Mastering Business Analytics – serie

This second edition of Essentials of Pricing Analytics provides a comprehensive introduction to pricing as a tactical business function and is a practical toolbox for implementing solutions to diverse pricing challenges.Beyond theoretical perspectives, the second edition of Essentials of Pricing Analytics demonstrates practical implementations of analytical tools using global case studies. Covering fundamental pricing theory, break-even analysis, price sensitivity, optimization techniques, revenue management, and ethical considerations, the updated edition features new content on price differentiation, and AI applications in pricing strategy. It also expands on implementation examples to include R and Python alongside Excel.This accessible text is ideal for advanced undergraduate, MBA, and postgraduate students of pricing strategy, entrepreneurship, marketing strategy, and operations, as well as practitioners seeking effective methods to implement pricing strategies and maximize profits.Online resources include Excel templates, R and Python scripts for most examples covered in the book, a comprehensive test bank, and PowerPoint slides for each chapter.

This second edition of Digital Analytics for Marketing provides students with a comprehensive overview of the tools needed to measure digital activity and implement best practices when using data to inform marketing strategy. It is the first text of its kind to introduce students to analytics platforms from a practical marketing perspective.Demonstrating how to integrate large amounts of data from web, digital, social, and search platforms, this helpful guide offers actionable insights into data analysis, explaining how to "connect the dots" and "humanize" information to make effective marketing decisions. The authors cover timely topics, such as social media, web analytics, marketing analytics challenges, and dashboards, helping students to make sense of business measurement challenges, extract insights, and take effective actions. The book’s experiential approach, combined with chapter objectives, summaries, and review questions, will engage readers, deepening their learning by helping them to think outside the box.Filled with engaging, interactive exercises and interesting insights from industry experts, this book will appeal to undergraduate and postgraduate students of digital marketing, online marketing, and analytics.Online support materials for this book include an instructor’s manual, test bank, and PowerPoint slides.

This second edition of Digital Analytics for Marketing provides students with a comprehensive overview of the tools needed to measure digital activity and implement best practices when using data to inform marketing strategy. It is the first text of its kind to introduce students to analytics platforms from a practical marketing perspective.Demonstrating how to integrate large amounts of data from web, digital, social, and search platforms, this helpful guide offers actionable insights into data analysis, explaining how to "connect the dots" and "humanize" information to make effective marketing decisions. The authors cover timely topics, such as social media, web analytics, marketing analytics challenges, and dashboards, helping students to make sense of business measurement challenges, extract insights, and take effective actions. The book’s experiential approach, combined with chapter objectives, summaries, and review questions, will engage readers, deepening their learning by helping them to think outside the box.Filled with engaging, interactive exercises and interesting insights from industry experts, this book will appeal to undergraduate and postgraduate students of digital marketing, online marketing, and analytics.Online support materials for this book include an instructor’s manual, test bank, and PowerPoint slides.

This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing.Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies.Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management.Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters.

This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing.Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies.Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management.Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters.

Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading. This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.

Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading. This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.

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.

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.

Supply Chain Analytics, second edition, introduces the reader to data analytics and demonstrates the value of its effective use in the improvement of supply chain (SC) process performance. By describing four key SC processes and illustrating – through worked examples – how the descriptive, predictive, and prescriptive analytic methods can be applied to enhance those processes, this book presents a more comprehensive learning experience for the reader than has been offered previously.Key topics and issues are addressed, including the capriciousness of modern SC operating environments; the imperative of SC sustainability; the need for heightened SC risk management; the building of SC resilience; the pursuit of SC optimisation; and the use of big data, data mining, cloud computing, machine learning, artificial intelligence (AI), and importantly the social issues confronting SC analysts in carrying out their work.The author identifies four core SC processes – strategy, design, execution, and people – to which the analytic techniques explained can be applied to ensure continuous performance improvement and the growth of competitive advantage.Pedagogy to aid learning is incorporated throughout, including an opening section for each chapter explaining the intended learning outcomes; worked examples illustrating how each analytic technique works, how it is applied, and what to be careful of; tables, diagrams, and equations to help ‘visualise’ the concepts and methods covered; end-of-chapter case studies; review questions; and assignment tasks.Providing both management expertise and technical skills, which are essential to decision-makers in the SC, this textbook is an essential reading for advanced undergraduate and postgraduate students of SC analytics, SC leaders, and SC operations management professionals. Its practice-based and applied approach also makes it valuable for teaching academics, organisational trainers and coaches, operating SC practitioners, and those pursuing professional qualifications.Online resources include chapter-by-chapter PowerPoint slides, tutorial exercises, written assignments, worked examples using Excel, and a test bank of exam questions.

