The fastest growing brands of the 21st century have succeeded by building and harnessing the power of brand communities. In doing so, they were able to earn engagement and loyalty, with relatively low risk. Community Building for Marketers looks at how brands have successfully mastered community marketing and how you can do it too. Covering everything from how to start and grow a successful community, to setting your community's vision, mission and values, as well as defining what success looks like for you, this book is the ultimate step-by-step guide. With real-world examples from a wide range of companies such as Buffer, Sanity and The TEFL Org, this book is designed to help you succeed at community marketing no matter what type of business you're in. Whether your community is still in its early days or has been around for a while and needs a boost, Community Building for Marketers will help you capitalize upon the opportunities community marketing offers, transforming your customers from passive consumers to active, engaged brand advocates.
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Bowei Chen is an Associate Professor of Marketing Analytics and Data Science at the Adam Smith Business School, University of Glasgow. He is also the Programme Director of the MSc in Finance and Management and an ESRC IAA Reviewer.
Gerhard Kling is a Professor in Finance at the University of Aberdeen. He has worked in higher education for over 18 years (SOAS, University of Southampton, UWE, Utrecht University). His current interests focus on machine learning (ML), artificial intelligence (AI), and their applications in FinTech and Green Finance.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Your essential textbook for mastering business analytics through Python.Business Analytics with Python by Bowei Chen and Gerhard Kling is the definitive guide for upper-level undergraduate and postgraduate students studying business, management or finance. Designed to support analytics modules that prioritize practical application, this textbook introduces students to data-driven decision-making through Python, without assuming a background in computer science. It aligns with course outcomes by integrating statistical, mathematical and machine learning techniques into a unified business context.This textbook takes a holistic approach to business analytics, exploring how Python can be used to interpret and solve real-world problems. From foundational coding skills to the implementation of supervised and unsupervised machine learning methods, students learn how to translate data into insight across key business functions. Through industry-relevant case studies, including customer churn analysis, fraud detection and sales forecasting, learners build confidence in applying analytics to real organizational challenges.Pedagogical features include: - A running case study that reinforces practical learning across chapters - Clear learning objectives and chapter summaries to track progress - Step-by-step exercises and coding activities to build analytical fluency - Examples grounded in real business applications for immediate relevance Whether preparing for exams or building analytical capability for a future career, this textbook equips students with the tools to turn business data into strategic advantage. N° de réf. du vendeur LU-9781398617179
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