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| examples of marketing analytics: Cutting-edge Marketing Analytics Rajkumar Venkatesan, Paul Farris, Ronald T. Wilcox, 2015 Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics. For each marketing problem, the authors help you: Identify the right data and analytics techniques Conduct the analysis and obtain insights from it Outline what-if scenarios and define optimal solutions Connect your insights to strategic decision-making Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of: The real value of marketing analytics How to integrate quantitative analysis with managerial sensibility How to apply linear regression, logistic regression, cluster analysis, and Anova models The crucial role of careful experimental design For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics |
| examples of marketing analytics: Marketing Analytics Mike Grigsby, 2018-04-03 Who is most likely to buy and what is the best way to target them? How can businesses improve strategy without identifying the key influencing factors? The second edition of Marketing Analytics enables marketers and business analysts to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, this book offers a welcome handbook on how statistics, consumer analytics and modelling can be put to optimal use. The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage. |
| examples of marketing analytics: Marketing Analytics Wayne L. Winston, 2014-01-08 Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel. |
| examples of marketing analytics: R for Marketing Research and Analytics Chris Chapman, Elea McDonnell Feit, 2015-03-25 This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications. |
| examples of marketing analytics: Marketing Analytics Stephan Sorger, 2013-01-31 Offers marketing students and professionals a practical guide to strategic decision models and marketing metrics. The tools described in the book will aid marketers in making intelligent decisions to drive revenue and results in their organizations. |
| examples of marketing analytics: Handbook of Marketing Analytics Natalie Mizik, Dominique M. Hanssens, 2018 Marketing Science contributes significantly to the development and validation of analytical tools with a wide range of applications in business, public policy and litigation support. The Handbook of Marketing Analytics showcases the analytical methods used in marketing and their high-impact real-life applications. Fourteen chapters provide an overview of specific marketing analytic methods in some technical detail and 22 case studies present thorough examples of the use of each method in marketing management, public policy, and litigation support. All contributing authors are recognized authorities in their area of specialty. |
| examples of marketing analytics: The Definitive Guide to Marketing Analytics and Metrics (Collection) Cesar Brea, Rajkumar Venkatesan, Paul Farris, Ronald T. Wilcox, Neil Bendle, Phillip Pfeifer, David Reibstein, 2014-08-18 A brand new collection introducing today's most powerful strategies and techniques for measuring and optimizing marketing… 3 authoritative books, now in a convenient e-format, at a great price! 3 authoritative Books help you measure, analyze, and optimize every marketing investment you'll ever make Measuring and optimize your marketing investments is more crucial than ever. But, with an explosion in channels and complexity, it's also more challenging than ever. Fortunately, marketing metrics and analytics have taken giant leaps forward in recent years: techniques now exist for accurately quantifying performance and applying what you learn to improve it. In this unique 3 Book package, world-class experts present these new approaches, and show how to profit from them. In Marketing and Sales Analytics, leading consultant Cesar A. Breaexamines the experiences of 15 leaders who've built high-value analytics capabilities in multiple industries. Then, building on what they've learned, he presents a complete blueprint for succeeding with marketing analytics. You'll learn how to evaluate ecosystemic conditions for success, frame the right questions, and organize your people, data, and operating infrastructure to answer them. Brea helps you overcome key challenges ranging from governance to overcoming hidden biases. Along the way, he also offers specific guidance on crucial decisions such as buy vs. build?, centralize or decentralize?, and hire generalists or specialists? Next, in Cutting Edge Marketing Analytics, three pioneering experts introduce today's most valuable marketing analytics methods and tools, and offer a best-practice methodology for successful implementation. They augment this knowledge with hands on case studies, guiding you through solving key problems in resource allocation, segmentation, pricing, campaign management, firm valuation, and digital marketing strategy. All case studies are accompanied by real data used by the protagonists to make decisions. As you practice, you'll gain a deeper understanding of the value of marketing analytics, learn to integrate quantitative analysis with managerial sensibilities, master core statistical tools, and discover how to avoid crucial pitfalls. Finally, in the award-winning Marketing Metrics, Second Edition, Paul W. Farris and his colleagues show how to choose the right metrics for every marketing challenge. You'll learn how to use dashboards to view market