Products related to Analytics:
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Data Analytics in Marketing, Entrepreneurship, and Innovation
Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences.Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics.It features case studies that provide realistic examples of applications.This multifaceted examination of data analytics looks at: Business analyticsApplying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analyticsDeveloping new productsTechnopreneurshipDisruptive versus incremental innovationThe book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing.Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery.Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques.Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.
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Digital Analytics for Marketing
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.
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Business Models : Innovation, Digital Transformation, and Analytics
Since the beginning of time, running a business has involved using logic by which the business operates.This logic is called the business model in management science, which increasingly is focusing on issues surrounding business models.Research trends related to business models include value creation, value chain operationalization, and social and ecological aspects, as well as innovation and digital transformation.Business Models: Innovation, Digital Transformation, and Analytics examines how innovation, digital transformation, and the composition of value affect the existence and development of business models.The book starts by addressing the conceptual development of business models and by discussing the essence of innovation in those models.Chapters in the book investigate how: Business models can analyze digital transformation scenarios Individual business model elements effect selected performance measures as well as how the elements are significant for the enterprise value composition The environment effects the profitability of the high-growth enterprise business models Employer branding business models are perceived by the generation Z workforce To implement responsible business models in the enterprise Cyber risk is captured in business models Decision algorithms are important to business analyticsThis book is a compendium of knowledge about the use of business models in the context of innovative activities, digital transformation, and value composition.It attempts to combine the theory and practice and offers a look at business models currently used in companies, especially high-growth enterprises, in various countries of the world and indicates the prospects for their development.
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Data Analytics for Business : Lessons for Sales, Marketing, and Strategy
Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down.This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications.The foundation of this text is the author’s 20-plus years of developing and delivering big data and artificial intelligence solutions across multiple industries: financial services, pharmaceuticals, consumer packaged goods, media, and retail.He provides guidelines and summarized cases for those studying or working in the fields of data science, data engineering, and business analytics.The book also offers a distinctive style: a series of essays, each of which summarizes a critical lesson or provides a step-by-step business process, with specific examples of successes and failures. Sales and marketing executives, project managers, business and engineering professionals, and graduate students will find this clear and comprehensive book the ideal companion when navigating the complex world of big data analytics.
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Are Instagram analytics apps legal?
Yes, Instagram analytics apps are legal as long as they comply with Instagram's terms of service and data privacy regulations. These apps provide users with insights and data about their Instagram account performance, such as follower growth, engagement metrics, and audience demographics. It is important to choose a reputable analytics app that prioritizes user privacy and data security to ensure compliance with legal requirements.
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Where can one study Biomedical Analytics?
One can study Biomedical Analytics at various universities and colleges that offer programs in health informatics, bioinformatics, or biomedical data science. Some well-known institutions that offer programs in Biomedical Analytics include Stanford University, Harvard University, Johns Hopkins University, and the University of California, Los Angeles. Additionally, there are online programs and professional certifications available for those looking to specialize in Biomedical Analytics.
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Which offers better opportunities in the job market: developing a data analytics app or web development?
Both developing a data analytics app and web development offer great opportunities in the job market, but the demand for data analytics skills is currently higher. Data analytics is a rapidly growing field, and businesses are increasingly relying on data to make informed decisions. Developing a data analytics app requires skills in data analysis, programming, and understanding of business needs, making it a valuable skill set in the job market. However, web development also offers great opportunities, especially with the increasing demand for online presence and e-commerce. Ultimately, both fields offer promising career prospects, but data analytics may currently have a slight edge in the job market.
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How can I access external YouTube analytics?
To access external YouTube analytics, you can use YouTube's Analytics API. This API allows you to retrieve data and metrics from your YouTube channel and videos programmatically. You will need to set up a project in the Google Developers Console, obtain API credentials, and then use these credentials to make requests to the Analytics API. This will allow you to access detailed analytics data such as views, watch time, and audience demographics for your YouTube content.
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ISE Predictive Analytics for Business Strategy
Designed for courses that provide a conceptual and broad-based introduction to econometrics and business analytics, Predictive Analytics for Business Strategy, 1st edition provides future managers with a basic understanding of what data can do in forming business strategy without getting into a taxonomy of models and their statistical properties.Through engaging questions, explanations, and applications, students develop a deeper understanding of the fundamental reasoning behind how and why analysis can generate actionable knowledge and learn to think critically about whether a given analysis has merit or not.
