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| data driven marketing examples: 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. |
| data driven marketing examples: Data Driven: Harnessing Data and AI to Reinvent Customer Engagement Tom Chavez, Chris O’Hara, Vivek Vaidya, 2018-10-05 Axiom Business Book Award Silver Medalist in Business TechnologyThe indispensable guide to data-powered marketing from the team behind the data management platform that helps fuel Salesforce―the #1 customer relationship management (CRM) company in the worldA tectonic shift in the practice of marketing is underway. Digital technology, social media, and e-commerce have radically changed the way consumers access information, order products, and shop for services. Using the latest technologies―cloud, mobile, social, internet of things (IoT), and artificial intelligence (AI)―we have more data about consumers and their needs, wants, and affinities than ever before. Data Driven will show you how to:●Target and delight your customers with unprecedented accuracy and success●Bring customers closer to your brand and inspire them to engage, purchase, and remain loyal●Capture, organize, and analyze data from every source and activate it across every channel●Create a data-powered marketing strategy that can be customized for any audience●Serve individual consumers with highly personalized interactions●Deliver better customer service for the best customer experience●Improve your products and optimize your operating systems●Use AI and IoT to predict the future direction of marketsYou’ll discover the three principles for building a successful data strategy and the five sources of data-driven power. You’ll see how top companies put these data-driven strategies into action: how Pandora used second- and third-hand data to learn more about its listeners; how Georgia-Pacific moved from scarcity to abundance in the data sphere; and how Dunkin’ Brands leveraged CRM data as a force multiplier for customer engagement. And if you’re wondering what the future holds, you’ll receive seven forecasts to better prepare you for what may come next. Sure to be a classic, Data Driven is a practical road map to the modern marketing landscape and a toolkit for success in the face of changes already underway and still to come. |
| data driven marketing examples: Big Data Marketing Lisa Arthur, 2013-10-07 Leverage big data insights to improve customer experiences and insure business success Many of today's businesses find themselves caught in a snarl of internal data, paralyzed by internal silos, and executing antiquated marketing approaches. As a result, consumers are losing patience, shareholders are clamoring for growth and differentiation, and marketers are left struggling to untangle the massive mess. Big Data Marketing provides a strategic road map for executives who want to clear the chaos and start driving competitive advantage and top line growth. Using real-world examples, non-technical language, additional downloadable resources, and a healthy dose of humor, Big Data Marketing will help you discover the remedy offered by data-driven marketing. Explains how marketers can use data to learn what they need to know Details strategies to drive marketing relevance and Return On Marketing Investment (ROMI) Provides a five-step approach in the journey to a more data-driven marketing organization Author Lisa Arthur, the Chief Marketing Officer for Teradata Applications, the leader in integrated marketing software, meets with thousands of CMOs and marketing professionals annually through public speaking and events Big Data Marketing reveals patterns in your customers' behavior and proven ways to elevate customer experiences. Leverage these insights to insure your business's success. |
| data driven marketing examples: Data Driven Marketing For Dummies David Semmelroth, 2013-10-07 Embrace data and use it to sell and market your products Data is everywhere and it keeps growing and accumulating. Companies need to embrace big data and make it work harder to help them sell and market their products. Successful data analysis can help marketing professionals spot sales trends, develop smarter marketing campaigns, and accurately predict customer loyalty. Data Driven Marketing For Dummies helps companies use all the data at their disposal to make current customers more satisfied, reach new customers, and sell to their most important customer segments more efficiently. Identifying the common characteristics of customers who buy the same products from your company (or who might be likely to leave you) Tips on using data to predict customer purchasing behavior based on past performance Using customer data and marketing analytics to predict when customers will purchase certain items Information on how data collected can help with merchandise planning Breaking down customers into segments for easier market targeting Building a 360 degree view of a customer base Data Driven Marketing For Dummies assists marketing professionals at all levels of business in accelerating sales through analytical insights. |
| data driven marketing examples: 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. |
