Artificial Intelligence Marketing and Predicting Consumer Choice


Book Description

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.




Predicting and Changing Behavior


Book Description

This book describes the reasoned action approach, an integrative framework for the prediction and change of human social behavior. It provides an up-to-date review of relevant research, discusses critical issues related to the reasoned action framework, and provides methodological and conceptual tools for the prediction and explanation of social behavior and for designing behavior change interventions.




Enhancing and Predicting Digital Consumer Behavior with AI


Book Description

Understanding consumer behavior in today's digital landscape is more challenging than ever. Businesses must navigate a sea of data to discern meaningful patterns and correlations that drive effective customer engagement and product development. However, the ever-changing nature of consumer behavior presents a daunting task, making it difficult for companies to gauge the wants and needs of their target audience accurately. Enhancing and Predicting Digital Consumer Behavior with AI offers a comprehensive solution to this pressing issue. A strong focus on concepts, theories, and analytical techniques for tracking consumer behavior changes provides the roadmap for businesses to navigate the complexities of the digital age. By covering topics such as digital consumers, emotional intelligence, and data analytics, this book serves as a timely and invaluable resource for academics and practitioners seeking to understand and adapt to the evolving landscape of consumer behavior.




Artificial Intelligence for Marketing


Book Description

A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.




Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)


Book Description

This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. These endeavors have made new contribution to globalization and creating a community of shared future. With the rapid development of modern economic society, in the process of economic management, informatization has become the mainstream of economic development in the future. At the same time, with the emergence of advanced management technologies such as blockchain technology and big data technology, real market information can be quickly obtained in the process of economic management, which greatly reduces the operating costs of the market economy and effectively enhances the management level of operators, thus contributing to the sustained, rapid and healthy development of the market economy. Under the new situation, the innovative application of economic management research is of great practical significance. 2022 International Conference on Bigdata, Blockchain and Economic Management (ICBBEM 2022) will be held on March 25–27, 2022 in Wuhan, China. ICBBEM 2022 will focus on the latest fields of Bigdata, Blockchain and Economic Management to provide an international platform for experts, professors, scholars and engineers from universities, scientific institutes, enterprises and government-affiliated institutions at home and abroad to share experiences, to expand professional fields, to exchange new ideas face to face, to present research results, and to discuss the key challenging issues and research directions facing the development of this field, with a view to promoting the development and application of theories and technologies in universities and enterprises.




Handbook of Consumer Psychology


Book Description

This Handbook contains a unique collection of chapters written by the world's leading researchers in the dynamic field of consumer psychology. Although these researchers are housed in different academic departments (ie. marketing, psychology, advertising, communications) all have the common goal of attaining a better scientific understanding of cognitive, affective, and behavioral responses to products and services, the marketing of these products and services, and societal and ethical concerns associated with marketing processes. Consumer psychology is a discipline at the interface of marketing, advertising and psychology. The research in this area focuses on fundamental psychological processes as well as on issues associated with the use of theoretical principles in applied contexts. The Handbook presents state-of-the-art research as well as providing a place for authors to put forward suggestions for future research and practice. The Handbook is most appropriate for graduate level courses in marketing, psychology, communications, consumer behavior and advertising.




Handbook of Research Methods in Consumer Psychology


Book Description

What impact can various research methods have on consumer psychology? How can they help us understand the workings of the consumer mind? And how can the field of consumer psychology best utilize these methods? In the Handbook of Research Methods in Consumer Psychology, leading consumer psychologists summarize key aspects of the research process and explain how different methods enrich understanding of how consumers process information to form judgments and opinions and to make consumption-related decisions. Kardes, Herr, and Schwarz provide an in-depth analysis of the scientific research methods needed to understand consumption-related judgments and decisions. The book is split into five parts, demonstrating the breadth of the volume: classic approaches, contemporary approaches, online research methods, data analysis, and philosophy of science. A variety of leading researchers give insight into a wide range of topics, reflecting both long-standing debate and more recent developments in the field to encourage discussion and the advancement of consumer research. The Handbook of Research Methods in Consumer Psychology is essential reading for researchers, students, and professionals interested in consumer psychology and behavior.




Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era


Book Description

The emergence of new technologies within the industrial revolution has transformed businesses to a new socio-digital era. In this new era, businesses are concerned with collecting data on customer needs, behaviors, and preferences for driving effective customer engagement and product development, as well as for crucial decision making. However, the ever-shifting behaviors of consumers provide many challenges for businesses to pinpoint the wants and needs of their audience. The Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era focuses on the concepts, theories, and analytical techniques to track consumer behavior change. It provides multidisciplinary research and practice focusing on social and behavioral analytics to track consumer behavior shifts and improve decision making among businesses. Covering topics such as consumer sentiment analysis, emotional intelligence, and online purchase decision making, this premier reference source is a timely resource for business executives, entrepreneurs, data analysts, marketers, advertisers, government officials, social media professionals, libraries, students and educators of higher education, researchers, and academicians.




Wiley CPA Examination Review, Outlines and Study Guides


Book Description

The #1 CPA exam review self-study leader The CPA exam review self-study program more CPA candidates turn to take the test and pass it, Wiley CPA Exam Review 39th Edition contains more than 4,200 multiple-choice questions and includes complete information on the Task Based Simulations. Published annually, this comprehensive two-volume paperback set provides all the information candidates need to master in order to pass the new Uniform CPA Examination format. Features multiple-choice questions, new AICPA Task Based Simulations, and written communication questions, all based on the new CBT-e format Covers all requirements and divides the exam into 47 self-contained modules for flexible study Offers nearly three times as many examples as other CPA exam study guides With timely and up-to-the-minute coverage, Wiley CPA Exam Review 39th Edition covers all requirements for the CPA Exam, giving the candidate maximum flexibility in planning their course of study—and success.




Modeling Techniques in Predictive Analytics


Book Description

Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you're new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you're already a modeler, programmer, or manager, it will teach you crucial skills you don't yet have. This guide illuminates the discipline through realistic vignettes and intuitive data visualizations-not complex math. Thomas W. Miller, leader of Northwestern University's pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today's key applications for predictive analytics, delivering skills and knowledge to put models to work-and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively.