For over 25 years, marketers have longed to connect with their customers and prospects as individuals. As the volume of customer communications across touch points grows exponentially and consumers' attention spans shrink by the day, delivering maximally relevant, individualized experiences has become an imperative. And while the one-to-one dream h.
Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.
For over 25 years, marketers have longed to connect with their customers and prospects as individuals. As the volume of customer communications across touch points grows exponentially and consumers' attention spans shrink by the day, delivering maximally relevant, individualized experiences has become an imperative. And while the one-to-one dream had been unattainable for years, machine learning and real-time processing have made it possible today. In this book--now in its second edition--discover what one-to-one personalization is all about, how it's evolved and what the future entails. Learn how it's driven by machine learning, delivered across channels and powered by in-depth customer data brought together in a customer data platform (CDP). Get inspired by the potential for your business and gain insights on how to develop your own personalization strategy and program. Discover how to turn the one-to-one dream into a reality.
How ed tech was born: Twentieth-century teaching machines--from Sidney Pressey's mechanized test-giver to B. F. Skinner's behaviorist bell-ringing box. Contrary to popular belief, ed tech did not begin with videos on the internet. The idea of technology that would allow students to "go at their own pace" did not originate in Silicon Valley. In Teaching Machines, education writer Audrey Watters offers a lively history of predigital educational technology, from Sidney Pressey's mechanized positive-reinforcement provider to B. F. Skinner's behaviorist bell-ringing box. Watters shows that these machines and the pedagogy that accompanied them sprang from ideas--bite-sized content, individualized instruction--that had legs and were later picked up by textbook publishers and early advocates for computerized learning. Watters pays particular attention to the role of the media--newspapers, magazines, television, and film--in shaping people's perceptions of teaching machines as well as the psychological theories underpinning them. She considers these machines in the context of education reform, the political reverberations of Sputnik, and the rise of the testing and textbook industries. She chronicles Skinner's attempts to bring his teaching machines to market, culminating in the famous behaviorist's efforts to launch Didak 101, the "pre-verbal" machine that taught spelling. (Alternate names proposed by Skinner include "Autodidak," "Instructomat," and "Autostructor.") Telling these somewhat cautionary tales, Watters challenges what she calls "the teleology of ed tech"--the idea that not only is computerized education inevitable, but technological progress is the sole driver of events.
Marketers are harnessing the enormous power of AI to drive unprecedented results The world of marketing is undergoing major change. Sophisticated algorithms can test billions of marketing messages and measure results, and shift the weight of campaigns—all in real time. What’s next? A complete transformation of marketing as we know it, where machines themselves design and implement customized advertising tactics at virtually every point of digital contact.The Invisible Brand provides an in-depth exploration of the risks and rewards of this epochal shift—while delivering the information and insight you need to stay ahead of the game. Renowned technologist William Ammerman draws from his decades of experience at the forefront of digital marketing to provide a roadmap to our data-driven future. You’ll learn how data and AI will forge a new level of persuasiveness and influence for reshaping consumers’ buying decisions. You’ll understand the technology behind these changes and see how it is already at work in digital assistants, recommendation engines and digital advertising. And you’ll find unmatched insight into how to harness the power of artificial intelligence for maximum results.As we enter the age of mass customization of messaging, power and influence will go to those who know the consumer best. Whether you are a marketing executive or concerned citizen, The Invisible Brand provides everything you need to understand how brands are harnessing the extraordinary amounts of data at their disposal—and capitalizing on it with AI.
To succeed at B2B marketing today, you must excel across all areas: from getting your message out, to generating demand, to enabling sales teams. New technologies and new techniques make excellence possible. Now, top B2B marketer Kim Ann King brings together all the best practices and tools you need to make excellence real. In The Complete Guide to B2B Marketing, King helps you succeed by focusing on the three pillars of cutting-edge B2B marketing: automation, personalization, and experimentation. Drawing on her pioneering experience at companies like Akamai and Open Market, King shows how to: Systematically assess your context and customer, via personas, profiles, and other powerful techniques Choose among today's panoply of marketing options, tools, and techniques Build a more agile B2B marketing organization, and link its goals more tightly to strategy More accurately estimate marketing spend and ROI Systematically optimize demand generation and many other key functions Leverage higher-value approaches to web/mobile, SEO, and customer community-building Gain more value from corporate standards and your creative services vendors Discover what worked and what didn't, and use this knowledge to improve more quickly You'll find comprehensive, actionable resources, including best-practices checklists for every tactic, vendor checklists for evaluating new marketing technologies, a complete corporate marketing plan outline, and a start-to-finish marketing communications case study. If you're a B2B marketer, you'll find The Complete Guide to B2B Marketing invaluable – whatever your company's size, product, service, or industry.
Every business on the planet is trying to maximize the value created by its customers Learn how to do it, step by step, in this newly revised Fourth Edition of Managing Customer Experience and Relationships: A Strategic Framework. Written by Don Peppers and Martha Rogers, Ph.D., recognized for decades as two of the world's leading experts on customer experience issues, the book combines theory, case studies, and strategic analyses to guide a company on its own quest to position its customers at the very center of its business model, and to "treat different customers differently." This latest edition adds new material including: How to manage the mass-customization principles that drive digital interactions How to understand and manage data-driven marketing analytics issues, without having to do the math How to implement and monitor customer success management, the new discipline that has arisen alongside software-as-a-service businesses How to deal with the increasing threat to privacy, autonomy, and competition posed by the big tech companies like Facebook, Amazon, and Google Teaching slide decks to accompany the book, author-written test banks for all chapters, a complete glossary for the field, and full indexing Ideal not just for students, but for managers, executives, and other business leaders, Managing Customer Experience and Relationships should prove an indispensable resource for marketing, sales, or customer service professionals in both the B2C and B2B world.
According to Infosys, 86% of consumers surveyed indicated that personalized content has some impact on what they purchase and 25% said that personalization plays a large role in their purchases. And yet, looking at the data, two things stand out: Most companies say that personalizing the customer experience is a critical "must have," and they have the statistics to back it up. Very few companies believe they are delivering enough personalized content, or deliver it well. What's holding these companies back from their personalization goals? And how can you avoid the pitfalls and make personalization possible with your own enterprise content? In this book, global content strategy expert Val Swisher and senior content strategist Regina Lynn Preciado show you exactly what it takes to deliver personalized experiences at scale. You'll learn: Why personalized content is imperative to the enterprise Why so many companies fail to deliver - and how to avoid the pitfalls The five dimensions of content standardization How to bring people, technology, and process together The impact of big data and artificial intelligence The only way to deliver personalized content at scale is to automate the process at the point of delivery. And for that to work, you've got to change how you "do" content. The Personalization Paradox: Why Companies Fail (and How to Succeed) at Delivering Personalized Experiences at Scale shows you how.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.
