Chapter 12: Data Analytics in Marketing Management: A Literature Review Applying TCCM Framework

Data analytics in marketing has expanded significantly. Technological advancements facilitate consumer–brand interactions, enhancing relationship-building. This study employs the Theory-Context-Characteristics-Methods framework to analyse existing theories, contexts, characteristics and methodologies within marketing data analytics literature. A systematic review of 197 articles was conducted utilising the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. Various research methodologies, including Structural Equation Modelling and case studies, are utilised to investigate industry trends and consumer behaviour. These inquiries address topics from Business Intelligence’s role to Industry 4.0 effects. The research reveals an increasing diversity in theoretical frameworks, incorporating Market Orientation and Dynamic Capability theories. The integration of advanced technologies like Artificial Intelligence and machine learning reflects a shift towards sophisticated analytical methodologies. These trends indicate a focus on practical applications, exemplified by Algorithmic Bias Management and Digital Supply Chain, transitioning theoretical insights into actionable marketing analytics solutions. A proposed framework identifies multiple factors influencing readiness for data analytics adoption, which affects performance outcomes and practices. Performance outcomes are shaped by guidelines and various factors, including customer and market-related variables. Management readiness, external support and other moderating factors influence relationships between independent and dependent variables. The examined sectors encompass various industries such as Banking and Education. The studies involve varied sampling units, suggesting a wide inquiry scope. However, sectors like Healthcare and Government are underrepresented, which may restrict the applicability of findings to broader societal contexts. The primary emphasis appears to be on commercial and technological sectors, potentially limiting the findings’ generalisability.