| data driven marketing examples: Direct, Digital & Data-Driven Marketing Lisa Spiller, 2020-01-09 In this latest edition of her classic text, Lisa Spiller takes an insightful, in-depth look at contemporary marketing concepts, tactics, and techniques and the dynamic innovations that continue to drive and shape this multi-faceted, multi-dimensional field. Direct, Digital, and Data-Driven Marketing recognizes the growth of the various digital formats as the newest interactive channels for conducting modern marketing. But it does not overlook the traditional principles of direct marketing still relevant today. This book examines the field both as it once was and as it is evolving. With plenty of learning features online resources, the Fifth Edition provides an engaging journey, which will leave any marketing student with a thorough knowledge of how all kinds of businesses manage regular communication with their customer base and target demographic. |
| data driven marketing examples: Creating a Data-Driven Organization Carl Anderson, 2015-07-23 What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company ... Through interviews and examples from data scientists and analytics leaders in a variety of industries ... Anderson explains the analytics value chain you need to adopt when building predictive business models--Publisher's description. |
| data driven marketing examples: Data-Driven Marketing Content Lee Wilson, 2019-06-19 This practical content guide empowers businesses to understand, identify and act on big-data opportunities, producing superior business insights for prolific marketing gains. |
| data driven marketing examples: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it! |
| data driven marketing examples: Programmatic Advertising Oliver Busch, 2015-11-26 This fundamental guide on programmatic advertising explains in detail how automated, data-driven advertising really works in practice and how the right adoption leads to a competitive advantage for advertisers, agencies and media. The new way of planning, steering and measuring marketing may still appear complex and threatening but promising at once to most decision makers. This collaborative compendium combines proven experience and best practice in 22 articles written by 45 renowned experts from all around the globe. Among them Dr. Florian Heinemann/Project-A, Peter Würtenberger/Axel-Springer, Deirdre McGlashan/MediaCom, Dr. Marc Grether/Xaxis, Michael Lamb/MediaMath, Carolin Owen/IPG, Stefan Bardega/Zenith, Arun Kumar/Cadreon, Dr. Ralf Strauss/Marketingverband, Jonathan Becher/SAP and many more great minds. |
| data driven marketing examples: Intelligent Data-driven Marketing Mathias Elsässer, 2022 |
| data driven marketing examples: The Data-Driven Project Manager Mario Vanhoucke, 2018-03-27 Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as dynamic scheduling) which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or dynamic scheduling) via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles |
| data driven marketing examples: The Big Data-Driven Business Russell Glass, Sean Callahan, 2014-11-24 Get the expert perspective and practical advice on big data The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples—from Nate Silver to Copernicus, and Apple to Blackberry—to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehensive and accessible guide on how to win customers, beat competitors, and boost the bottom line with big data. The marketplace has entered an era where the customer holds all the cards. With unprecedented choice in both the consumer world and the B2B world, it's imperative that businesses gain a greater understanding of their customers and prospects. Big data is the key to this insight, because it provides a comprehensive view of a company's customers—who they are, and who they may be tomorrow. The Big Data-Driven Business is a complete guide to the future of business as seen through the lens of big data, with expert advice on real-world applications. Learn what big data is, and how it will transform the enterprise Explore why major corporations are betting their companies on marketing technology Read case studies of big data winners and losers Discover how to change privacy and security, and remodel marketing Better information allows for better decisions, better targeting, and better reach. Big data has become an indispensable tool for the most effective marketers in the business, and it's becoming less of a competitive advantage and more like an industry standard. Remaining relevant as the marketplace evolves requires a full understanding and application of big data, and The Big Data-Driven Business provides the practical guidance businesses need. |
| data driven marketing examples: Big Data and AI Driven Marketing Analytics Jeen Su Lim, John Heinrichs, Kee Sook Lim, 2020-04-10 |
| data driven marketing examples: Data-Driven Personas Bernard J. Jansen, Joni Salminen, 2022-05-31 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. |
| data driven marketing examples: 10 Sectors of Digital Marketing John Maxwell, 2023-04-09 Introducing 10 Sectors of Digital Marketing, the ultimate guide to understanding the basics of digital marketing. This e-book from Bookzon World provides a comprehensive overview of the 10 best parts of digital marketing, allowing you to develop a strong foundation for your online marketing efforts. Inside this e-book, you'll discover the key concepts, strategies, and techniques that make digital marketing so effective, including SEO, content marketing, social media marketing, email marketing, and more. With clear explanations and real-world examples, 10 Sectors of Digital Marketing is the perfect resource for anyone looking to master the art of online marketing. Whether you're new to the world of digital marketing or looking to expand your knowledge and skills, this e-book is an essential resource that you won't want to miss. So don't wait – get your copy today and start building your digital marketing skills with confidence! |
