploring AI Frameworks, Ethical Dimensions and Regulations
- Chapter 8 Ethical Navigation Paradigms in AI-Driven Marketing: Insights and Perspectives
- Chapter 9 Artificial Intelligence in Digital Marketing: The Ethical Implications of Digital Influence on Markets and Consumer
- Chapter 10 Exploring the Balance Between Personalisation and Automation in Human–AI Interaction
- Chapter 11 Improving the Image of Marketing: AI Has the Potential to Assist in Marketing Decisions and Change Perceptions
- Chapter 12 Exploring the Practices of Chinese Short Video Platforms to Enhance User Stickiness and Grooming the Customers: A Case Study of DOUYIN China (TikTok)
- Chapter 13 Market Grooming: How Neuromarketing Influences Consumers’ Purchase Decisions?