The second edition of Consumer Behaviour and Analytics provides a consumer behaviour textbook for the new marketing reality. In a world of Big Data, machine learning and artificial intelligence, this key text reviews the issues, research and concepts essential for navigating this new terrain. It demonstrates how we can use data-driven insight and merge this with insight from extant research to inform knowledge-driven decision-making.
Adopting a practical and managerial lens, while also exploring the rich lineage of academic consumer research, this textbook approaches its subject from a refreshing and original standpoint. It contains numerous accessible examples, scenarios and exhibits, and condenses the disparate array of relevant work into a workable, coherent, synthesized and readable whole. Providing an effective tour of the concepts and ideas most relevant in the age of analytics-driven marketing (from data visualization to semiotics), the book concludes with an adaptive structure to inform managerial decision-making.
Consumer Behaviour and Analytics provides a unique distillation from a vast array of social and behavioural research merged with the knowledge potential of digital insight. It offers an effective and efficient summary for undergraduate, postgraduate or executive courses in consumer behaviour and marketing analytics, and also functions as a supplementary text for other marketing modules. Online resources include PowerPoint slides.
List of figures
List of tables
Preface
Acknowledgements
Chapter 1 An introduction to consumer analytics
Chapter 2 Purchase insight and the anatomy of transactions
Chapter 3 Web and social activity
Chapter 4 Extant research, decision-making and exogenous cognition
Chapter 5 Elemental features of consumer choice: needs, economics, deliberation and impulse.
Chapter 6 Perceptual and communicative features of consumer choice
Chapter 7 Individual and social features of consumption
Chapter 8 Knowledge-driven marketing and the Modular Adaptive Dynamic Schematic
Index
Biography
Andrew Smith, BSc, MSc, PhD, is the founding Director of the transdisciplinary N/LAB at Nottingham University Business School, UK, where he is Professor of Consumer Behaviour & Analytics. He is also an associate of The Horizon Institute (for digital economy research). Professor Smith has published numerous papers on consumer behaviour and analytics and worked on a number of funded research projects for Research Councils UK, ESRC, EPSRC, DFID, ERC, Bill and Melinda Gates Foundation, European Union, The Office of Fair Trading and Innovate UK, among others. These projects have involved various entities, multinationals and NGOs (including Co-op, Walgreens Boots Alliance, World Bank Group, Tesco, IPSOS and Experian, among others). In 2023, he received a Leverhulme Trust Fellowship award.
'Consumer marketing is increasingly analytics driven, with data driven insight the core underpinning of many businesses. Consumer Behaviour and Analytics is a concise, inventive, original and accessible text that develops new approaches, concepts and structure to fit the new reality of analytics driven marketing. Linking new possibilities and approaches with existing academic consumer research, and grounded in examples and exhibits, this book is a ground-breaking and informative volume.'– Leigh Sparks, Professor of Retail Studies and Deputy Principal, University of Stirling, Scotland
'The effects of Big Data, machine learning and AI on the terrain of marketing and consumer research have been seismic. Smith’s book provides a timely and concise review of this new landscape by demystifying analytics-driven concepts and methods whilst cross-referencing with more traditional fields of consumer knowledge. The book inventively integrates old and new concepts into a framework that will appeal to marketing practitioners and students alike. An absolutely essential read for anyone interested in a well-balanced understanding of contemporary consumer behaviour and analytics.' - Professor Andreas Chatzidakis, Royal Holloway, University of London, UK
