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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.
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ITShades.com has been founded with singular aim of engaging and enabling the best and brightest of businesses, professionals and students with opportunities, learnings, best practices, collaboration and innovation from IT industry. This document brings together a set of latest data points and publicly available information relevant for Insurance Industry. We are very excited to share this content and believe that readers will benefit from this periodic publication immensely.
As digital transformation becomes increasingly central to effective corporate strategy, today's students must learn how information systems provide the foundation for modern business enterprises. Known for its rich Canadian content and focus on active learning, Introduction to Information Systems, Sixth Canadian Edition shows students how they can use IS to help their current or future employers increase profitability, improve customer service, manage daily operations, and drive impact in their markets. This course demonstrates that IT is the backbone of any business, whether a student is majoring in accounting, finance, marketing, human resources, production/operations management, or MIS. In short, students will learn how information systems provide the foundation for all modern organizations, whether they are public sector, private sector, for-profit, or not-for-profit.
Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs
Regulating Digital Industries is the first book to address the tech backlash within a coherent policy framework. It treats competition, privacy and free speech as objectives that must be pursued in a coordinated fashion by a dedicated industry regulator. It contains detailed discussions of current policy controversies involving social media companies, search engines, electronic commerce platforms and mobile apps. It argues for new laws and regulations to promote competition, privacy and free speech in tech and outlines the structure and powers of a regulatory agency able to develop, implement and enforce digital rules for the twenty-first century. Deeply informed by the history of regulation and antitrust in the United States, it brings to bear insights from the breakup of AT&T and the Microsoft case and from broadcasting and financial services regulation to enrich the discussion of remedies to the failure of tech competition, the massive invasion of privacy by digital firms and the information disorder perpetuated by social media platforms. It offers a comprehensive summary of regulatory reform efforts in the United States and abroad and shows how accomplishing the goals of these reform efforts requires the establishment of a single digital agency with jurisdiction to reconcile and balance the complementary and conflicting goals of promoting competition, protecting privacy, and preserving free speech in digital industries. It discusses in detail how a digital regulatory agency would be structured and the powers it would need to have. It confronts head on some of the challenges in establishing a strong digital regulator including the First Amendment roadblock that limits government authority over digital speech and the judicial opposition to the expansion of the administrative state. It is essential reading for policymakers, public interest advocates, industry representatives, academic researchers and the general public interested in a coherent policy approach to today’s tech industry discontents.