This book presents the foundations of using analytics from the laboratory, social media platforms, and the web. The authors cover key topics including analytics strategy, data gathering approaches, data preprocessing, data quality assessment, analytical methods, tools, and validation methods. The book includes chapters explaining web analytics, social media analytics, and how to create an analytics strategy. The authors also cover on data sources, such as online surveys, crowdsourcing, eye tracking, mouse tracking, social media APIs, search logs, and analytics triangulation. The book also discusses analytical tools for social media analytics, search analytics, persona analytics, user studies, and website analytics. The authors conclude by examining the validity of online analytics.

Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools—data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.

It is long past time to take business ethics seriously. This is not because business people feel the need to appear virtuous, attentive to sustainability, or devoted to their stakeholders, but because business ethics can offer a competitive advantage to companies that prioritize it. A strong reputation and trustworthiness reduce transaction costs with partners, foster loyalty among employees, and attract top young talent. This book explores the many ways companies around the world can achieve such a competitive advantage. Use this volume to stay informed in this field, which will only grow in importance as technology continues to shed light on who provides the goods and services we rely on.

This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References

Audience and media analytics is more important now than ever, and this latest volume in the cutting-edge BEA Electronic Media Research Series collects some of the top scholars working with big data and analytics today. These chapters describe the development and help define media analytics as an academic discipline and professional practice. Understanding audiences is integral to creating and distributing media messages and the study of media analytics requires knowing a range of skills including research methods, the necessary tools available, familiarity with statistical procedures, and a mindset to provide insights and apply findings. This book summarizes the insights of analytics practitioners regarding the current state of legacy media analysis and social media analytics. Topics covered include the evolution of media technologies, the teaching of media measurement and analytics, the transition taking place in media research, and the use of media analytics to answer meaningful questions, drive content creation, and engage with audiences.

This practical content guide empowers businesses to understand, identify and act on big-data opportunities, producing superior business insights for prolific marketing gains.

Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.