dynamics from multiple perspectives, maximize accuracy, and triangulate to optimal solutions. You'll discover high-value metrics for promotional strategy, advertising, distribution, customer perceptions, market share, competitors' power, margins, pricing, products and portfolios, customer profitability, sales forces, channels, and more. This extensively updated edition introduces innovative metrics ranging from Net Promoter to social media and brand equity measurement, and shows how to build comprehensive models to optimize every marketing decision you make. If you need to measure and improve marketing performance, this 3-book package will be your most valuable resource. From world-renowned business sustainability experts Cesar A. Brea, Rajkumar Venkatesan, Paul W. Farris, Ronald T. Wilcox, Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein |
| examples of marketing analytics: Data Science for Marketing Analytics Tommy Blanchard, Debasish Behera, Pranshu Bhatnagar, 2019-03-30 Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. |
| examples of marketing analytics: Marketing Analytics Mike Grigsby, 2015-06-03 Who is most likely to buy and what is the best way to target them? Marketing Analytics enables marketers and business analysts to answer these questions by leveraging proven methodologies to measure and improve upon the effectiveness of marketing programs. Marketing Analytics demonstrates how statistics, analytics and modeling can be put to optimal use to increase the effectiveness of every day marketing activities, from targeted list creation and data segmentation to testing campaign effectiveness and forecasting demand. The author explores many common marketing challenges and demonstrates how to apply different data models to arrive at viable solutions. Business cases and critical analysis are included to illustrate and reinforce key concepts throughout. Beginners will benefit from clear, jargon-free explanations of methodologies relating to statistics, marketing strategy and consumer behaviour. More experienced practitioners will appreciate the more complex aspects of data analytics and data modeling, discovering new applications of various techniques in every day practice. Readers of Marketing Analytics will come away with a firm foundation in markets analytics and the tools they need to gain competitive edge and increase market share. Online supporting resources for this book include a bank of test questions as well as data sets relating to many of the chapters. |
| examples of marketing analytics: Data Science for Marketing Analytics Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali, 2021-09-07 Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily. |
| examples of marketing analytics: Data-Driven Marketing Mark Jeffery, 2010-02-08 NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATION How organizations can deliver significant performance gains through strategic investment in marketing In the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing. Explains how to use data-driven marketing to deliver return on marketing investment (ROMI) in any organization In-depth discussion of the fifteen key metrics every marketer should know Based on original research from America's leading marketing business school, complemented by experience teaching ROMI to executives at Microsoft, DuPont, Nisan, Philips, Sony and many other firms Uses data from a rigorous survey on strategic marketing performance management of 252 Fortune 1000 firms, capturing $53 billion of annual marketing spending In-depth examples of how to apply the principles in small and large organizations Free downloadable ROMI templates for all examples given in the book With every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time. |
| examples of marketing analytics: Predictive Marketing Omer Artun, Dominique Levin, 2015-08-06 Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience. |
| examples of marketing analytics: The Analytical Marketer Adele Sweetwood, 2016-09-13 How to lead the change Analytics are driving big changes, not only in what marketing departments do but in how they are organized, staffed, led, and run. Leaders are grappling with issues that range from building an analytically driven marketing organization and determining the kinds of structure and talent that are needed to leading interactions with IT, finance, and sales and creating a unified view of the customer. The Analytical Marketer provides critical insight into the changing marketing organization—digital, agile, and analytical—and the tools for reinventing it. Written by the head of global marketing for SAS, The Analytical Marketer is based on the author’s firsthand experience of transforming a marketing organization from “art” to “art and science.” Challenged and inspired by their company’s own analytics products, the SAS marketing team was forced to rethink itself in order to take advantage of the new capabilities that those tools offer the modern marketer. Key marketers and managers at SAS tell their stories alongside the author’s candid lessons learned as she led the marketing organization’s transformation. With additional examples from other leading companies, this book is a practical guide and set of best practices for creating a new marketing culture that thrives on and adds value through data and analytics. |