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Business Analytics
Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 4E.You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills.Real examples and memorable visuals illustrate data and results for each topic.Step-by-step instructions guide you through using Microsoft® Excel, Tableau, R, and JMP Pro software to perform even advanced analytics concepts.Practical, relevant problems at all levels of difficulty further help you apply what you've learned.This edition assists you in becoming proficient in topics beyond the traditional quantitative concepts, such as data visualization and data mining, which are increasingly important in today's analytical problem solving.MindTap digital learning resources with an interactive eBook, algorithmic practice problems with solutions and Exploring Analytics visualizations strengthen your understanding of key concepts.
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Marketing Strategy : Based on First Principles and Data Analytics
Marketing Strategy offers a unique and dynamic approach based on four underlying principles that underpin marketing today: All customers differ; All customers change; All competitors react; and All resources are limited.The structured framework of this acclaimed textbook allows marketers to develop effective and flexible strategies to deal with diverse marketing problems under varying circumstances.Uniquely integrating marketing analytics and data driven techniques with fundamental strategic pillars the book exemplifies a contemporary, evidence-based approach.This base toolkit will support students’ decision-making processes and equip them for a world driven by big data.The second edition builds on the first’s successful core foundation, with additional pedagogy and key updates. Research-based, action-oriented, and authored by world-leading experts, Marketing Strategy is the ideal resource for advanced undergraduate, MBA, and EMBA students of marketing, and executives looking to bring a more systematic approach to corporate marketing strategies. New to this Edition:- Revised and updated throughout to reflect new research and industry developments, including expanded coverage of digital marketing, influencer marketing and social media strategies- Enhanced pedagogy including new Worked Examples of Data Analytics Techniques and unsolved Analytics Driven Case Exercises, to offer students hands-on practice of data manipulation as well as classroom activities to stimulate peer-to-peer discussion- Expanded range of examples to cover over 250 diverse companies from 25 countries and most industry segments- Vibrant visual presentation with a new full colour designAccompanying online resources for this title can be found at bloomsburyonlineresources.com/marketing-strategy-2e.These resources are designed to support teaching and learning when using this textbook and are available at no extra cost.
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Applied Marketing Analytics Using R
Marketing has become increasingly data-driven in recent years as a result of new emerging technologies such as AI, granular data availability and ever-growing analytics tools.With this trend only set to continue, it’s vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success. Taking a very hands-on approach with the use of real-world datasets, case studies and R (a free statistical package), this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks.Chapters include learning objectives, figures, tables and questions to help facilitate learning. Supporting online resources are available to instructors to support teaching, including datasets and software codes and solutions (R Markdowns, HTML files) as well as PowerPoint slides, a teaching guide and a testbank. This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers. Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London. Dr. Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.
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How can one use plausible analytics with a web app on a server?
Plausible analytics can be used with a web app on a server by integrating the Plausible tracking code into the web app's codebase. This tracking code will then collect data on user interactions and behavior on the web app. The data collected can be analyzed to gain insights into user engagement, popular features, and areas for improvement. By using Plausible analytics, developers can make data-driven decisions to optimize the web app for better user experience and performance.
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What is the question for evaluation in Google Analytics?
The question for evaluation in Google Analytics is typically focused on understanding user behavior and website performance. It could be something like "What are the top pages on my website in terms of traffic and engagement?" or "How are users finding my website and what are the most effective acquisition channels?" These questions help businesses and website owners to analyze and optimize their online presence for better performance and user experience.
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Can someone explain to me what Google Analytics is?
Google Analytics is a web analytics service offered by Google that allows website owners to track and analyze their website traffic. It provides valuable insights into how users interact with a website, including information about the number of visitors, their demographics, the pages they visit, and how they found the website. This data can help website owners make informed decisions about their marketing strategies, content, and user experience to improve their website's performance. Overall, Google Analytics is a powerful tool for understanding and optimizing website traffic.
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How can the Google Analytics cookie be a first-party cookie?
The Google Analytics cookie can be a first-party cookie because it is set by the website domain that the user is visiting. When a user visits a website that uses Google Analytics, the website sets the Google Analytics cookie on the user's browser. This means that the cookie is considered a first-party cookie because it is set by the same domain that the user is interacting with. As a result, the cookie can be used to track and analyze user behavior on that specific website.
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