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Data-Driven Marketing Analytics: Research Methods and Analytical Tools bridges the gap between traditional marketing research and modern big data analytics, offering a step-by-step guide to transforming data into actionable insights. Readers will gain practical skills to design and manage research projects, predict customer behaviour, and uncover hidden patterns in purchasing data. The book delivers these benefits through hands-on exercises, shareable datasets, and visual workflows, ensuring accessibility for users without coding experience. Key features include real-world case studies, interactive examples, and tools for segmentation, forecasting, and strategic decision-making. This book is tailored for postgraduate students, researchers, and marketing professionals seeking to master data-driven decision-making. It is ideal for advanced courses in Marketing Analytics, Management Information Systems, and Business Statistics. The book is supported by a comprehensive online repository containing over 100 ready-to-use files, including datasets, Excel solutions, SPSS files, and Orange workflows.
Data-Driven Marketing Analytics: Research Methods and Analytical Tools bridges the gap between traditional marketing research and modern big data analytics, offering a step-by-step guide to transforming data into actionable insights. Readers will gain practical skills to design and manage research projects, predict customer behaviour, and uncover hidden patterns in purchasing data. The book delivers these benefits through hands-on exercises, shareable datasets, and visual workflows, ensuring accessibility for users without coding experience. Key features include real-world case studies, interactive examples, and tools for segmentation, forecasting, and strategic decision-making. This book is tailored for postgraduate students, researchers, and marketing professionals seeking to master data-driven decision-making. It is ideal for advanced courses in Marketing Analytics, Management Information Systems, and Business Statistics. The book is supported by a comprehensive online repository containing over 100 ready-to-use files, including datasets, Excel solutions, SPSS files, and Orange workflows.
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