| examples of marketing analytics: Marketing Analytics Robert W. Palmatier, J. Andrew Petersen, Frank Germann, 2022-03-24 Using data analytics and big data in marketing and strategic decision-making is a key priority at many organisations and subsequently a vital part of the skills set for a successful marketing professional operating today. Authored by world-leading authorities in the field, Marketing Analytics provides a thoroughly contemporary overview of marketing analytics and coverage of a wide range of cutting edge data analytics techniques. It offers a powerful framework, organising data analysis techniques around solving four underlying marketing problems: the 'First Principles of Marketing'. In this way, it offers an action-oriented, applied approach to managing marketing complexities and issues, and a sound grounding in making effective decisions based on strong evidence. It is supported by vivid international cases and examples, and applied pedagogical features. The companion website offers comprehensive classroom instruction slides, videos including walk throughs on all the examples and methods in the book, data sets, a test bank and a solution guide for instructors. |
| examples of marketing analytics: Principles of Marketing Engineering, 2nd Edition Gary L. Lilien, Arvind Rangaswamy, Arnaud De Bruyn, 2013 The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering-putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). Marketing Engineering is the systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision process. (For more information on Excel-based models that support these concepts, visit DecisionPro.biz.) We have designed this book primarily for the business school student or marketing manager, who, with minimal background and technical training, must understand and employ the basic tools and models associated with Marketing Engineering. We offer an accessible overview of the most widely used marketing engineering concepts and tools and show how they drive the collection of the right data and information to perform the right analyses to make better marketing plans, better product designs, and better marketing decisions. What's New In the 2nd Edition While much has changed in the nearly five years since the first edition of Principles of Marketing Engineering was published, much has remained the same. Hence, we have not changed the basic structure or contents of the book. We have, however Updated the examples and references. Added new content on customer lifetime value and customer valuation methods. Added several new pricing models. Added new material on reverse perceptual mapping to describe some exciting enhancements to our Marketing Engineering for Excel software. Provided some new perspectives on the future of Marketing Engineering. Provided better alignment between the content of the text and both the software and cases available with Marketing Engineering for Excel 2.0. |
| examples of marketing analytics: Marketing Analytics José Marcos Carvalho de Mesquita, Erik Kostelijk, 2021-11-01 Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading. This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context. |
| examples of marketing analytics: Marketing and Sales Analytics Cesar A. Brea, 2014 Today, an effective marketing analytics executive is even more important than a brilliant data scientist. That's because successful analytics investments now require managerial orchestration of many elements that go far beyond conventional definitions of analytics. Marketing and Sales Analytics examines the experiences of sales and marketing leaders and practitioners who have successfully built high value analytics capabilities in multiple industries. Then, drawing on their experiences, top analytics consultant Cesar Brea introduces overarching frameworks and specific tools that can help you achieve the same levels of success in your own organization. Brea shows how to: Establish the ecosystemic conditions for analytic success Reconcile the diverse perspectives that impact analytics initiatives (Business v. IT, Sales v. Marketing, Analysts v. Creatives v. Managers, and Everyone v. Finance) Decide what success will look like Agree on the questions to ask Organize both internal and external data Establish operational flexibility, and balance flexibility with efficiency Recruit the right people and organize them optimally Intelligently decide what to do yourself, and what to hire vendors for Balance research, analytics, and testing Implement proven research, analytics, and testing strategies Deliver results through storytelling (and recognize its limitations) Control the biases that creep into analytics research Maintain momentum, implement governance, and keep score |
| examples of marketing analytics: Marketing Analytics: A Practitioner's Guide To Marketing Analytics And Research Methods Ashok Charan, 2015-05-20 The digital age has transformed the very nature of marketing. Armed with smartphones, tablets, PCs and smart TVs, consumers are increasingly hanging out on the internet. Cyberspace has changed the way they communicate, and the way they shop and buy. This fluid, de-centralized and multidirectional medium is changing the way brands engage with consumers.At the same time, technology and innovation, coupled with the explosion of business data, has fundamentally altered the manner we collect, process, analyse and disseminate market intelligence. The increased volume, variety and velocity of information enables marketers to respond with much greater speed, to changes in the marketplace. Market intelligence is timelier, less expensive, and more accurate and actionable.Anchored in this age of transformations, Marketing Analytics is a practitioner's guide to marketing management in the 21st century. The text devotes considerable attention to the way market analytic techniques and market research processes are being refined and re-engineered. Written by a marketing veteran, it is intended to guide marketers as they craft market strategies, and execute their day to day tasks. |
| examples of marketing analytics: Engaging Customers Using Big Data Arvind Sathi, 2017-03-15 Data is transforming how and where we market to our customers. Using a series of case studies from pioneers, this book will describe how each marketing function is undergoing fundamental changes, and provides practical guidance about how companies can learn the tools and techniques to take advantage of marketing analytics. |
| examples of marketing analytics: Marketing Analytics Robert W. Palmatier, J. Andrew Petersen, Frank Germann, 2022-03-24 All customers differ. All customers change. All competitors react. All resources are limited. Robert W. Palmatier's dynamic First Principles of Marketing framework provides the structure for this research-based, action-orientated guide to organizing analytics tools, marketing models and methodologies. When should you use a specific technique in data analytics? How does each new analytics technique improve performance? Which techniques are worth time and investment to implement? As organizations prioritize digital growth to better connect with customers, it is vital that you are able to respond confidently to these questions, enabling you to utilize marketing analytics to better understand your business and increase revenue. Marketing Analytics will help you to: · Learn how to contextualize models and statistical analysis within the foundational principles of marketing through the use of a problem-centric framework. · Understand technical analyses by engaging with a pertinent range of vivid examples, and a running case study to contextualize practical, jargon-free descriptions. · Embark on an applied learning pathway with a comprehensive companion website including datasets and walk-through videos on challenging tasks: bloomsbury.pub/marketing-analytics. · Take a software-agnostic approach to learning, enhanced by the provision of examples in free, open-source R and Tableau software. Authored by world-leading experts in marketing strategy, Marketing Analytics is the ideal textbook for advanced undergraduate, postgraduate and MBA students of marketing, and practitioners seeking to direct effective strategy from an analysis-based evidential approach. |
| examples of marketing analytics: Digital Marketing Analytics Kevin Hartman, 2020-09-15 From Kevin Hartman, Director of Analytics at Google, comes an essential guide for anyone seeking to collect, analyze, and visualize data in today's digital world (printed in black & white to keep print costs down). Even if you know nothing about digital marketing analytics, digital marketing analytics knows plenty about you. It's a fundamental, inescapable, and permanent cornerstone of modern business that affects the lives of analytics professionals and consumers in equal measure. This five-part book is an attempt to provide the context, perspective, and information needed to make analytics accessible to people who understand its reach and relevance and want to learn more. PART 1: The Day the Geeks Took Over The ubiquity of data analytics today isn't just a product of the past half-century's transformative and revolutionary changes in commerce and technology. Humanity has been developing, analyzing, and using data for millennia. Understanding where digital marketing analytics is now and where it will be in five, 10, or 50 years requires a holistic and historical view of our relationship and interaction with data. Part 1 looks at modern analysts and analytics in the context of its distinct historical epochs, each one containing major inflection points and laying a foundation for future advancements in the ART + SCIENCE that is modern data analytics. PART 2: Consumer/Brand Relationships The methods that brands use to build relationships with consumers - online video, search, display ads, and social media - give analysts a wealth of data about behaviors on these platforms. Knowing how to assess successful consumer/brand relationships and understanding a consumer's purchase journey requires a useable framework for parsing this data. In Part 2, we explore each digital channel in-depth, including a discussion of key metrics and measurements, how consumers interact with brands on each platform, and ways of organizing consumer data that enable actionable insights. PART 3: The Science of Analytics Part 3 focuses on understanding digital data creation, how brands use that data to measure digital marketing effectiveness, and the tools and skill sets analysts need to work effectively with data. While the contents are lightly technical, this section veers into the colloquial as we dive into multitouch attribution models, media mix models, incrementality studies, and other ways analysts conduct marketing measurement today. Part 3 also provides a useful framework for evaluating data analysis and visualization tools and explains the critical importance of digital marketing maturity to analysts and the companies for which they work. PART 4: The Art of Analytics Every analyst dreams of coming up with the Big Idea - the game-changing and previously unseen insight or approach that gives their organization a competitive advantage and their career a huge boost. But dreaming won't get you there. It requires a thoughtful and disciplined approach to analysis projects. In this part of the book, I detail the four elements of the Marketing Analytics Process (MAP): plan, collect, analyze, report. Part 4 also explains the role of the analyst, the six mutually exclusive and collectively exhaustive (MECE) marketing objectives, how to find context and patterns in collected data, and how to avoid the pitfalls of bias. PART 5: Storytelling with Data In Part 5, we dive headlong into the most important aspect of digital marketing analytics: transforming the data the analyst compiled into a comprehensive, coherent, and meaningful report. I outline the key characteristics of good visuals and the minutiae of chart design and provide a five-step process for analysts to follow when they're on their feet and presenting to an audience. |
| examples of marketing analytics: Marketing Analytics Rajkumar Venkatesan, Paul W. Farris, Ronald T. Wilcox, 2021-01-13 The authors of the pioneering Cutting-Edge Marketing Analytics return to the vital conversation of leveraging big data with Marketing Analytics: Essential Tools for Data-Driven Decisions, which updates and expands on the earlier book as we enter the 2020s. As they illustrate, big data analytics is the engine that drives marketing, providing a forward-looking, predictive perspective for marketing decision-making. The book presents actual cases and data, giving readers invaluable real-world instruction. The cases show how to identify relevant data, choose the best analytics technique, and investigate the link between marketing plans and customer behavior. These actual scenarios shed light on the most pressing marketing questions, such as setting the optimal price for one’s product or designing effective digital marketing campaigns. Big data is currently the most powerful resource to the marketing professional, and this book illustrates how to fully harness that power to effectively maximize marketing efforts. |
| examples of marketing analytics: Digital Marketing Dave Chaffey, Fiona Ellis-Chadwick, 2012-10-12 Now in its fifth edition, Digital Marketing (previously Internet Marketing) provides comprehensive, practical guidance on how companies can get the most out of digital media to meet their marketing goals. Digital Marketing links marketing theory with practical business experience through case studies and interviews from cutting edge companies such as eBay and Facebook, to help students understand digital marketing in the real world. |
| examples of marketing analytics: Marketing Analytics Santino Spencer, 2023-06-29 Are you new to marketing or struggling to get started with understanding marketing analytics? Do you want to be able to answer questions like - how do our marketing activities compare to the competition? Are your marketing resources properly allocated? Marketing Analytics is the guide you need! We will teach you how to establish your marketing analytics strategy in 7 easy steps. This guide is designed to provide you with all the tools you need in a concise, easy to understand format that will answer all your burning questions and get you on your way to establishing successful marketing analytics. Marketing analytics encompasses technologies and processes that enable marketing strategists to evaluate the success of their initiatives. Strategists accomplish this by measuring performance in the various channels they are present in, business metrics like marketing effectiveness, marking attribution, and return on investment (ROI). The purpose of marketing analytics is to collect data from across all marketing channels and consolidate it into a market view. Marketing Analytics provides you some pointers and tips for navigating a marketing analytics strategy, it also asks you to think and consider how you currently are strategizing. It helps you to evaluate where you are and what you, as an individual, need to change to push it to the next level. In a comprehensive step-by-step reference format, each chapter corresponds to a specific element of marketing analytics. The clear-cut organization makes it simple to follow along and refer back to areas you still feel confused about as you go. This guide is complete with coherent examples to help you distinguish between each element and log them into your long-term memory. YOU'LL LEARN: How to determine stakeholders Ways to navigate data integration The importance of key performance indicators Ways of implementing analytics The importance of data governance The purpose of conducting financial analysis The role of IT How to measure success What to look for with Vendors And much more! To help you on this journey of achieving the goal of becoming a marketing analyst, this guide goes through many actionable examples and strategies. As you press yourself to grow, you will find that there are so many experiences you have already had that will help formulate your ability to establish successful marketing analytics. Let's get started! |
| examples of marketing analytics: Pragmalytics Cesar A. Brea, 2012-10-30 The promise of marketing analytics in the age of Big Data is the ability to make your marketing efforts much more targetable, trackable, and testable. But in practice, realizing this promise is hard -- logically, technically, and especially organizationally. Pragmalytics helps you address this challenge with practical techniques and real-world examples, to help you better navigate the modern marketing forest among ever-denser thickets of data, channels, and tools. REACTIONS TO PRAGMALYTICS This is really good... full of common sense approaches that not only blend analytics and creativity, but hold everyone's thinking to a behavioral set of imperatives... a grounded human starting place that lets you make better decisions. -Ben Kline, ex CSO/CMO, Leo Burnett This is a must read for business executives confronting the digital imperative. Brea's lively prose is on-point, provocative, and actionable. -Bob Neuhaus, Global Sector Head - Financial Services, TNS This book presents practical advice with good examples and an easy-to-read style. I recommend it to senior marketing executives trying to approach multi-channel strategies in a more manageable way. -Jeffrey Hupe, Founder, Phronesis Group, LLC, and former VP Global Strategy and Innovation, The Nielsen Group |
| examples of marketing analytics: Hands-On Data Science for Marketing Yoon Hyup Hwang, 2019-03-29 Optimize your marketing strategies through analytics and machine learning Key FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learnLearn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segmentsWho this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples. |
| examples of marketing analytics: Creating Value with Data Analytics in Marketing Peter C. Verhoef, Edwin Kooge, Natasha Walk, Jaap E. Wieringa, 2021-11-07 The key competing texts are practitioner-focused ‘how to’ guides, whilst our book combines rigorous theory with practical insight and examples, with authors from both the academic and business world, making it more adoptable as a student text; Unlike other books on the subject, this has a customer focus and an exploration of how big data can add value to customers as well as organisations; Enables readers to move from big data to big solutions by demonstrating how to integrate data analytics into specific goals and processes for implementation; Highly successful and well regarded both for students and practitioners |
| examples of marketing analytics: Marketing Analytics Roadmap Jerry Rackley, 2015-05-30 Many managers view marketing as a creative endeavor, not something that is measurable or manageable by numbers. But today’s leaders in the C-suite demand greater accountability. They want to know that they are getting a return on their marketing investment. And to get that ROI number, you need analytics. This expectation is intimidating for the many sales and marketing managers who rely on marketing instincts, not metrics, to do their work. But Marketing Analytics Roadmap: Methods, Metrics, and Tools demonstrates that employing analytics isn't just a way to keep the CEO off your back. It improves marketing results and ensures marketers a seat at the table where big decisions get made. In this book, analytics expert Jerry Rackley shows you how to understand and implement a sound marketing analytics process that helps eliminate the guesswork about the results produced by your marketing efforts. The result? You will acquire—and keep—more customers. Even better, you'll find that an analytics process helps the entire organization make better decisions, and not just marketers. Marketing Analytics Roadmap explains: How to use analytics to create marketing and sales metrics that guide your actions and provide valuable feedback on your efforts How to structure and use dashboards to report marketing results How to put industry-leading analytics software and other tools to good use How Big Data is shaping the marketing analytics landscape Sales and marketing teams that master marketing analytics will find them a powerful servant that enables agility, raises effectiveness, and creates confidence. Marketing Analytics Roadmap shows you how to build a well-planned and executed marketing analytics strategy that will enhance the credibility of your marketing team and help you not only get a seat at the big-decisions table, but keep it once there. |
| examples of marketing analytics: The Data Loom Stephen Few, 2019-05-15 Contrary to popular myth, we do not yet live in the Information Age. At best, we live the Data Age, obsessed with the production, collection, storage, dissemination, and monetization of digital data. But data, in and of itself, isn't valuable. Data only becomes valuable when we make sense of it. We rely on information professionals to help us understand data, but most fail in their efforts. Why? Not because they lack intelligence or tools, but mostly because they lack the necessary skills. Most information professionals have been trained primarily in the use of data analysis tools (Tableau, PowerBI, Qlik, SAS, Excel, R, etc.), but even the best tools are only useful in the hands of skilled individuals. Anyone can pick up a hammer and pound a nail, but only skilled carpenters can use a hammer to build a reliable structure. Making sense of data is skilled work, and developing those skills requires study and practice. Weaving data into understanding involves several distinct but complementary thinking skills. Foremost among them are critical thinking and scientific thinking. Until information professionals develop these capabilities, we will remain in the dark ages of data. This book is for information professionals, especially those who have been thrust into this important work without having a chance to develop these foundational skills. If you're an information professional and have never been trained to think critically and scientifically with data, this book will get you started. Once on this path, you'll be able to help usher in an Information Age worthy of the name. |
