Masterarbeit, 2024
89 Seiten, Note: 66
1.0 INTRODUCTION
1.1 Background of Study
1.2 Research Problem and Justification
1.3 Research Aim and Objectives
1.3.1 Research Aim
1.3.2 Research Objectives
1.4 Research Questions
1.5 Chapterization Structure of Dissertation
2.0 LITERATURE REVIEW
2.1 Brief Overview of Marketing
2.2 Digital Marketing as a Modern Approach to Marketing
2.2.1 Search Engine Optimisation
2.2.2 Content Marketing
2.2.3 Social Media Marketing
2.2.4 Influencer Marketing
2.2.5 Email Marketing
2.2.6 Challenges Associated with the Use of Digital Marketing
2.3 Artificial Intelligence and its Relevance to Digital Marketing
2.4 Small and Medium Enterprise
2.5 Theoretical Framework
2.5.1 Maslow’s Hierarchy of Needs
2.5.2 Cognitive Dissonance Theory
2.5.3 Blue Ocean Theory
2.6 Artificial Intelligence on Digital Marketing in the Nigerian Context
3.0 METHODOLOGY
3.1 Research Philosophy
3.1.1 Positivist Research Philosophy
3.1.2 Interpretivist Research Philosophy
3.1.3 Pragmatic Research Philosophy
3.1.4 Rationale Behind the Choice of Research Philosophy
3.2 Research Approach
3.2.1 Rationale for the Choice of Abductive Approach
3.3 Research Strategy
3.4 Data Collection
3.5 Data Analysis
3.6 Ethical Consideration
4.0 DATA PRESENTATION, ANALYSIS, AND DISCUSSION
4.1 Quantitative Analysis
4.1.1 Descriptive Analysis of Questionnaire
4.1.2 Statistical Analysis of Questionnaire
4.2 Qualitative Analysis
4.2.1 Result-generating marketing campaign
4.2.2 Reduces Financial Waste
4.2.3 Effective and Speedy Connection to Prospective Customers
4.2.4 Infrastructural and Regulatory Deficiency
4.2.5 Limited Trained and Schooled Digital Marketer and AI Professionals
5.0 CONCLUSION AND RECOMMENDATIONS
5.1 Summary
5.2 Key Findings
5.3 Recommendations
This dissertation examines the impact of integrating artificial intelligence (AI) into the digital marketing strategies of small and medium enterprises (SMEs) in Nigeria, with the objective of identifying opportunities and challenges in this evolving landscape.
2.3 Artificial Intelligence and its Relevance to Digital Marketing
Basri (2020) posits that about 2.77 billion users surf the social media platforms globally, in which a huge data is generated through these interactions. These interactions are characterized by the display of diverse attitudes, dispositions, beliefs, and desires of customers, which are important information needed for strategic marketing initiatives. These variables are essential for digital marketers to review and make decisions, which will require the understanding of human psychology. It is important to note that AI is one of the few fourth industrial revolution technologies that suitably provides this functionality (Yau et al. 2021).
The term artificial intelligence was first mentioned in the research carried out by John McCarthy in 1955 with its associates (Svetlana et al., 2022). The term was defined by the researcher as intelligent machines driven by science and technology, with keen focus on computer programs with high level intelligence. Several other definitions have emerged in recent times, especially after the evolution of the fourth industrial revolution technologies. A few of the technologies that characterized the fourth industrial revolution, which are also important to the operations of AI include machine learning, big data, and natural language processing (Najem et al., 2022). Machine learning, which utilizes algorithms and data set, evolved and produced deep learning that leverage on the capabilities of the human brain to process images, texts, and sounds.
Artificial intelligence can therefore be defined as the simulation of human intelligence through software programs by exploring machine learning, natural language processing, data mining, image recognition to mention but a few to manage human functions to facilitate the duties that are carried out by humans (Chen et al. 2022). AI has the capacity to utilize and alter data into useful information to monitor consumer behavior and for strategic business purposes (Rabby et al. 2021). Nanayakkara (2020) asserts that AI can assist in providing competitive pricing by exploring pricing patterns, evaluating price elasticity, and track buying patterns of consumers.
1.0 INTRODUCTION: This chapter provides the foundation for the research, outlining the shift towards digital marketing and the need for AI adoption among Nigerian SMEs.
2.0 LITERATURE REVIEW: An analysis of branding, the digital revolution, and theoretical frameworks like Blue Ocean Theory that explain SME growth and AI application.
3.0 METHODOLOGY: Covers the pragmatic research philosophy and abductive approach used to collect and analyze quantitative and qualitative data.
4.0 DATA PRESENTATION, ANALYSIS, AND DISCUSSION: Details the empirical findings from surveys and interviews, evaluating the impact of AI on sales and marketing performance.
5.0 CONCLUSION AND RECOMMENDATIONS: Synthesizes the core findings and offers strategic guidance for government policy and SME practice.
Artificial Intelligence, Digital Marketing, SMEs, Nigeria, Consumer Behavior, Business Performance, Machine Learning, Data Analytics, Marketing Strategy, Competitive Advantage, Technological Infrastructure, Entrepreneurship, Marketing Automation, Customer Retention, Business Management.
The research mainly investigates how artificial intelligence influences the effectiveness of digital marketing strategies implemented by small and medium-sized enterprises (SMEs) within the Nigerian business environment.
The study focuses on the intersection of digital marketing practices, the integration of AI tools, the operational challenges of Nigerian SMEs, and theoretical frameworks that explain organizational performance.
The primary aim is to examine the impact of AI on digital marketing performance, identify associated challenges, and provide actionable recommendations for SMEs to integrate these technologies into their strategies.
The study adopts a pragmatic research philosophy using a mixed-methods (abductive) approach, combining quantitative survey data with qualitative insights from semi-structured interviews.
It covers the evolution of marketing, the specific barriers Nigerian SMEs encounter (such as infrastructure and talent gaps), and how AI technologies can facilitate data-driven decision-making and cost optimization.
Essential keywords include Artificial Intelligence, Digital Marketing, Nigeria, SMEs, business performance, consumer behavior, and marketing strategy.
The study identifies the lack of trained and schooled AI professionals and limited local university curricula focused on AI as major barriers to effective technology integration.
Recommendations include public-private partnerships to improve infrastructure, urging universities to include AI in business curricula, and encouraging future studies to compare SME performance with larger corporations.
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