Advanced Marketing Analytics

Nasir Salari has written a definitive guide for the modern analytics era. While the book is rigorously focused on marketing, its frameworks are so robust that I found it equally valuable for two distinct purposes: refining a complex corporate marketing report and adopting it for my Master's level Management Information Simulation module.
The inclusion of real-world datasets, such as the bike-sharing case studies, alongside critical topics like Exploratory Data Analysis and unsupervised learning, makes this an invaluable resource. It is rare to find a text that bridges the gap between industry application and academic curriculum so effectively.

Nasir Salari's new book 'Advanced Marketing Analytics' is relatively concise yet is very rich in content: ranging from simpler to complicated techniques and from structured to unstructured data processing. I have come across many marketing analytics books in the market but Dr Salari's new book offers something unique. It integrates the three pillars - concepts, techniques and software packages - of advanced marketing analytics brilliantly and is written in a very clear and logical language. What's more, the book is properly arranged so that readers can choose to follow it from start to end to learn the totality of knowledge delivered in the book or choose to focus on one or more separate chapters for their specific task purpose. Similarly, readers can also choose to learn and follow the Python language embedded in the book or choose the no-code or point-and-click route if they prefer to skip the programme language.
To summarise, Dr Salari's new book's richness in content, seamless integration of concepts, techniques and software packages as well as modularity arrangement makes it a potential stand-out winner in the market.

Advanced Marketing Analytics presents a comprehensive and contemporary examination of the role of data, technology, and advanced analytical tools in understanding consumer behaviour and supporting informed marketing decision-making in today's dynamic business environment. The book effectively bridges theory and practice, enabling students and professionals to transform large volumes of digital data into actionable insights for strategy development, performance measurement, customer prediction, and marketing optimization.
The inclusion of dedicated chapters on Segmentation and Clustering and Advanced Regression in Marketing significantly enhances the book's academic depth and practical relevance by introducing modern machine learning concepts such as supervised and unsupervised learning, K-Nearest Neighbours (KNN), and advanced regression techniques aligned with current industry standards. Furthermore, the clear and engaging treatment of natural language processing (NLP) and A/B testing demonstrates the author's strong command of contemporary analytical methods and their real-world marketing applications. Overall, the book is highly relevant and well-positioned to prepare readers for advanced studies and professional roles in an increasingly data-driven and analytics-focused marketing landscape.