Supply Chain Analytics, second edition, introduces the reader to data analytics and demonstrates the value of its effective use in the improvement of supply chain (SC) process performance. By describing four key SC processes and illustrating – through worked examples – how the descriptive, predictive, and prescriptive analytic methods can be applied to enhance those processes, this book presents a more comprehensive learning experience for the reader than has been offered previously.Key topics and issues are addressed, including the capriciousness of modern SC operating environments; the imperative of SC sustainability; the need for heightened SC risk management; the building of SC resilience; the pursuit of SC optimisation; and the use of big data, data mining, cloud computing, machine learning, artificial intelligence (AI), and importantly the social issues confronting SC analysts in carrying out their work.The author identifies four core SC processes – strategy, design, execution, and people – to which the analytic techniques explained can be applied to ensure continuous performance improvement and the growth of competitive advantage.Pedagogy to aid learning is incorporated throughout, including an opening section for each chapter explaining the intended learning outcomes; worked examples illustrating how each analytic technique works, how it is applied, and what to be careful of; tables, diagrams, and equations to help ‘visualise’ the concepts and methods covered; end-of-chapter case studies; review questions; and assignment tasks.Providing both management expertise and technical skills, which are essential to decision-makers in the SC, this textbook is an essential reading for advanced undergraduate and postgraduate students of SC analytics, SC leaders, and SC operations management professionals. Its practice-based and applied approach also makes it valuable for teaching academics, organisational trainers and coaches, operating SC practitioners, and those pursuing professional qualifications.Online resources include chapter-by-chapter PowerPoint slides, tutorial exercises, written assignments, worked examples using Excel, and a test bank of exam questions.

Practical Supply Chain and Logistics Analytics provides essential analytical techniques for managing distribution, transportation, inventory, manufacturing, network design, customer logistics, and procurement across the supply chain.This book delivers practical decision-analysis methodologies that supply chain professionals can immediately implement in their daily operations. Readers will gain a working knowledge of fundamental logistics analytical methods that offer critical quantitative perspectives for better decision-making. The text presents a comprehensive range of techniques with step-by-step guidance, real-world examples, and actionable insights that bridge theory and practice. Each chapter builds analytical competency through accessible explanations and implementable frameworks, enabling professionals to address specific logistics management challenges efficiently while developing their quantitative skill set for long-term career advancement.University lecturers will find it complements traditional supply chain textbooks and can also serve as the primary text for a first supply chain analytics class, while logistics professionals at all levels can use it as a reference guide for developing analyses to address specific management decisions.

Practical Supply Chain and Logistics Analytics provides essential analytical techniques for managing distribution, transportation, inventory, manufacturing, network design, customer logistics, and procurement across the supply chain.This book delivers practical decision-analysis methodologies that supply chain professionals can immediately implement in their daily operations. Readers will gain a working knowledge of fundamental logistics analytical methods that offer critical quantitative perspectives for better decision-making. The text presents a comprehensive range of techniques with step-by-step guidance, real-world examples, and actionable insights that bridge theory and practice. Each chapter builds analytical competency through accessible explanations and implementable frameworks, enabling professionals to address specific logistics management challenges efficiently while developing their quantitative skill set for long-term career advancement.University lecturers will find it complements traditional supply chain textbooks and can also serve as the primary text for a first supply chain analytics class, while logistics professionals at all levels can use it as a reference guide for developing analyses to address specific management decisions.