| examples of marketing analytics: Introduction to Marketing Analytics Prof. Dr. R. Gopal, Prof. Dr. Gagandeep Kaur Nagra, Dr. Priya Vij, 2024-10-15 Introduction to Marketing Analytics delves into the foundational elements of marketing, known as the 4Ps—Product, Price, Place, and Promotion—and expands upon them to include additional key components crucial for services marketing, such as People, Process, and Physical Evidence. These elements are vital for companies to develop coherent marketing strategies that not only attract new customers but also build long-term loyalty among existing ones. The rise of digital technologies has significantly transformed how companies engage with consumers and conduct market research. Big data analytics now allows for personalized marketing efforts, creating campaigns offering organizations the ability to better understand and respond to customer journeys. Moreover, the book highlights the growing role of artificial intelligence (AI) and machine learning in modern marketing strategies. By integrating these advanced technologies, businesses can better meet their customers’ evolving needs, outpacing the competition. It covers various analysis techniques, such as marketing mix modelling, that help organizations understand the impact of different marketing activities on sales and other key performance indicators (KPIs). Through real-life examples and case studies, this book highlights a practical guide for professionals looking to apply data-driven marketing strategies to drive growth, innovation, and sustainable success in a constantly changing market landscape. |
| examples of marketing analytics: Marketing Strategy Robert W. Palmatier, Shrihari Sridhar, 2020-12-31 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 design |
| examples of marketing analytics: Marketing Analytics Practitioner's Guide, The - Volume 1: Brand And Consumer Ashok Charan, 2023-09-13 As the use of analytics becomes increasingly important in today's business landscape, The Marketing Analytics Practitioner's Guide (MAPG) provides a thorough understanding of marketing management concepts and their practical applications, making it a valuable resource for professionals and students alike.The four-volume compendium of MAPG provides an in-depth look at marketing management concepts and their practical applications, equipping readers with the knowledge and skills needed to effectively inform daily marketing decisions and strategy development and implementation. It seamlessly blends the art and science of marketing, reflecting the discipline's evolution in the era of data analytics. Whether you're a seasoned marketer or new to the field, the MAPG is an essential guide for mastering the use of analytics in modern marketing practices.Volume I is focused on Brand and Consumer. Part I of this volume is dedicated to understanding the concepts and methods of brand sensing and brand equity. It delves into the analytic techniques used to track and profile brand image, and explains the key components of brand equity, how to measure it, and what factors drive it. It provides readers with a comprehensive framework for measuring and understanding brand equity and the tools to pursue its growth.Part II of this volume focuses on understanding consumers through qualitative and quantitative research methods, segmentation, customer satisfaction, customer value management, consumer panels, consumer analytics and big data. The volume covers the analytic tools used to extract insights from consumer transactions, which are becoming increasingly important in today's data-driven world. It also covers the use of consumer analytics and big data specifically within consumer markets. |
| examples of marketing analytics: Marketing Analytics A. Mansurali, P. Mary Jeyanthi, 2023-02-02 With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions. This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more. This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use. |
| examples of marketing analytics: Web Analytics Avinash Kaushik, 2007-07-30 Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company’s bottom line. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| examples of marketing analytics: Sport Business Analytics C. Keith Harrison, Scott Bukstein, 2016-11-18 Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. |
| examples of marketing analytics: The AI Marketing Canvas Raj Venkatesan, Jim Lecinski, 2021-05-18 This book offers a direct, actionable plan CMOs can use to map out initiatives that are properly sequenced and designed for success—regardless of where their marketing organization is in the process. The authors pose the following critical questions to marketers: (1) How should modern marketers be thinking about artificial intelligence and machine learning? and (2) How should marketers be developing a strategy and plan to implement AI into their marketing toolkit? The opening chapters provide marketing leaders with an overview of what exactly AI is and how is it different than traditional computer science approaches. Venkatesan and Lecinski, then, propose a best-practice, five-stage framework for implementing what they term the AI Marketing Canvas. Their approach is based on research and interviews they conducted with leading marketers, and offers many tangible examples of what brands are doing at each stage of the AI Marketing Canvas. By way of guidance, Venkatesan and Lecinski provide examples of brands—including Google, Lyft, Ancestry.com, and Coca-Cola—that have successfully woven AI into their marketing strategies. The book concludes with a discussion of important implications for marketing leaders—for your team and culture. |
| examples of marketing analytics: Marketing ROI James Lenskold, 2003-08-22 ROI (Return on Investment) is today's key business tool for measuring how effectively money was spent--yet few marketing managers receive any ROI training at all. Marketing ROIchanges all that, showing marketing pros at every level how to use ROI and other financial metrics to support their strategic decision making. This comprehensive book details how an accurate working knowledge of ROI is essential for using the latest marketing measurements, and provides insights for gaining the greatest competitive advantage from the skilled use and understanding of ROI concepts. |
| examples of marketing analytics: Lean Analytics Alistair Croll, Benjamin Yoskovitz, 2024-02-23 Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products |
| examples of marketing analytics: Measure What Matters John Doerr, 2018-04-24 #1 New York Times Bestseller Legendary venture capitalist John Doerr reveals how the goal-setting system of Objectives and Key Results (OKRs) has helped tech giants from Intel to Google achieve explosive growth—and how it can help any organization thrive. In the fall of 1999, John Doerr met with the founders of a start-up whom he'd just given $12.5 million, the biggest investment of his career. Larry Page and Sergey Brin had amazing technology, entrepreneurial energy, and sky-high ambitions, but no real business plan. For Google to change the world (or even to survive), Page and Brin had to learn how to make tough choices on priorities while keeping their team on track. They'd have to know when to pull the plug on losing propositions, to fail fast. And they needed timely, relevant data to track their progress—to measure what mattered. Doerr taught them about a proven approach to operating excellence: Objectives and Key Results. He had first discovered OKRs in the 1970s as an engineer at Intel, where the legendary Andy Grove (the greatest manager of his or any era) drove the best-run company Doerr had ever seen. Later, as a venture capitalist, Doerr shared Grove's brainchild with more than fifty companies. Wherever the process was faithfully practiced, it worked. In this goal-setting system, objectives define what we seek to achieve; key results are how those top-priority goals will be attained with specific, measurable actions within a set time frame. Everyone's goals, from entry level to CEO, are transparent to the entire organization. The benefits are profound. OKRs surface an organization's most important work. They focus effort and foster coordination. They keep employees on track. They link objectives across silos to unify and strengthen the entire company. Along the way, OKRs enhance workplace satisfaction and boost retention. In Measure What Matters, Doerr shares a broad range of first-person, behind-the-scenes case studies, with narrators including Bono and Bill Gates, to demonstrate the focus, agility, and explosive growth that OKRs have spurred at so many great organizations. This book will help a new generation of leaders capture the same magic. |
| examples of marketing analytics: Marketing Analytics: Creating Customer Centric Culture Joseph B. Rivera, 2020-02-17 A game-changing approach to marketing by an experienced author, speaker and businessman Joseph B. Rivera. Joseph B. Rivera has first-hand experience in business. He has learned everything through hard work and perseverance, and has inspired quite a lot of entrepreneurs, businessmen, executives, employees, and business students to challenge themselves in this modern era of commerce. For the first time, Joseph B. Rivera offers his years of experience and wisdom in this one compact, very accessible and enduring masterpiece. MARKETING ANALYTICS: CREATING CUSTOMER-CENTRIC CULTURE helps you to create a transformative culture toward excellence in your business. Whether you are an executive, businessman, business owner, investor, marketer, trainer, speaker or a student of marketing, you will be proud of what you will learn. When applied right, you will change the way products and services are designed, created and offered to the world. This book teaches you how to meaningfully connect emotionally and practically to your consumers. Remember, it is not just all about the money. Here, Joseph has put together his passion, insights, observation and experience to mentor you: ✔️How to understand the needs of the market. ✔️How to position your business. ✔️How to overcome competition. ✔️How to revolutionize your business. Learn the art or marketing analytics, and be a game changer. |
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 Apache …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; …
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