| data driven marketing examples: Predictive Analytics and Generative AI for Data-Driven Marketing Strategies Hemachandran K, Debdutta Choudhury, Raul Villamarin Rodriguez, Jorge A. Wise, Revathi T, 2024-12-10 In providing an in-depth exploration of cutting-edge technologies and how they are used to support data-driven marketing strategies and empower organizations to make the right decisions, Predictive Analytics and Generative AI for Data-Driven Marketing Strategies includes real-world case studies and examples from diverse marketing domains. This book demonstrates how predictive analytics and generative AI have been successfully applied to solve marketing challenges and drive tangible results. This book showcases emerging trends in predictive analytics and generative AI for marketing, and their potential impact on the future of data-driven marketing. This book is meant for professionals and scholars to gather the skills and resources to use predictive analytics and generative AI effectively for marketing strategies. This book: • Examines the different predictive analytics models and algorithms, such as regression analysis, decision trees, and neural networks, and demonstrates how they may be utilized to get insightful conclusions from marketing data. • Includes generative AI techniques, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), showcasing how these techniques can generate synthetic data for marketing insights and decision-making. • Highlights the importance of data-driven marketing choices and illustrates how generative AI and predictive analytics may be quite useful in this context. • Integrates the principles of data science with marketing concepts, offering a cohesive understanding of how predictive analytics and generative AI can power data-driven marketing decisions. • Presents the recent advances in predictive analytics and generative AI and discusses how they can affect the area of data-driven marketing. |
| data driven marketing examples: DATA-DRIVEN MARKETING IN THE AGE OF ARTIFICIAL INTELLIGENCE Dr. Raghava R. Gundala, Dr Pujari, Dr. G. VIJAYAKUMAR, 2024-03-20 In order to maximize the effectiveness of brand communication and propel the expansion of a company, data-driven marketing is a strategic strategy that makes use of consumer data. It entails gathering, analyzing, and making use of data from a variety of sources in order to obtain insights about the behavior, tastes, and trends of different types of customers. This information is then used to create marketing strategies, messaging, and campaigns to particular audiences, which ultimately results in marketing efforts that are more personalized and successful. The expansion of online platforms and the introduction of digital technology have both played a vital role in the development of data-driven marketing. Today's organizations have access to large volumes of data that are created by interactions with customers, activity on social media platforms, visits to websites, and other digital touchpoints. The abundance of data that is available to marketers gives them with important information on the demographics, interests, purchasing history, and online activity of their target audience population. The use of data has evolved into an essential component of successful marketing campaigns in this era of digital technology. The use of data-driven marketing completely transforms the method in which firms comprehend and interact with their clientele clients.[1] Businesses have the ability to get significant insights into the behavior, tastes, and trends of their customers by using the power of data analytics. This introduction serves as a doorway to explore the ideas, practices, and advantages of data-driven marketing. It gives organizations the ability to harness data to drive growth, improve customer connections, and maintain a competitive advantage in a market that is highly competitive. We invite you to accompany us on a trip into the realm of data-driven marketing, where each click, interaction, and transaction holds the key to unlocking new possibilities and driving success. Now that we have a better understanding of data-driven marketing, we will investigate the ways in which companies may efficiently gather, analyze, and make use of data in order to personalize their marketing efforts. |
