The rapid growth of technological developments on the internet has led many companies to adapt their businesses to the digital ecosystem and implement new methods and techniques to improve the users' experiences and their analytical strategies. Moreover, in the past few years, the digital ecosystem has been chosen as the main channel used by consumers for the purchase of goods and services. As a result, digital marketing and online advertising have become the main strategies used by companies in their marketing actions. Advertising can be designed and shown considering users' interests based on what they visit or where they go. That implies that the user experience is improved as long as they receive personalized adverts focused on what they were curious or concerned about. Thus, techniques such as artificial intelligence (AI), data mining, or business intelligence have allowed companies to act accordingly in real-time without user perception. Big Data Marketing Strategies for Superior Customer Experience compiles and studies the major practices and case studies of big data marketing in recent years. In this digital era, this book can be used as a sourcebook on study cases focused on digital marketing strategies as well as the identification of new technologies that will help the development of initiatives and practices focused on marketing and data sciences. Covering topics such as customer satisfaction, collective intelligence, and sentiment analysis, this premier reference source is an essential resource for students and educators of higher education, marketers, innovators, business leaders and managers, entrepreneurs, librarians, researchers, and academicians.

In the last decade, the development of new technologies has made innovation a fundamental pillar of education. Teaching innovation is characterized by digital, technological, and didactic elements and processes to improve design-thinking in the teaching field. Therefore, teaching innovation includes the evolution of both teaching and learning models to drive improvements in educational methodologies. In this context, one of the research areas that has been most relevant to date in teaching innovation is university communities and higher education centers. Teaching innovation is a pioneer in the understanding and comprehension of the different teaching methodologies and models developed in the academic area. In this way, teaching innovation is a process that seeks validation in the academic and teaching communities at universities in order to promote the improvement of teaching and its practices and uses in the future characterized by digital development and data-based methods. The development of new teaching innovation methodologies and practices at universities is the challenge of the 21st century for the development of a resilient and efficient education. Therefore, this edited book aims to compile and study the major practices and case studies of teaching innovation developed in recent years at universities. In this way, teachers and educators can use the contributions presented in this book based on teaching processes, practices, case studies, and interactive activities. In this digital era, this book can be used as a sourcebook on study cases focused on teaching innovation methodologies as well as on the identification of new technologies that will help the development of initiatives and practices focused on teaching innovation at universities.

In today's global culture where the internet has established itself as a main tool of communication, the global system of economy and regulations, as well as data and decisions based on data analysis, have become essential for public actors and institutions. Governments need to be updated and use the latest technologies to understand what society's demands are, and user behavioral data, which can be pulled by intelligent applications, can offer tremendous insights into this. Application of Artificial Intelligence in Government Practices and Processes identifies definitional perspectives of behavioral data science and what its use by governments means for automation, predictability, and risks to privacy and free decision making in society. Many governments can train their algorithms to work with machine learning, leading to the capacity to interfere in the behavior of society and potentially achieve a change in societal behavior without society itself even being aware of it. As such, the use of artificial intelligence by governments has raised concerns about privacy and personal security issues. Covering topics such as digital democracy, data extraction techniques, and political communications, this book is an essential resource for data analysts, politicians, journalists, public figures, executives, researchers, data specialists, communication specialists, digital marketers, and academicians.

In the last decade, the use of data sciences in the digital marketing environment has increased. Digital marketing has transformed how companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the internet has given rise to new business models based on the bidirectionality of communication between companies and internet users. Digital marketing, new business models, data-driven approaches, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies are beginning to see the digital ecosystem as not only the present but also the future. However, despite these advances, relevant evidence on the measures to improve the management of data sciences in digital marketing remains scarce. Advanced Digital Marketing Strategies in a Data-Driven Era contains high-quality research that presents a holistic overview of the main applications of data sciences to digital marketing and generates insights related to the creation of innovative data mining and knowledge discovery techniques applied to traditional and digital marketing strategies. The book analyzes how companies are adopting these new data-driven methods and how these strategies influence digital marketing. Discussing topics such as digital strategies, social media marketing, big data, marketing analytics, and data sciences, this book is essential for marketers, digital marketers, advertisers, brand managers, managers, executives, social media analysts, IT specialists, data scientists, students, researchers, and academicians in the field.

The rapid growth of technological developments on the internet has led many companies to adapt their businesses to the digital ecosystem and implement new methods and techniques to improve the users' experiences and their analytical strategies. Moreover, in the past few years, the digital ecosystem has been chosen as the main channel used by consumers for the purchase of goods and services. As a result, digital marketing and online advertising have become the main strategies used by companies in their marketing actions. Advertising can be designed and shown considering users' interests based on what they visit or where they go. That implies that the user experience is improved as long as they receive personalized adverts focused on what they were curious or concerned about. Thus, techniques such as artificial intelligence (AI), data mining, or business intelligence have allowed companies to act accordingly in real-time without user perception. Big Data Marketing Strategies for Superior Customer Experience compiles and studies the major practices and case studies of big data marketing in recent years. In this digital era, this book can be used as a sourcebook on study cases focused on digital marketing strategies as well as the identification of new technologies that will help the development of initiatives and practices focused on marketing and data sciences. Covering topics such as customer satisfaction, collective intelligence, and sentiment analysis, this premier reference source is an essential resource for students and educators of higher education, marketers, innovators, business leaders and managers, entrepreneurs, librarians, researchers, and academicians.

In the last decade, the development of new technologies has made innovation a fundamental pillar of education. Teaching innovation includes the evolution of both teaching and learning models to drive improvements in educational methodologies. Teaching innovation is a pioneer in the understanding and comprehension of the different teaching methodologies and models developed in the academic area. Teaching innovation is a process that seeks validation in the academic and teaching communities at universities in order to promote the improvement and its practices and uses in the future characterized by digital development and data-based methods. Teaching Innovation in University Education: Case Studies and Main Practices features the major practices and case studies of teaching innovation developed in recent years at universities. It is a source on study cases focused on teaching innovation methodologies as well as on the identification of new technologies that will help the development of initiatives and practices focused on teaching innovation at higher education institutions. Covering topics such as didactic strategics, service learning, and technology-based gamification, this premier reference source is an indispensable resource for pre-service teachers, lecturers, students, faculty, administrators, libraries, entrepreneurs, researchers, and academicians.

In the last decade, the use of data sciences in the digital marketing environment has increased. Digital marketing has transformed how companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the internet has given rise to new business models based on the bidirectionality of communication between companies and internet users. Digital marketing, new business models, data-driven approaches, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies are beginning to see the digital ecosystem as not only the present but also the future. However, despite these advances, relevant evidence on the measures to improve the management of data sciences in digital marketing remains scarce. Advanced Digital Marketing Strategies in a Data-Driven Era contains high-quality research that presents a holistic overview of the main applications of data sciences to digital marketing and generates insights related to the creation of innovative data mining and knowledge discovery techniques applied to traditional and digital marketing strategies. The book analyzes how companies are adopting these new data-driven methods and how these strategies influence digital marketing. Discussing topics such as digital strategies, social media marketing, big data, marketing analytics, and data sciences, this book is essential for marketers, digital marketers, advertisers, brand managers, managers, executives, social media analysts, IT specialists, data scientists, students, researchers, and academicians in the field.