Autorentext
Dr Nasir Salari joined Bath Spa University in 2013 after completing his PhD in Marketing at the University of Birmingham. He is currently the Academic Research Lead and Partnership Leader at Bath Spa University. Dr Salari has extensive teaching experience in various aspects of Business Management, including Marketing Analytics, Data Science and Innovation Adoption Behaviour. His teaching is informed by a deep understanding of both marketing and data science, ensuring that students gain a contemporary and practical education that bridges these crucial fields. His expertise lies at the intersection of marketing and data science, with a particular focus on the application of advanced analytical techniques to marketing challenges. Dr Salari holds professional certificates in Data Science from the Data Incubator and Cambridge Spark and is actively engaged in research exploring the integration of data science into marketing practices. His research interests include Natural Language Processing (NLP) for sentiment analysis and machine learning techniques such as Approximate Nearest Neighbours, Random Forests, t-SNE, and K-Means clustering, among others. In his role as Academic Research Lead, Dr Salari focuses on advancing the research activities within the Business School's research centre. As Partnership Leader, he is responsible for developing and managing strategic partnerships that enhance the Business School's academic and professional network.

Klappentext

This textbook is ideal for learning and understanding more advanced data and analytical techniques in marketing analytics. Advanced Marketing Analytics by Nasir Salari provides postgraduate students with a clear and comprehensive pathway through the advanced concepts, methods and applications that define modern marketing analytics. Designed for students undertaking marketing analytics courses or degrees, it supports learners in developing critical data literacy and analytical skills, even with little or no prior coding experience. This textbook builds a strong foundation across all three key areas of marketing analytics: descriptive, predictive and prescriptive, showing how each contributes to better marketing insight and decision making. It explores no-code to low-code analytical approaches, data preparation, A/B testing, Market Basket Analysis and the integration of AI, machine learning and big data into marketing practice. Understand how marketers use cluster analysis, data mining, visualisation, segmentation and other techniques to understand consumers, optimize campaigns and deliver measurable results. Learning features include: - defined learning objectives and practical exercises for structured study - discussion questions and a key terms and formulae list to reinforce critical thinking - online resources with PowerPoint slides Combining academic rigor with industry practice, Advanced Marketing Analytics equips postgraduate students with the analytical mindset and practical tools to turn complex marketing data into strategical, evidence-based insights.

Inhalt

Chapter - 01: Introduction to marketing analytics; Chapter - 02: Understanding and preparing data for marketing analytics Chapter - 03: Predictive analytics techniques in marketing; Chapter - 04: Advanced analytical techniques; Chapter - 05: Prescriptive analytics and optimisation in marketing; Chapter - 06: Tools and technologies for marketing analytics; Chapter - 07: Ethical considerations and future trends;