| data driven marketing examples: Data-Driven Marketing for Strategic Success Rosário, Albérico Travassos, Cruz, Rui Nunes, Moniz, Luis Bettencourt, 2024-08-09 In the field of modern marketing, a pivotal challenge emerges as traditional strategies grapple with the complexities of an increasingly data-centric world. Marketers, researchers, and business consultants find themselves at a crossroads, navigating the intricate intersection of data science and strategic marketing practices. This challenge serves as the catalyst for Data-Driven Marketing for Strategic Success, a guide designed to address the pressing issues faced by academic scholars and professionals alike. This comprehensive exploration unveils the transformative power of data in reshaping marketing strategies, offering a beacon of strategic success in a sea of uncertainty. This book transcends the realm of traditional marketing literature. It stands as a useful resource, not merely adding elements to ongoing research but shaping the very future of how researchers, practitioners, and students engage with the dynamic world of data-driven marketing. It is strategically tailored to reach a diverse audience, offering valuable insights to academics and researchers exploring advanced topics, practitioners in the marketing industry seeking practical applications, and graduate students studying data science, marketing, and business analytics. Policymakers, ethicists, and industry regulators will find the dedicated section on ethical considerations particularly relevant, emphasizing the importance of responsible practices in the data-driven marketing landscape. |
| data driven marketing examples: The Data-driven Organization Jonas Rashedi, 2022-12-11 Data has become an indispensable success factor for every company. However, the road towards a data-driven organization is paved with numerous challenges. This book presents a process model for the path to a data-driven company and provides recommendations for the design of all relevant fields of action: Which structures need to be created? Which systems and processes have proven beneficial? How can the quality of the data be ensured and what requirements exist for a data-driven organization in the areas of governance and communication? And last but not least: How can employees be brought along on the journey and what implications does the data-driven organization have for our corporate culture? The book presents an orientation and action framework for the strategic and operational design of a data-driven organization and is valuable for managers who are involved in data management in companies and organizations. |
| data driven marketing examples: 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. |
| data driven marketing examples: Contemporary Issues in Digital Marketing Outi Niininen, 2021-11-29 This book presents a comprehensive overview of the key topics, best practices, future opportunities and challenges in the Digital Marketing discourse. With contributions from world-renowned experts, the book covers: Big Data, Artificial Intelligence and Analytics in Digital Marketing Emerging technologies and how they can enhance User Experience How ‘digital’ is changing servicescapes Issues surrounding ethics and privacy Current and future issues surrounding Social Media Key considerations for the future of Digital Marketing Case studies and examples from real-life organisations Unique in its rigorous, research-driven and accessible approach to the subject of Digital Marketing, this text is valuable supplementary reading for advanced undergraduate and postgraduate students studying Digital and Social Media Marketing, Customer Experience Management, Digital Analytics and Digital Transformation. |
| data driven marketing examples: Data-Driven Marketing Mark Jeffery, To paraphrase the old adage: Half of marketing dollars are effective, we just don t know which half! This book changes the marketing game so you ll really know what s working and what s not. The 15 metrics, along with the case examples, are an authoritative toolkit for making better decisions to create new markets, drive revenue, increase customer satisfaction, and improve profitability. John M. Boushy, former CEO, Ameristar Casinos, Inc. A groundbreaking combination of research, frameworks, and pragmatic advice for both controlling and radically improving marketing. A must-read for the entire marketing organization, from the CMO to the front lines. Barry Judge, Executive Vice President and Chief Marketing Officer, Best Buy Business-to-consumer marketing and business-to-business marketing are very different. Through detailed examples, this outstanding book shows how to apply data-driven marketing in both worlds for real results. This book is for anyone in business, not just marketing, who wants to step up the performance of their marketing. David G. Bills, Senior Vice President and Chief Marketing and Sales Officer, DuPont Every year, baseball teams go to places like Florida and Arizona to run through the basics which are the cornerstone of performance excellence. This book is the marketing equivalent of taking all those ground balls. An essential read for every marketer who cares about and wants to improve upon the science of their craft. Derek Ungless, Executive Vice President and Chief Marketing Officer, DSW Shoe WarehouseData-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know |
| data driven marketing examples: Data-Driven Storytelling Nathalie Henry Riche, Christophe Hurter, Nicholas Diakopoulos, Sheelagh Carpendale, 2018-03-28 This book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. |
| data driven marketing examples: 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. |
| data driven marketing examples: Data Governance Dimitrios Sargiotis, |
| data driven marketing examples: Trendology C. Kerns, 2014-12-01 In this, the first data-driven guide to real time marketing, Chris Kerns outlines the value of RTM via a comprehensive social data performance analysis. He lays out best practices for measuring RTM, injects a data-driven mindset into every step of its methodology, and shows how marketers can grow RTM into a daily win for brands across the globe. |
