Advanced Marketing Analytics

This textbook takes students on a comprehensive learning journey on more advanced concepts and techniques in marketing analytics, offering support to those with little to no coding experience.
Advanced Marketing Analytics is an essential resource or postgraduate students and covers:
- No-code to low-code analytics solutions
- How to understand data for marketing analytics
- Market Basket Analysis
- A/B testing
- Preparing data for marketing analytics
- Emerging trends in AI, machine learning and big data
This book covers all three areas of marketing analytics such as descriptive, predictive and prescriptive analytics, and includes software tools such as SPSS, Microsoft Excel and Rapid Miner. It also has real-world examples from global companies highlighting and emphasising the importance of why marketers should be more data-analytical.
In-text resources include a glossary, learning outcomes, discussion questions and further reading questions. Online resources include PowerPoint slides for lecturers, and a lecturers' manual with practical exercises and datasets.

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.