| data driven marketing examples: TRADITIONAL AND DATA-DRIVEN PREDICTIVE STATISTICAL MODELS Dr. Neeta Kishor Dhane, 2021-07-23 The desire to know the unknown has always been one of the human characteristics that distinguish humans from other living things on the earth. The past is known but cannot be changed, and hence is if no interest. The present is happening and everyone is witnessing it and therefore it is not exciting. But the future is both unknown and perhaps therefore uncertain, and is therefore both interesting and exciting. Using past experience for predicting the unknown future was initially treated as an art because it require careful choice of parts of the past that will make prediction both easy and accurate, and there were times when it was felt that it is impossible to formulate a method for this. Prediction was then not considered to be scientific empirical sciences that learn from scientist and professionals realized the scientific nature of the ability to predict. What then began as the preparation for developing a prediction formula involved finding common patterns in past data and their consequences so that the consequence can be predicted as soon as the relevant pattern is observed. At the same time the discipline of statistics developed the concept and methodology for building statistical models. With experience in the development and applications of different models, scientists and researchers identify models as belonging to four different classes namely, the class of descriptive models, the class of diagnostic models, the class of predictive models, and the class of prescriptive or prognostic models. The scientific or theoretical activity of building models and analyzing data accordingly is known as analytics. It has therefore been recognized that there are four classes of analytics, namely descriptive analytics, diagnostic analytics, prescriptive analytics and predictive analytics. These four classes are defined briefly for convenience of the reader. |
| data driven marketing examples: Mastering Marketing Data Science Iain Brown, 2024-04-26 Unlock the Power of Data: Transform Your Marketing Strategies with Data Science In the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers, Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively. Comprehensive Coverage: From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science. Practical Applications: Engage with real-world examples, hands-on exercises in both Python & SAS, and actionable insights to apply in your marketing campaigns. Expert Guidance: Benefit from Dr. Iain Brown's decade of experience as he shares cutting-edge techniques and ethical considerations in marketing data science. Future-Ready Skills: Learn about the latest advancements, including generative AI, to stay ahead in the rapidly evolving marketing landscape. Accessible Learning: Tailored for both beginners and seasoned professionals, this book ensures a smooth learning curve with a clear, engaging narrative. Mastering Marketing Data Science is designed as a comprehensive how-to guide, weaving together theory and practice to offer a dynamic, workbook-style learning experience. Dr. Brown's voice and expertise guide you through the complexities of marketing data science, making sophisticated concepts accessible and actionable. |
| data driven marketing examples: Unlocking Success: The Art of Strategic Marketing in the Digital Age Samuel Inbaraja S, 2023-08-04 Unlocking Success: The Art of Strategic Marketing in the Digital Age is not just theory; it incorporates several case studies that illustrate real-world application of strategies in various business contexts. The book also offers a special section on 'Boost Your Stamina with Easyfit's Personalized Fitness Journey,' connecting the concepts of strategic marketing to personal health and wellbeing. This comprehensive guide is a valuable resource for marketers, business owners, entrepreneurs, and students who aspire to understand and succeed in the dynamic world of digital marketing. Its practical insights and case studies bring marketing strategies to life, setting you on the right path towards unlocking success. |
| data driven marketing examples: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| data driven marketing examples: Marketing Management Support Systems Berend Wierenga, Gerrit Harm van Bruggen, 2000-04-30 The challenge for the future is designing marketing management support systems that combine these newer technologies into maximally effective systems that constitute a real competitive edge in the marketplace. This book aims to help spur this implementation by offering a framework for matching the demand and supply of information in order to guide the functional design and development of marketing management support systems in specific situations. |
| data driven marketing examples: Data-Driven Public Relations Research Jim Eggensperger, Natalie Redcross, 2018-09-03 The public relations industry is undergoing a revolution in using data to define promotional programs, to measure influence and to address the needs of clients with more precision than ever. Applying tools that range from online surveys to social-media listening to applying big data with sophisticated algorithms, today’s PR professionals are data-driven in virtually everything they do. Data-Driven Public Relations Research is the first book for PR students and practitioners to offer an overview of these new practices as well as a glimpse into the future of these new applications, including big data and some of the applications from real-world PR campaigns and strategic planning. It includes contemporary cases involving brand name companies who are blazing new trails in the use of metrics in public relations. This book presents a practical, accessible approach that requires no prior training or experience, with easy to follow, step-by-step measurement examples from existing campaigns. Using Excel, the book enables readers to export lessons from the classroom to the office, where use of statistical packages is rare and can give PR practitioners the advantage over competitors. This pragmatic approach helps readers apply metrics to PR problems such as: Finding the best target audiences Understanding audience communication needs and preferences How best to present research outcomes How to manage major projects with specialized research firms. Accompanying electronic resources for the book include sample answers to the book’s discussion questions, PowerPoint lecture slides for instructors and sample research exercises using Excel. |
| data driven marketing examples: Data-Driven Business Models for the Digital Economy Rado Kotorov, 2020-04-21 Today the fastest growing companies have no physical assets. Instead, they create innovative digital products and new data-driven business models. They capture huge market share fast and their capitalizations skyrocket. The success of these digital giants is pushing all companies to rethink their business models and to start digitizing their products and services. Whether you are a new start-up building a digital product or service, or an employee of an established company that is transitioning to digital, you need to consider how digitization has transformed every aspect of management. Data-driven business models scale not through asset accumulation and product standardization, but through disaggregation of supply and demand. The winners in the new economy master the demand for one and the supply to millions. Throughout the book the author illustrates with examples and use cases how the market competition has changed and how companies adept to the new rules of the game. The economic levers of scale and scope are also different in the digital economy and companies have to learn new tactics how to achieve and sustain their competitive advantage. While data is at the core of all digital business models, the monetization strategies vary across products, services and business models. Our Monetization Matrix is a model that helps managers, marketers, sales professionals, and technical product designers to align the digital product design with the data-driven business model. |
| data driven marketing examples: Recommendation Engines Michael Schrage, 2020-09-01 How companies like Amazon, Netflix, and Spotify know what you might also like: the history, technology, business, and societal impact of online recommendation engines. Increasingly, our technologies are giving us better, faster, smarter, and more personal advice than our own families and best friends. Amazon already knows what kind of books and household goods you like and is more than eager to recommend more; YouTube and TikTok always have another video lined up to show you; Netflix has crunched the numbers of your viewing habits to suggest whole genres that you would enjoy. In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences you might also like. |
| data driven marketing examples: 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. |
| data driven marketing examples: New Horizons for a Data-Driven Economy José María Cavanillas, Edward Curry, Wolfgang Wahlster, 2016-04-04 In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment. |
| data driven marketing examples: Advertising: Methods, Research and Practices Noprita Herari, Ulani Yunus, Santosh Swarnakar, Dr. Linie Darli, Suchivrat Arya, Aijaz Ahmad Mir, Md. Nuruddin Pier Shihab, Lakshita Pant, Dr. Shrinkhala Upadhyaya, Dr. Mona Gupta, Dr. Chetna Bhatia, Dr. Anjali Gupta, Manna Dey, Dr. Abhilasha R, Gadamsetty Surya, Manisha Khanal, Akshoy Kumar Das Chakravorty, Dr. Seema Shukla, Ms. Ashiqha Sultana, Dr. Jisha K, Saranya P S, Dr. Kongkona Dutta, Dr. Shafia Jan, Mohammad Azhar Ishaq, Ritika Sanwal, Vani Harpanahalli, Nagunuri. Srinivas, P. Ganesh Anand, Dr. Ravi Kant Vajpai, Dr. Alka Sanyal, Mr. Adarsh Kumar, Dr. Rachna Patel, Dr. Samuel Okechukwu Omeje, Buike Oparaugo, Dr. Obiora C. Igwebuike, Jyoti Dutta, Dr. Kuldeep Siwach, Alex Arghya Adhikari, Devaki V, Dr. Archana Sharma, Arpan Paul, Vimal Kr. Singh, Tran Minh Tung, Sanchita Chatterjee, Dr. Rohit Ganguly, Dr. Manpreet Kaur, Vaishali Sinha, Shailja Singh, Manishi Shriwas, Dr. C. M. Vinaya Kumar, Dr. Shruti Mehrotra, Dr. Reshmi Naskar, Sumedha Halder, 2024-05-25 Millions of people are exposed to thousands of brands daily through different means, and we may categorise some as advertisements. William M. O’Barr calls it “conditioning of the consumers.” Advertisements can be analysed from different perspectives. For instance, Philip Nelson, in his study “Advertising as Information,” analyses advertisements based on the capacity of advertisements to direct the information toward the consumers, helping them separate one brand from another. Demetrios Vakratsas and Tim Ambler, in their study “How Advertising Works: What Do We Really Know?” discussed factors like “consumer’s belief and attitudes” and “behavioral effects” leading to purchasing behavior and brand choice. Research and advertising are intertwined, and it helps to explore the horizon of advertising that helps to improve the advertising industry. The book “Advertising: Methods, Research and Practices” offers a collection of concepts and perspectives like brand identity, buying habits, online advertising, digital gaming, political advertising, contemporary Indian advertising, new age advertising, the impact of advertising on food habits and consumption preferences, AI intervention in advertising, unethical advertising practices, chocolate advertising, marketing of toys, Digital marketing and advertising. The chapters also include metaphorical language in advertising, advertising appeals, e-sport marketing, sustainable advertising, celebrity and advertising, subliminal advertising, MSME and advertising, women in advertising, public service advertising, advertisement for positive behavior change, advertisements on menstrual health and hygiene and many more. Collectively, the chapters would help in understanding the different perspectives of advertising as practice as well as the dimensions of research requirements. |
| data driven marketing examples: Drilling Down: Turning Customer Data into Profits with a Spreadsheet Jim Novo, 2004-06-18 I spend a lot of time in marketing-oriented discussion lists. If you do, you probably also sense the incredible frustration of people who keep asking about using their customer data to retain customers and increase profits. Everybody knows they should be doing it, but can't find out how to do it. Consultants and agencies make this process sound like some kind of black magic, something you can't possibly do yourself. I disagree. I think the average business owner can do a perfectly decent job creating profiles and using them to retain customers and drive profits. Thus the book. The examples provided are Internet specific, but the methods can be used in any business where customer data is available. This book is about the down-and-dirty, nitty-gritty art of taking chunks of data generated by your customers and making sense of it, getting it to speak to you, creating insight into what types of marketing or general business actions you can take to make your business more profitable. We'll be talking about action-oriented ideas you can generate on your own to drive sales and profits, ideas that will reveal themselves by analyzing your own customer data, using only a spreadsheet. We have all heard how important it is to collect customer data, to know your customer. What I don't hear much about is what exactly you DO with all that data once you have collected it. How is it used? What exactly is Drilling Down into the data supposed to tell me, and what am I looking for when I get there? For that matter, what data should I be collecting and how will I use it when I have it? And how much is this process going to cost me? The following list outlines what you will learn and be able to do after reading the Drilling Down book: --What data is important to collect about a customer and what data is not --How to create action-oriented customer profiles with an Excel spreadsheet --How to use these profiles to plan marketing promotions --How to use these profiles to define the future value of your customers --How to use these profiles to measure the general health of your business --How to use these profiles to encourage customers to do what you want them to --How to predict when a customer is about to defect and leave you --How to increase your profits while decreasing your marketing costs --How to design high ROI (Return on Investment) marketing promotions How to blow away investors with predictions of the future profitability of your business Table of Contents Chapter 1: What's a Customer Profile? Chapter 2: Data-Driven Marketing - Customer Retention Basics Chapter 3: The Language of Data, The Science of Profit Chapter 4: Interactivity Changes the Rules of the Game Chapter 5: How to Build a Customer Profiling Spreadsheet Chapter 6: How to Profile (Score) Your Customers Chapter 7: Marketing Using Customer Scores - Basic Approach Chapter 8: Using Customer Characteristics and Multiple Scores Chapter 9: Watching Scores over Time - Customer LifeCycles Chapter 10: Customer Scoring Grids - Profiling on Steroids Chapter 11: Calculating and Using LifeTime Value in Promotions Chapter 12: Turning Profiles into Profits - the Staging Area Chapter 13: Turning Profiles into Profits - the Financial Model Chapter 14: Turning Profiles into Profits - Financial Tweaks Chapter 15: Measuring Success in Best Customer Promotions Chapter 16: Some Final Thoughts Seasonal Adjustments to Marketing Promotions Don't Fight Customer Behavior CRM Software and Customer Scoring Data-Driven Marketing Program Descriptions There's more! Automate the basic customer scoring process on large groups of customers. Use the software included free with this edition! Windows OS and MS Access and Excel required to run the software. |
| data driven marketing examples: Creating Value with Big Data Analytics Peter C. Verhoef, Edwin Kooge, Natasha Walk, 2016-01-08 Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
